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Session-based example using dressipi dataset and XLNet architecture #849

Merged
merged 30 commits into from
Nov 24, 2022
Merged

Session-based example using dressipi dataset and XLNet architecture #849

merged 30 commits into from
Nov 24, 2022

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rnyak
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@rnyak rnyak commented Nov 2, 2022

This PR is addressing session-based example creation task in #734.

Currently

  • This PR modifies the existing session-based example notebook. We could remove the custom biLSTM class and we can directly use tf.keras.layers.Bidirectional instead.
  • we can run XLNET architecture however weight-tying and loader does not work properly (see blockers below) unless we go with workaround solutions.

Blockers:
we need these two tickets to be solved

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GitHub pull request #849 of commit 72a64f478e0208b520c4a121b11e1ac7710cdcee, no merge conflicts.
Running as SYSTEM
Setting status of 72a64f478e0208b520c4a121b11e1ac7710cdcee to PENDING with url https://10.20.13.93:8080/job/merlin_models/1701/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 72a64f478e0208b520c4a121b11e1ac7710cdcee^{commit} # timeout=10
Checking out Revision 72a64f478e0208b520c4a121b11e1ac7710cdcee (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 72a64f478e0208b520c4a121b11e1ac7710cdcee # timeout=10
Commit message: "session-based example with Transformer"
 > git rev-list --no-walk e839e2b5fbcac6d03199493b1c33fc12a967fdde # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins13504666351335199062.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
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Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
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Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
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Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/1/merlin-models-0.9.0+24.g72a64f47.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.0,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.0,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@5905283777ff5ebd748a1c91b7c9fde5710ae775,merlin-models==0.9.0+24.g72a64f47,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='4022098995'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-j0uu1dri
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-j0uu1dri
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (3.19.5)
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Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.4)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (8.1.3)
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Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.7.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (3.1.2)
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[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-v_ksdp0c

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-v_ksdp0c

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 59579f2c46006fcb22795623ee9400c658166670

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

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[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/test-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 833 items


tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss                              [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py .................................       [ 12%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 16%]

.....................                                                    [ 19%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 19%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 19%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 21%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 21%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 21%]

tests/unit/tf/core/test_aggregation.py .........                         [ 22%]

tests/unit/tf/core/test_base.py ..                                       [ 22%]

tests/unit/tf/core/test_combinators.py s....................             [ 25%]

tests/unit/tf/core/test_encoder.py ..                                    [ 25%]

tests/unit/tf/core/test_index.py ...                                     [ 25%]

tests/unit/tf/core/test_prediction.py ..                                 [ 26%]

tests/unit/tf/core/test_tabular.py ......                                [ 26%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 27%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 27%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 27%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 27%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 27%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 27%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 27%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 27%]

[ 27%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 27%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 28%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 28%]

tests/unit/tf/inputs/test_continuous.py .......                          [ 29%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]

........                                                                 [ 34%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 36%]

tests/unit/tf/layers/test_queue.py ..............                        [ 37%]

tests/unit/tf/losses/test_losses.py .......................              [ 40%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 41%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 44%]

tests/unit/tf/models/test_base.py s........................              [ 47%]

tests/unit/tf/models/test_benchmark.py ..                                [ 47%]

tests/unit/tf/models/test_ranking.py ..................................  [ 51%]

tests/unit/tf/models/test_retrieval.py ................................. [ 55%]

..........................................                               [ 60%]

tests/unit/tf/outputs/test_base.py ......                                [ 61%]

tests/unit/tf/outputs/test_classification.py ......                      [ 62%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 63%]

tests/unit/tf/outputs/test_regression.py ..                              [ 63%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 64%]

tests/unit/tf/outputs/test_topk.py .                                     [ 64%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 64%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 66%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 67%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 67%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 68%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 68%]

tests/unit/tf/transformers/test_block.py .....................           [ 71%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 72%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 72%]

tests/unit/tf/transforms/test_features.py s............................. [ 76%]

.......................s......                                           [ 79%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 81%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 84%]

tests/unit/tf/utils/test_batch.py ....                                   [ 84%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 85%]

tests/unit/torch/test_dataset.py .........                               [ 86%]

tests/unit/torch/test_public_api.py .                                    [ 86%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 87%]

tests/unit/torch/features/test_continuous.py ..                          [ 87%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 89%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 92%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 93%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f81c63a4520>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f81c63a4520>

cell = {'cell_type': 'code', 'execution_count': 45, 'id': '337e6653-38a7-4a9e-b300-46bd0213b30e', 'metadata': {'execution': {...   learning_rate=LEARNING_RATE\n)\nmodel.compile(run_eagerly=False, optimizer=optimizer)\nmodel.fit(loader, epochs=2)'}

cell_index = 87

exec_reply = {'buffers': [], 'content': {'ename': 'InvalidArgumentError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'b899595a...e, 'engine': 'b899595a-7ac6-418b-8586-2a51026bc62b', 'started': '2022-11-02T15:51:14.541885Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           optimizer = tf.keras.optimizers.Adam(

E               learning_rate=LEARNING_RATE

E           )

E           model.compile(run_eagerly=False, optimizer=optimizer)

E           model.fit(loader, epochs=2)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mInvalidArgumentError�[0m                      Traceback (most recent call last)

E           Cell �[0;32mIn [45], line 5�[0m

E           �[1;32m      1�[0m optimizer �[38;5;241m=�[39m tf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(

E           �[1;32m      2�[0m     learning_rate�[38;5;241m=�[39mLEARNING_RATE

E           �[1;32m      3�[0m )

E           �[1;32m      4�[0m model�[38;5;241m.�[39mcompile(run_eagerly�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, optimizer�[38;5;241m=�[39moptimizer)

E           �[0;32m----> 5�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mloader�[49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m2�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:856�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    853�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    854�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 856�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    858�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    859�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1107�[0m, in �[0;36mModel.call�[0;34m(self, inputs, targets, training, testing, output_context)�[0m

E           �[1;32m   1104�[0m     outputs, context �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_call_child(�[38;5;28mself�[39m�[38;5;241m.�[39mpre, outputs, context)

E           �[1;32m   1106�[0m �[38;5;28;01mfor�[39;00m block �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mblocks:

E           �[0;32m-> 1107�[0m     outputs, context �[38;5;241m=�[39m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43m_call_child�[49m�[43m(�[49m�[43mblock�[49m�[43m,�[49m�[43m �[49m�[43moutputs�[49m�[43m,�[49m�[43m �[49m�[43mcontext�[49m�[43m)�[49m

E           �[1;32m   1109�[0m �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mpost:

E           �[1;32m   1110�[0m     outputs, context �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_call_child(�[38;5;28mself�[39m�[38;5;241m.�[39mpost, outputs, context)

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1136�[0m, in �[0;36mModel._call_child�[0;34m(self, child, inputs, context)�[0m

E           �[1;32m   1133�[0m �[38;5;28;01mif�[39;00m �[38;5;28many�[39m(�[38;5;28misinstance�[39m(sub, ModelBlock) �[38;5;28;01mfor�[39;00m sub �[38;5;129;01min�[39;00m child�[38;5;241m.�[39msubmodules):

E           �[1;32m   1134�[0m     �[38;5;28;01mdel�[39;00m call_kwargs[�[38;5;124m"�[39m�[38;5;124mfeatures�[39m�[38;5;124m"�[39m]

E           �[0;32m-> 1136�[0m outputs �[38;5;241m=�[39m �[43mcall_layer�[49m�[43m(�[49m�[43mchild�[49m�[43m,�[49m�[43m �[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mcall_kwargs�[49m�[43m)�[49m

E           �[1;32m   1137�[0m �[38;5;28;01mif�[39;00m �[38;5;28misinstance�[39m(outputs, Prediction):

E           �[1;32m   1138�[0m     targets �[38;5;241m=�[39m outputs�[38;5;241m.�[39mtargets �[38;5;28;01mif�[39;00m outputs�[38;5;241m.�[39mtargets �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m �[38;5;28;01melse�[39;00m context�[38;5;241m.�[39mtargets

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:437�[0m, in �[0;36mcall_layer�[0;34m(layer, inputs, args, **kwargs)�[0m

E           �[1;32m    433�[0m         call_fn �[38;5;241m=�[39m �[38;5;28mtype�[39m(layer)�[38;5;241m.�[39mcall

E           �[1;32m    435�[0m         filtered_kwargs �[38;5;241m=�[39m filter_kwargs(filtered_kwargs, call_fn, �[38;5;241m�[39m�[38;5;241m�[39m_k)

E           �[0;32m--> 437�[0m �[38;5;28;01mreturn�[39;00m �[43mlayer�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfiltered_kwargs�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/base.py:136�[0m, in �[0;36mModelOutput.__call__�[0;34m(self, inputs, args, **kwargs)�[0m

E           �[1;32m    133�[0m     inputs �[38;5;241m=�[39m tf_utils�[38;5;241m.�[39mcall_layer(�[38;5;28mself�[39m�[38;5;241m.�[39mpre, inputs, �[38;5;241m�[39m�[38;5;241m�[39mkwargs)

E           �[1;32m    135�[0m �[38;5;66;03m# super call�[39;00m

E           �[0;32m--> 136�[0m outputs �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43mModelOutput�[49m�[43m,�[49m�[43m �[49m�[38;5;28;43mself�[39;49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[38;5;21;43m__call__�[39;49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mkwargs�[49m�[43m)�[49m

E           �[1;32m    138�[0m �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mpost:

E           �[1;32m    139�[0m     outputs �[38;5;241m=�[39m tf_utils�[38;5;241m.�[39mcall_layer(�[38;5;28mself�[39m�[38;5;241m.�[39mpost, outputs, �[38;5;241m�[39m�[38;5;241m�[39mkwargs)

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/base.py:114�[0m, in �[0;36mModelOutput.call�[0;34m(self, inputs, training, testing, **kwargs)�[0m

E           �[1;32m    113�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mcall�[39m(�[38;5;28mself�[39m, inputs, training�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, testing�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, �[38;5;241m�[39m�[38;5;241m�[39mkwargs):

E           �[0;32m--> 114�[0m     �[38;5;28;01mreturn�[39;00m �[43mtf_utils�[49m�[38;5;241;43m.�[39;49m�[43mcall_layer�[49m�[43m(�[49m

E           �[1;32m    115�[0m �[43m        �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mto_call�[49m�[43m,�[49m�[43m �[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[43mtraining�[49m�[38;5;241;43m=�[39;49m�[43mtraining�[49m�[43m,�[49m�[43m �[49m�[43mtesting�[49m�[38;5;241;43m=�[39;49m�[43mtesting�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mkwargs�[49m

E           �[1;32m    116�[0m �[43m    �[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:437�[0m, in �[0;36mcall_layer�[0;34m(layer, inputs, args, **kwargs)�[0m

E           �[1;32m    433�[0m         call_fn �[38;5;241m=�[39m �[38;5;28mtype�[39m(layer)�[38;5;241m.�[39mcall

E           �[1;32m    435�[0m         filtered_kwargs �[38;5;241m=�[39m filter_kwargs(filtered_kwargs, call_fn, �[38;5;241m�[39m�[38;5;241m�[39m_k)

E           �[0;32m--> 437�[0m �[38;5;28;01mreturn�[39;00m �[43mlayer�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfiltered_kwargs�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/classification.py:330�[0m, in �[0;36mEmbeddingTablePrediction.call�[0;34m(self, inputs, training, **kwargs)�[0m

E           �[1;32m    329�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mcall�[39m(�[38;5;28mself�[39m, inputs, training�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, �[38;5;241m�[39m�[38;5;241m*�[39mkwargs) �[38;5;241m-�[39m�[38;5;241m>�[39m tf�[38;5;241m.�[39mTensor:

E           �[0;32m--> 330�[0m     logits �[38;5;241m=�[39m �[43mtf�[49m�[38;5;241;43m.�[39;49m�[43mmatmul�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mtable�[49m�[38;5;241;43m.�[39;49m�[43mtable�[49m�[38;5;241;43m.�[39;49m�[43membeddings�[49m�[43m,�[49m�[43m �[49m�[43mtranspose_b�[49m�[38;5;241;43m=�[39;49m�[38;5;28;43;01mTrue�[39;49;00m�[43m)�[49m

E           �[1;32m    331�[0m     logits �[38;5;241m=�[39m tf�[38;5;241m.�[39mnn�[38;5;241m.�[39mbias_add(logits, �[38;5;28mself�[39m�[38;5;241m.�[39mbias)

E           �[1;32m    333�[0m     �[38;5;28;01mreturn�[39;00m logits

E

E           �[0;31mInvalidArgumentError�[0m: Exception encountered when calling layer "embedding_table_prediction" (type EmbeddingTablePrediction).

E

E           Matrix size-incompatible: In[0]: [1024,32], In[1]: [6663,24] [Op:MatMul]

E

E           Call arguments received by layer "embedding_table_prediction" (type EmbeddingTablePrediction):

E             • inputs=tf.Tensor(shape=(1024, 32), dtype=float32)

E             • training=False

E             • kwargs={'testing': 'False', 'features': {'f_47_list_seq': '<tf.RaggedTensor [[11, 0, 0],\n [17, 0, 0],\n [2, 0, 0],\n ...,\n [14, 0, 0],\n [7, 0, 0],\n [14, 0, 0]]>', 'f_68_list_seq': '<tf.RaggedTensor [[13, 0, 0],\n [51, 0, 0],\n [30, 0, 0],\n ...,\n [16, 0, 0],\n [41, 0, 0],\n [17, 0, 0]]>', 'item_id_list_seq': '<tf.RaggedTensor [[17, 0, 0],\n [25, 0, 0],\n [90, 0, 0],\n ...,\n [31, 0, 0],\n [43, 0, 0],\n [19, 0, 0]]>'}}

E           InvalidArgumentError: Exception encountered when calling layer "embedding_table_prediction" (type EmbeddingTablePrediction).

E

E           Matrix size-incompatible: In[0]: [1024,32], In[1]: [6663,24] [Op:MatMul]

E

E           Call arguments received by layer "embedding_table_prediction" (type EmbeddingTablePrediction):

E             • inputs=tf.Tensor(shape=(1024, 32), dtype=float32)

E             • training=False

E             • kwargs={'testing': 'False', 'features': {'f_47_list_seq': '<tf.RaggedTensor [[11, 0, 0],\n [17, 0, 0],\n [2, 0, 0],\n ...,\n [14, 0, 0],\n [7, 0, 0],\n [14, 0, 0]]>', 'f_68_list_seq': '<tf.RaggedTensor [[13, 0, 0],\n [51, 0, 0],\n [30, 0, 0],\n ...,\n [16, 0, 0],\n [41, 0, 0],\n [17, 0, 0]]>', 'item_id_list_seq': '<tf.RaggedTensor [[17, 0, 0],\n [25, 0, 0],\n [90, 0, 0],\n ...,\n [31, 0, 0],\n [43, 0, 0],\n [19, 0, 0]]>'}}


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-02 15:50:42.395963: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-02 15:50:45.746044: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-02 15:50:45.746214: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-02 15:50:45.747113: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-02 15:50:45.747169: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-02 15:50:45.747794: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-02 15:50:45.747839: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-02 15:50:45.748443: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-02 15:50:45.748492: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-02 15:51:06.909770: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8500

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

_______________ test_usecase_incremental_training_layer_freezing _______________


tb = <testbook.client.TestbookNotebookClient object at 0x7f81c6be0280>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_incremental_training_layer_freezing(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py:22:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f81c6be0280>

cell = {'cell_type': 'code', 'execution_count': 8, 'id': '791e06ec-c0cb-4c0f-9e41-7e5c8fa1dc4e', 'metadata': {'execution': {'...: 'model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))\nmodel.fit(day_1, batch_size=1024, epochs=1)'}

cell_index = 13

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '9e40b7...e, 'engine': '9e40b7b8-9fee-4cf6-9853-0af9c7e1e0e1', 'started': '2022-11-02T15:51:39.345148Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))

E           model.fit(day_1, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [8], line 2�[0m

E           �[1;32m      1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))

E           �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:856�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    853�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    854�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 856�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    858�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    859�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1059�[0m, in �[0;36mModel._maybe_build�[0;34m(self, inputs)�[0m

E           �[1;32m   1057�[0m             child�[38;5;241m.�[39m_feature_shapes �[38;5;241m=�[39m feature_shapes

E           �[1;32m   1058�[0m             child�[38;5;241m.�[39m_feature_dtypes �[38;5;241m=�[39m feature_dtypes

E           �[0;32m-> 1059�[0m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43m_maybe_build�[49m�[43m(�[49m�[43minputs�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1077�[0m, in �[0;36mModel.build�[0;34m(self, input_shape)�[0m

E           �[1;32m   1075�[0m �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mblocks:

E           �[1;32m   1076�[0m     �[38;5;28;01mtry�[39;00m:

E           �[0;32m-> 1077�[0m         layer�[38;5;241m.�[39mbuild(input_shape)

E           �[1;32m   1078�[0m     �[38;5;28;01mexcept�[39;00m �[38;5;167;01mTypeError�[39;00m:

E           �[1;32m   1079�[0m         t, v, tb �[38;5;241m=�[39m sys�[38;5;241m.�[39mexc_info()

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:582�[0m, in �[0;36mParallelBlock.build�[0;34m(self, input_shape)�[0m

E           �[1;32m    578�[0m �[38;5;28;01mfor�[39;00m name, layer �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mparallel_dict�[38;5;241m.�[39mitems():

E           �[1;32m    579�[0m     layer_input_shape �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_maybe_filter_layer_inputs_using_schema(

E           �[1;32m    580�[0m         name, layer, input_shape

E           �[1;32m    581�[0m     )

E           �[0;32m--> 582�[0m     �[43mlayer�[49m�[38;5;241;43m.�[39;49m�[43mbuild�[49m�[43m(�[49m�[43mlayer_input_shape�[49m�[43m)�[49m

E           �[1;32m    583�[0m     layer_out_shape �[38;5;241m=�[39m layer�[38;5;241m.�[39mcompute_output_shape(layer_input_shape)

E           �[1;32m    584�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mautomatic_pruning �[38;5;129;01mand�[39;00m layer_out_shape �[38;5;241m==�[39m {}:

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:109�[0m, in �[0;36mModelBlock.build�[0;34m(self, input_shapes)�[0m

E           �[1;32m    108�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mbuild�[39m(�[38;5;28mself�[39m, input_shapes):

E           �[0;32m--> 109�[0m     �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mblock�[49m�[38;5;241;43m.�[39;49m�[43mbuild�[49m�[43m(�[49m�[43minput_shapes�[49m�[43m)�[49m

E           �[1;32m    111�[0m     �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m�[38;5;241m.�[39mbuild, �[38;5;124m"�[39m�[38;5;124m_is_default�[39m�[38;5;124m"�[39m):

E           �[1;32m    112�[0m         �[38;5;28mself�[39m�[38;5;241m.�[39m_build_input_shape �[38;5;241m=�[39m input_shapes

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:129�[0m, in �[0;36mSequentialBlock.build�[0;34m(self, input_shape)�[0m

E           �[1;32m    121�[0m �[38;5;124;03m"""Builds the sequential block�[39;00m

E           �[1;32m    122�[0m

E           �[1;32m    123�[0m �[38;5;124;03mParameters�[39;00m

E           �[0;32m   (...)�[0m

E           �[1;32m    126�[0m �[38;5;124;03m    The input shape, by default None�[39;00m

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E           �[1;32m    128�[0m �[38;5;28mself�[39m�[38;5;241m.�[39m_maybe_propagate_context(input_shape)

E           �[0;32m--> 129�[0m �[43mbuild_sequentially�[49m�[43m(�[49m�[38;5;28;43mself�[39;49m�[43m,�[49m�[43m �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mlayers�[49m�[43m,�[49m�[43m �[49m�[43minput_shape�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:833�[0m, in �[0;36mbuild_sequentially�[0;34m(self, layers, input_shape)�[0m

E           �[1;32m    831�[0m �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m layers:

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E           �[1;32m    835�[0m         t, v, tb �[38;5;241m=�[39m sys�[38;5;241m.�[39mexc_info()

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:582�[0m, in �[0;36mParallelBlock.build�[0;34m(self, input_shape)�[0m

E           �[1;32m    578�[0m �[38;5;28;01mfor�[39;00m name, layer �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mparallel_dict�[38;5;241m.�[39mitems():

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:582�[0m, in �[0;36mParallelBlock.build�[0;34m(self, input_shape)�[0m

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:364�[0m, in �[0;36mEmbeddingTable.build�[0;34m(self, input_shapes)�[0m

E           �[1;32m    362�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mbuild�[39m(�[38;5;28mself�[39m, input_shapes):

E           �[1;32m    363�[0m     �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtable�[38;5;241m.�[39mbuilt:

E           �[0;32m--> 364�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mtable�[49m�[38;5;241;43m.�[39;49m�[43mbuild�[49m�[43m(�[49m�[43minput_shapes�[49m�[43m)�[49m

E           �[1;32m    365�[0m     �[38;5;28;01mreturn�[39;00m �[38;5;28msuper�[39m(EmbeddingTable, �[38;5;28mself�[39m)�[38;5;241m.�[39mbuild(input_shapes)

E

E           �[0;31mResourceExhaustedError�[0m: failed to allocate memory [Op:AddV2]

E           ResourceExhaustedError: failed to allocate memory [Op:AddV2]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-02 15:51:33.469727: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-02 15:51:37.615636: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-02 15:51:37.615788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-02 15:51:37.616652: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-02 15:51:37.616709: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-02 15:51:37.617287: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-02 15:51:37.617336: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-02 15:51:37.617938: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-02 15:51:37.617986: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-02 15:51:39.663296: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 10027008/17069309952

2022-11-02 15:51:39.663345: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      2446401665

MaxInUse:                   2446401669

NumAllocs:                         101

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-02 15:51:39.663360: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-02 15:51:39.663368: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 1

2022-11-02 15:51:39.663375: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 15

2022-11-02 15:51:39.663380: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 2

2022-11-02 15:51:39.663386: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 2

2022-11-02 15:51:39.663391: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 2

2022-11-02 15:51:39.663397: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 1

2022-11-02 15:51:39.663403: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 1

2022-11-02 15:51:39.663408: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 1

2022-11-02 15:51:39.663414: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-02 15:51:39.663420: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 1

2022-11-02 15:51:39.663425: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 60720, 1

2022-11-02 15:51:39.663431: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 1

2022-11-02 15:51:39.663461: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 1

2022-11-02 15:51:39.663468: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 1

2022-11-02 15:51:39.663474: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 1

2022-11-02 15:51:39.663480: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 1

2022-11-02 15:51:39.663485: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 1

2022-11-02 15:51:39.663491: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 1

2022-11-02 15:51:39.663497: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 1

2022-11-02 15:51:39.663503: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 1

2022-11-02 15:51:39.663508: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 2

2022-11-02 15:51:39.663539: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 119 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 85 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:960: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 54 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filea3a5c7ij.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:614: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     60    24%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    3      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     15    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     40    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         114     10    91%

merlin/models/tf/blocks/optimizer.py                                   173     13    92%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   245     49    80%

merlin/models/tf/core/base.py                                          244     55    77%

merlin/models/tf/core/combinators.py                                   424     53    88%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       288     30    90%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   452     31    93%

merlin/models/tf/loader.py                                             243     73    70%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        707     76    89%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                425     35    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  107      2    98%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11297   2217    80%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 2 failed, 819 passed, 12 skipped, 1347 warnings in 1570.40s (0:26:10) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   test-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins17430561275749933700.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit c855fcba5c1fc18f38aa9b2027a155f56ed7b7f2, no merge conflicts.
Running as SYSTEM
Setting status of c855fcba5c1fc18f38aa9b2027a155f56ed7b7f2 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1741/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse c855fcba5c1fc18f38aa9b2027a155f56ed7b7f2^{commit} # timeout=10
Checking out Revision c855fcba5c1fc18f38aa9b2027a155f56ed7b7f2 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f c855fcba5c1fc18f38aa9b2027a155f56ed7b7f2 # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk 7fd5ae4a2b9979eb3090f99541528ff702e1c092 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins9300177806724881165.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+31.gc855fcba.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.2,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.2,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@61ca2edae832da4eb2c6b93390c24920e68de1ae,merlin-models==0.9.0+31.gc855fcba,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='3370988344'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-seut13yb
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-seut13yb
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 7059e2358683b8ed746065a883e3339e02d41b1e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+6.g7059e23) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+6.g7059e23) (0.55.1)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+6.g7059e23) (4.64.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+6.g7059e23) (1.10.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+6.g7059e23) (1.2.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+6.g7059e23) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+6.g7059e23) (1.3.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+6.g7059e23) (2022.5.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+6.g7059e23) (3.19.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+6.g7059e23) (21.3)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+6.g7059e23) (7.0.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+6.g7059e23) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+6.g7059e23) (0.4.3)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (1.2.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (1.7.0)
Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+6.g7059e23) (59.8.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+6.g7059e23) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+6.g7059e23) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+6.g7059e23) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+6.g7059e23) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+6.g7059e23) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+6.g7059e23) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+6.g7059e23) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+6.g7059e23) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+6.g7059e23) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+6.g7059e23) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+6.g7059e23) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+6.g7059e23) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+6.g7059e23) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+6.g7059e23-py3-none-any.whl size=118560 sha256=1b2d894a3fef09f7d8da4fd2fecd79e2d7c1969d252486f64b63e3dd6c5c9dde
  Stored in directory: /tmp/pip-ephem-wheel-cache-0wnm9ov9/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.8.0+5.g563be4b
    Uninstalling merlin-core-0.8.0+5.g563be4b:
      Successfully uninstalled merlin-core-0.8.0+5.g563be4b
Successfully installed merlin-core-0.8.0+6.g7059e23

[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-83ye6og6

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-83ye6og6

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.8.0+6.g7059e23)

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+3.g8e7edbaf) (1.8.1)

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.0.2+2.g61ca2ed)

Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (2022.3.0)

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[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/test-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 836 items


tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss                              [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py .................................       [ 12%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 16%]

.....................                                                    [ 19%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 19%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 19%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 21%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 21%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 21%]

tests/unit/tf/core/test_aggregation.py .........                         [ 22%]

tests/unit/tf/core/test_base.py ..                                       [ 22%]

tests/unit/tf/core/test_combinators.py s.....................            [ 25%]

tests/unit/tf/core/test_encoder.py ..                                    [ 25%]

tests/unit/tf/core/test_index.py ...                                     [ 25%]

tests/unit/tf/core/test_prediction.py ..                                 [ 26%]

tests/unit/tf/core/test_tabular.py ......                                [ 26%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 27%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 27%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 27%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 27%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 27%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 27%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 27%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 27%]

[ 27%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 27%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 28%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 28%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 29%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]

........                                                                 [ 34%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 36%]

tests/unit/tf/layers/test_queue.py ..............                        [ 38%]

tests/unit/tf/losses/test_losses.py .......................              [ 40%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 41%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 44%]

tests/unit/tf/models/test_base.py s........................              [ 47%]

tests/unit/tf/models/test_benchmark.py ..                                [ 47%]

tests/unit/tf/models/test_ranking.py ..................................  [ 51%]

tests/unit/tf/models/test_retrieval.py ................................. [ 55%]

...........................................                              [ 60%]

tests/unit/tf/outputs/test_base.py ......                                [ 61%]

tests/unit/tf/outputs/test_classification.py ......                      [ 62%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 63%]

tests/unit/tf/outputs/test_regression.py ..                              [ 64%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 64%]

tests/unit/tf/outputs/test_topk.py .                                     [ 64%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 64%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 66%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 67%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 68%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 68%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 68%]

tests/unit/tf/transformers/test_block.py .....................           [ 71%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 72%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 72%]

tests/unit/tf/transforms/test_features.py s............................. [ 76%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 81%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 84%]

tests/unit/tf/utils/test_batch.py ....                                   [ 84%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 85%]

tests/unit/torch/test_dataset.py .........                               [ 86%]

tests/unit/torch/test_public_api.py .                                    [ 86%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 87%]

tests/unit/torch/features/test_continuous.py ..                          [ 87%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 89%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 92%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 93%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f3a11dcc790>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f3a11dcc790>

cell = {'cell_type': 'code', 'execution_count': 45, 'id': '337e6653-38a7-4a9e-b300-46bd0213b30e', 'metadata': {'execution': {...   learning_rate=LEARNING_RATE\n)\nmodel.compile(run_eagerly=False, optimizer=optimizer)\nmodel.fit(loader, epochs=2)'}

cell_index = 87

exec_reply = {'buffers': [], 'content': {'ename': 'InvalidArgumentError', 'engine_info': {'engine_id': -1, 'engine_uuid': '5b6f6699...e, 'engine': '5b6f6699-6af4-4faa-826f-349c876a622e', 'started': '2022-11-04T19:15:47.297014Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           optimizer = tf.keras.optimizers.Adam(

E               learning_rate=LEARNING_RATE

E           )

E           model.compile(run_eagerly=False, optimizer=optimizer)

E           model.fit(loader, epochs=2)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mInvalidArgumentError�[0m                      Traceback (most recent call last)

E           Cell �[0;32mIn [45], line 5�[0m

E           �[1;32m      1�[0m optimizer �[38;5;241m=�[39m tf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(

E           �[1;32m      2�[0m     learning_rate�[38;5;241m=�[39mLEARNING_RATE

E           �[1;32m      3�[0m )

E           �[1;32m      4�[0m model�[38;5;241m.�[39mcompile(run_eagerly�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, optimizer�[38;5;241m=�[39moptimizer)

E           �[0;32m----> 5�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mloader�[49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m2�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:856�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    853�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    854�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 856�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    858�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    859�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

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E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1108�[0m, in �[0;36mModel.call�[0;34m(self, inputs, targets, training, testing, output_context)�[0m

E           �[1;32m   1105�[0m     outputs, context �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_call_child(�[38;5;28mself�[39m�[38;5;241m.�[39mpre, outputs, context)

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1137�[0m, in �[0;36mModel._call_child�[0;34m(self, child, inputs, context)�[0m

E           �[1;32m   1134�[0m �[38;5;28;01mif�[39;00m �[38;5;28many�[39m(�[38;5;28misinstance�[39m(sub, ModelBlock) �[38;5;28;01mfor�[39;00m sub �[38;5;129;01min�[39;00m child�[38;5;241m.�[39msubmodules):

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E           �[1;32m   1138�[0m �[38;5;28;01mif�[39;00m �[38;5;28misinstance�[39m(outputs, Prediction):

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:437�[0m, in �[0;36mcall_layer�[0;34m(layer, inputs, args, **kwargs)�[0m

E           �[1;32m    433�[0m         call_fn �[38;5;241m=�[39m �[38;5;28mtype�[39m(layer)�[38;5;241m.�[39mcall

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/base.py:136�[0m, in �[0;36mModelOutput.__call__�[0;34m(self, inputs, args, **kwargs)�[0m

E           �[1;32m    133�[0m     inputs �[38;5;241m=�[39m tf_utils�[38;5;241m.�[39mcall_layer(�[38;5;28mself�[39m�[38;5;241m.�[39mpre, inputs, �[38;5;241m�[39m�[38;5;241m�[39mkwargs)

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E           �[1;32m    138�[0m �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mpost:

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/base.py:114�[0m, in �[0;36mModelOutput.call�[0;34m(self, inputs, training, testing, **kwargs)�[0m

E           �[1;32m    113�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mcall�[39m(�[38;5;28mself�[39m, inputs, training�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, testing�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, �[38;5;241m�[39m�[38;5;241m�[39mkwargs):

E           �[0;32m--> 114�[0m     �[38;5;28;01mreturn�[39;00m �[43mtf_utils�[49m�[38;5;241;43m.�[39;49m�[43mcall_layer�[49m�[43m(�[49m

E           �[1;32m    115�[0m �[43m        �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mto_call�[49m�[43m,�[49m�[43m �[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[43mtraining�[49m�[38;5;241;43m=�[39;49m�[43mtraining�[49m�[43m,�[49m�[43m �[49m�[43mtesting�[49m�[38;5;241;43m=�[39;49m�[43mtesting�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mkwargs�[49m

E           �[1;32m    116�[0m �[43m    �[49m�[43m)�[49m

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E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:437�[0m, in �[0;36mcall_layer�[0;34m(layer, inputs, args, **kwargs)�[0m

E           �[1;32m    433�[0m         call_fn �[38;5;241m=�[39m �[38;5;28mtype�[39m(layer)�[38;5;241m.�[39mcall

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E           �[0;32m--> 437�[0m �[38;5;28;01mreturn�[39;00m �[43mlayer�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfiltered_kwargs�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/classification.py:330�[0m, in �[0;36mEmbeddingTablePrediction.call�[0;34m(self, inputs, training, **kwargs)�[0m

E           �[1;32m    329�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mcall�[39m(�[38;5;28mself�[39m, inputs, training�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, �[38;5;241m�[39m�[38;5;241m*�[39mkwargs) �[38;5;241m-�[39m�[38;5;241m>�[39m tf�[38;5;241m.�[39mTensor:

E           �[0;32m--> 330�[0m     logits �[38;5;241m=�[39m �[43mtf�[49m�[38;5;241;43m.�[39;49m�[43mmatmul�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mtable�[49m�[38;5;241;43m.�[39;49m�[43mtable�[49m�[38;5;241;43m.�[39;49m�[43membeddings�[49m�[43m,�[49m�[43m �[49m�[43mtranspose_b�[49m�[38;5;241;43m=�[39;49m�[38;5;28;43;01mTrue�[39;49;00m�[43m)�[49m

E           �[1;32m    331�[0m     logits �[38;5;241m=�[39m tf�[38;5;241m.�[39mnn�[38;5;241m.�[39mbias_add(logits, �[38;5;28mself�[39m�[38;5;241m.�[39mbias)

E           �[1;32m    333�[0m     �[38;5;28;01mreturn�[39;00m logits

E

E           �[0;31mInvalidArgumentError�[0m: Exception encountered when calling layer "embedding_table_prediction" (type EmbeddingTablePrediction).

E

E           Matrix size-incompatible: In[0]: [1024,32], In[1]: [6608,24] [Op:MatMul]

E

E           Call arguments received by layer "embedding_table_prediction" (type EmbeddingTablePrediction):

E             • inputs=tf.Tensor(shape=(1024, 32), dtype=float32)

E             • training=False

E             • kwargs={'testing': 'False', 'features': {'f_47_list_seq': '<tf.RaggedTensor [[[13],\n  [0],\n  [0]],\n\n [[6],\n  [0],\n  [0]],\n\n [[8],\n  [0],\n  [0]],\n\n ...,\n\n [[7],\n  [0],\n  [0]],\n\n [[9],\n  [0],\n  [0]],\n\n [[19],\n  [0],\n  [0]]]>', 'f_68_list_seq': '<tf.RaggedTensor [[[45],\n  [0],\n  [0]],\n\n [[24],\n  [0],\n  [0]],\n\n [[45],\n  [0],\n  [0]],\n\n ...,\n\n [[22],\n  [0],\n  [0]],\n\n [[33],\n  [0],\n  [0]],\n\n [[9],\n  [0],\n  [0]]]>', 'item_id_list_seq': '<tf.RaggedTensor [[[62],\n  [0],\n  [0]],\n\n [[45],\n  [0],\n  [0]],\n\n [[17],\n  [0],\n  [0]],\n\n ...,\n\n [[6],\n  [0],\n  [0]],\n\n [[3],\n  [0],\n  [0]],\n\n [[10],\n  [0],\n  [0]]]>'}}

E           InvalidArgumentError: Exception encountered when calling layer "embedding_table_prediction" (type EmbeddingTablePrediction).

E

E           Matrix size-incompatible: In[0]: [1024,32], In[1]: [6608,24] [Op:MatMul]

E

E           Call arguments received by layer "embedding_table_prediction" (type EmbeddingTablePrediction):

E             • inputs=tf.Tensor(shape=(1024, 32), dtype=float32)

E             • training=False

E             • kwargs={'testing': 'False', 'features': {'f_47_list_seq': '<tf.RaggedTensor [[[13],\n  [0],\n  [0]],\n\n [[6],\n  [0],\n  [0]],\n\n [[8],\n  [0],\n  [0]],\n\n ...,\n\n [[7],\n  [0],\n  [0]],\n\n [[9],\n  [0],\n  [0]],\n\n [[19],\n  [0],\n  [0]]]>', 'f_68_list_seq': '<tf.RaggedTensor [[[45],\n  [0],\n  [0]],\n\n [[24],\n  [0],\n  [0]],\n\n [[45],\n  [0],\n  [0]],\n\n ...,\n\n [[22],\n  [0],\n  [0]],\n\n [[33],\n  [0],\n  [0]],\n\n [[9],\n  [0],\n  [0]]]>', 'item_id_list_seq': '<tf.RaggedTensor [[[62],\n  [0],\n  [0]],\n\n [[45],\n  [0],\n  [0]],\n\n [[17],\n  [0],\n  [0]],\n\n ...,\n\n [[6],\n  [0],\n  [0]],\n\n [[3],\n  [0],\n  [0]],\n\n [[10],\n  [0],\n  [0]]]>'}}


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-04 19:15:15.847799: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-04 19:15:19.156066: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-04 19:15:19.156237: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-04 19:15:19.157069: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-04 19:15:19.157129: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-04 19:15:19.157735: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-04 19:15:19.157783: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-04 19:15:19.158389: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-04 19:15:19.158440: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-04 19:15:39.771007: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8500

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filecz_nnek9.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     60    24%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    3      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     15    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     40    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         114     10    91%

merlin/models/tf/blocks/optimizer.py                                   173     13    92%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     49    80%

merlin/models/tf/core/base.py                                          244     55    77%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     31    93%

merlin/models/tf/loader.py                                             245     73    70%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        708     75    89%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11357   2227    80%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 823 passed, 12 skipped, 1352 warnings in 1600.89s (0:26:40) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   test-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins10852325146448546568.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit ccd6aa822d25e9e4fbd73b0e3cf87586f8c0d2c4, no merge conflicts.
Running as SYSTEM
Setting status of ccd6aa822d25e9e4fbd73b0e3cf87586f8c0d2c4 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1773/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse ccd6aa822d25e9e4fbd73b0e3cf87586f8c0d2c4^{commit} # timeout=10
Checking out Revision ccd6aa822d25e9e4fbd73b0e3cf87586f8c0d2c4 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f ccd6aa822d25e9e4fbd73b0e3cf87586f8c0d2c4 # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk dffc060b0200ac11bac96fe2572129e2f2296aef # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins3000346045936939199.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+36.gccd6aa82.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.4,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.4,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+36.gccd6aa82,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2405621329'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-cw80f275
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-cw80f275
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 64755badd4e5756601f66e7e568201aedb8a4144
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.10.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (21.3)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.5.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (3.19.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (4.64.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (7.0.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (1.3.5)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.2.5)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (0.12.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.2.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.4.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (8.1.3)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.8.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.4)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (65.4.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+7.g64755ba) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (4.0.0)

[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-xtewlbrr

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-xtewlbrr

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+7.g64755ba)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.10.0)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 875 items


tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s........................              [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 49%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py .....................           [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f32180e9c70>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f32180e9c70>

cell = {'cell_type': 'code', 'execution_count': 45, 'id': '337e6653-38a7-4a9e-b300-46bd0213b30e', 'metadata': {'execution': {...   learning_rate=LEARNING_RATE\n)\nmodel.compile(run_eagerly=False, optimizer=optimizer)\nmodel.fit(loader, epochs=2)'}

cell_index = 87

exec_reply = {'buffers': [], 'content': {'ename': 'InvalidArgumentError', 'engine_info': {'engine_id': -1, 'engine_uuid': '77a646f3...e, 'engine': '77a646f3-6771-421a-9f76-8f602fa5277f', 'started': '2022-11-08T13:39:11.735943Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           optimizer = tf.keras.optimizers.Adam(

E               learning_rate=LEARNING_RATE

E           )

E           model.compile(run_eagerly=False, optimizer=optimizer)

E           model.fit(loader, epochs=2)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mInvalidArgumentError�[0m                      Traceback (most recent call last)

E           Cell �[0;32mIn [45], line 5�[0m

E           �[1;32m      1�[0m optimizer �[38;5;241m=�[39m tf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(

E           �[1;32m      2�[0m     learning_rate�[38;5;241m=�[39mLEARNING_RATE

E           �[1;32m      3�[0m )

E           �[1;32m      4�[0m model�[38;5;241m.�[39mcompile(run_eagerly�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, optimizer�[38;5;241m=�[39moptimizer)

E           �[0;32m----> 5�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mloader�[49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m2�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:899�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    896�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    897�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 899�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    901�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    902�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1179�[0m, in �[0;36mModel.call�[0;34m(self, inputs, targets, training, testing, output_context)�[0m

E           �[1;32m   1176�[0m     outputs, context �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_call_child(�[38;5;28mself�[39m�[38;5;241m.�[39mpre, outputs, context)

E           �[1;32m   1178�[0m �[38;5;28;01mfor�[39;00m block �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mblocks:

E           �[0;32m-> 1179�[0m     outputs, context �[38;5;241m=�[39m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43m_call_child�[49m�[43m(�[49m�[43mblock�[49m�[43m,�[49m�[43m �[49m�[43moutputs�[49m�[43m,�[49m�[43m �[49m�[43mcontext�[49m�[43m)�[49m

E           �[1;32m   1181�[0m �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mpost:

E           �[1;32m   1182�[0m     outputs, context �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_call_child(�[38;5;28mself�[39m�[38;5;241m.�[39mpost, outputs, context)

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1208�[0m, in �[0;36mModel._call_child�[0;34m(self, child, inputs, context)�[0m

E           �[1;32m   1205�[0m �[38;5;28;01mif�[39;00m �[38;5;28many�[39m(�[38;5;28misinstance�[39m(sub, ModelBlock) �[38;5;28;01mfor�[39;00m sub �[38;5;129;01min�[39;00m child�[38;5;241m.�[39msubmodules):

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E           �[0;32m-> 1208�[0m outputs �[38;5;241m=�[39m �[43mcall_layer�[49m�[43m(�[49m�[43mchild�[49m�[43m,�[49m�[43m �[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mcall_kwargs�[49m�[43m)�[49m

E           �[1;32m   1209�[0m �[38;5;28;01mif�[39;00m �[38;5;28misinstance�[39m(outputs, Prediction):

E           �[1;32m   1210�[0m     targets �[38;5;241m=�[39m outputs�[38;5;241m.�[39mtargets �[38;5;28;01mif�[39;00m outputs�[38;5;241m.�[39mtargets �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m �[38;5;28;01melse�[39;00m context�[38;5;241m.�[39mtargets

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:437�[0m, in �[0;36mcall_layer�[0;34m(layer, inputs, args, **kwargs)�[0m

E           �[1;32m    433�[0m         call_fn �[38;5;241m=�[39m �[38;5;28mtype�[39m(layer)�[38;5;241m.�[39mcall

E           �[1;32m    435�[0m         filtered_kwargs �[38;5;241m=�[39m filter_kwargs(filtered_kwargs, call_fn, �[38;5;241m�[39m�[38;5;241m�[39m_k)

E           �[0;32m--> 437�[0m �[38;5;28;01mreturn�[39;00m �[43mlayer�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfiltered_kwargs�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/base.py:136�[0m, in �[0;36mModelOutput.__call__�[0;34m(self, inputs, args, **kwargs)�[0m

E           �[1;32m    133�[0m     inputs �[38;5;241m=�[39m tf_utils�[38;5;241m.�[39mcall_layer(�[38;5;28mself�[39m�[38;5;241m.�[39mpre, inputs, �[38;5;241m�[39m�[38;5;241m�[39mkwargs)

E           �[1;32m    135�[0m �[38;5;66;03m# super call�[39;00m

E           �[0;32m--> 136�[0m outputs �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43mModelOutput�[49m�[43m,�[49m�[43m �[49m�[38;5;28;43mself�[39;49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[38;5;21;43m__call__�[39;49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mkwargs�[49m�[43m)�[49m

E           �[1;32m    138�[0m �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mpost:

E           �[1;32m    139�[0m     outputs �[38;5;241m=�[39m tf_utils�[38;5;241m.�[39mcall_layer(�[38;5;28mself�[39m�[38;5;241m.�[39mpost, outputs, �[38;5;241m�[39m�[38;5;241m�[39mkwargs)

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/base.py:114�[0m, in �[0;36mModelOutput.call�[0;34m(self, inputs, training, testing, **kwargs)�[0m

E           �[1;32m    113�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mcall�[39m(�[38;5;28mself�[39m, inputs, training�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, testing�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, �[38;5;241m�[39m�[38;5;241m�[39mkwargs):

E           �[0;32m--> 114�[0m     �[38;5;28;01mreturn�[39;00m �[43mtf_utils�[49m�[38;5;241;43m.�[39;49m�[43mcall_layer�[49m�[43m(�[49m

E           �[1;32m    115�[0m �[43m        �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mto_call�[49m�[43m,�[49m�[43m �[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[43mtraining�[49m�[38;5;241;43m=�[39;49m�[43mtraining�[49m�[43m,�[49m�[43m �[49m�[43mtesting�[49m�[38;5;241;43m=�[39;49m�[43mtesting�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mkwargs�[49m

E           �[1;32m    116�[0m �[43m    �[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:437�[0m, in �[0;36mcall_layer�[0;34m(layer, inputs, args, **kwargs)�[0m

E           �[1;32m    433�[0m         call_fn �[38;5;241m=�[39m �[38;5;28mtype�[39m(layer)�[38;5;241m.�[39mcall

E           �[1;32m    435�[0m         filtered_kwargs �[38;5;241m=�[39m filter_kwargs(filtered_kwargs, call_fn, �[38;5;241m�[39m�[38;5;241m�[39m_k)

E           �[0;32m--> 437�[0m �[38;5;28;01mreturn�[39;00m �[43mlayer�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfiltered_kwargs�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/outputs/classification.py:330�[0m, in �[0;36mEmbeddingTablePrediction.call�[0;34m(self, inputs, training, **kwargs)�[0m

E           �[1;32m    329�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mcall�[39m(�[38;5;28mself�[39m, inputs, training�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m, �[38;5;241m�[39m�[38;5;241m*�[39mkwargs) �[38;5;241m-�[39m�[38;5;241m>�[39m tf�[38;5;241m.�[39mTensor:

E           �[0;32m--> 330�[0m     logits �[38;5;241m=�[39m �[43mtf�[49m�[38;5;241;43m.�[39;49m�[43mmatmul�[49m�[43m(�[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mtable�[49m�[38;5;241;43m.�[39;49m�[43mtable�[49m�[38;5;241;43m.�[39;49m�[43membeddings�[49m�[43m,�[49m�[43m �[49m�[43mtranspose_b�[49m�[38;5;241;43m=�[39;49m�[38;5;28;43;01mTrue�[39;49;00m�[43m)�[49m

E           �[1;32m    331�[0m     logits �[38;5;241m=�[39m tf�[38;5;241m.�[39mnn�[38;5;241m.�[39mbias_add(logits, �[38;5;28mself�[39m�[38;5;241m.�[39mbias)

E           �[1;32m    333�[0m     �[38;5;28;01mreturn�[39;00m logits

E

E           �[0;31mInvalidArgumentError�[0m: Exception encountered when calling layer "embedding_table_prediction" (type EmbeddingTablePrediction).

E

E           Matrix size-incompatible: In[0]: [1024,32], In[1]: [6657,24] [Op:MatMul]

E

E           Call arguments received by layer "embedding_table_prediction" (type EmbeddingTablePrediction):

E             • inputs=tf.Tensor(shape=(1024, 32), dtype=float32)

E             • training=False

E             • kwargs={'testing': 'False', 'features': {'f_47_list_seq': '<tf.RaggedTensor [[[18],\n  [0],\n  [0]],\n\n [[2],\n  [0],\n  [0]],\n\n [[6],\n  [0],\n  [0]],\n\n ...,\n\n [[9],\n  [0],\n  [0]],\n\n [[10],\n  [0],\n  [0]],\n\n [[17],\n  [0],\n  [0]]]>', 'f_68_list_seq': '<tf.RaggedTensor [[[46],\n  [0],\n  [0]],\n\n [[23],\n  [0],\n  [0]],\n\n [[13],\n  [0],\n  [0]],\n\n ...,\n\n [[2],\n  [0],\n  [0]],\n\n [[5],\n  [0],\n  [0]],\n\n [[19],\n  [0],\n  [0]]]>', 'item_id_list_seq': '<tf.RaggedTensor [[[13],\n  [0],\n  [0]],\n\n [[6],\n  [0],\n  [0]],\n\n [[26],\n  [0],\n  [0]],\n\n ...,\n\n [[59],\n  [0],\n  [0]],\n\n [[12],\n  [0],\n  [0]],\n\n [[12],\n  [0],\n  [0]]]>'}}

E           InvalidArgumentError: Exception encountered when calling layer "embedding_table_prediction" (type EmbeddingTablePrediction).

E

E           Matrix size-incompatible: In[0]: [1024,32], In[1]: [6657,24] [Op:MatMul]

E

E           Call arguments received by layer "embedding_table_prediction" (type EmbeddingTablePrediction):

E             • inputs=tf.Tensor(shape=(1024, 32), dtype=float32)

E             • training=False

E             • kwargs={'testing': 'False', 'features': {'f_47_list_seq': '<tf.RaggedTensor [[[18],\n  [0],\n  [0]],\n\n [[2],\n  [0],\n  [0]],\n\n [[6],\n  [0],\n  [0]],\n\n ...,\n\n [[9],\n  [0],\n  [0]],\n\n [[10],\n  [0],\n  [0]],\n\n [[17],\n  [0],\n  [0]]]>', 'f_68_list_seq': '<tf.RaggedTensor [[[46],\n  [0],\n  [0]],\n\n [[23],\n  [0],\n  [0]],\n\n [[13],\n  [0],\n  [0]],\n\n ...,\n\n [[2],\n  [0],\n  [0]],\n\n [[5],\n  [0],\n  [0]],\n\n [[19],\n  [0],\n  [0]]]>', 'item_id_list_seq': '<tf.RaggedTensor [[[13],\n  [0],\n  [0]],\n\n [[6],\n  [0],\n  [0]],\n\n [[26],\n  [0],\n  [0]],\n\n ...,\n\n [[59],\n  [0],\n  [0]],\n\n [[12],\n  [0],\n  [0]],\n\n [[12],\n  [0],\n  [0]]]>'}}


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-08 13:38:38.662411: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-08 13:38:42.016192: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-08 13:38:42.016302: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-08 13:38:42.017129: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-08 13:38:42.017183: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-08 13:38:42.017811: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-08 13:38:42.017860: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-08 13:38:42.018479: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-08 13:38:42.018529: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-08 13:39:03.941744: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8500

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filepu3w9azt.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     50    80%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     31    93%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        751    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11543   2333    80%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 861 passed, 13 skipped, 1431 warnings in 1687.88s (0:28:07) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins15431973141797366852.sh

@rnyak rnyak added this to the Merlin 22.12 milestone Nov 8, 2022
@nvidia-merlin-bot
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GitHub pull request #849 of commit 585f0286218628dda075ca35a6d17f65de7e5676, no merge conflicts.
Running as SYSTEM
Setting status of 585f0286218628dda075ca35a6d17f65de7e5676 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1791/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 585f0286218628dda075ca35a6d17f65de7e5676^{commit} # timeout=10
Checking out Revision 585f0286218628dda075ca35a6d17f65de7e5676 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 585f0286218628dda075ca35a6d17f65de7e5676 # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk 644b568e69199b92fc5597a2ac165ea46fdebcc0 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins435848096930995835.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+41.g585f0286.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.5,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.5,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@b6f9a67b2c0caf1b0b1ded10e5491b5a0f13230a,merlin-models==0.9.0+41.g585f0286,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='704414433'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-329jbm75
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-329jbm75
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit c1ddc198bc1b0c39b5008a4ec07f2b7f02fd22c1
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.5.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.3.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (3.19.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (0.55.1)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (4.64.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.10.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (7.0.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.2.5)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (0.4.3)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (0.12.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.0.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.4.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.7.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.0.4)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (5.8.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (65.4.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+8.gc1ddc19) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (4.0.0)

[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-qbsx7bbu

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-qbsx7bbu

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+8.gc1ddc19)

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2+3.gb6f9a67)

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.3.5)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 876 items


tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py .....................           [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7faf1b3b0d60>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7faf1b3b0d60>

cell = {'cell_type': 'code', 'execution_count': 15, 'id': '65f5c222', 'metadata': {'execution': {'iopub.status.busy': '2022-1...train/"), output_files=10)\nworkflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"), output_files=1)'}

cell_index = 29

exec_reply = {'buffers': [], 'content': {'ename': 'TypeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '7d10957d-2bcf-49d8-...e, 'engine': '7d10957d-2bcf-49d8-b41f-5ff6131738d7', 'started': '2022-11-09T14:54:12.832390Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           # fit data

E           workflow.fit(train)

E

E           # transform and save data

E           workflow.transform(train).to_parquet(os.path.join(DATA_FOLDER, "train/"), output_files=10)

E           workflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"), output_files=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mTypeError�[0m                                 Traceback (most recent call last)

E           Cell �[0;32mIn [15], line 2�[0m

E           �[1;32m      1�[0m �[38;5;66;03m# fit data�[39;00m

E           �[0;32m----> 2�[0m �[43mworkflow�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m)�[49m

E           �[1;32m      4�[0m �[38;5;66;03m# transform and save data�[39;00m

E           �[1;32m      5�[0m workflow�[38;5;241m.�[39mtransform(train)�[38;5;241m.�[39mto_parquet(os�[38;5;241m.�[39mpath�[38;5;241m.�[39mjoin(DATA_FOLDER, �[38;5;124m"�[39m�[38;5;124mtrain/�[39m�[38;5;124m"�[39m), output_files�[38;5;241m=�[39m�[38;5;241m10�[39m)

E

E           File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/nvtabular/workflow/workflow.py:209�[0m, in �[0;36mWorkflow.fit�[0;34m(self, dataset)�[0m

E           �[1;32m    205�[0m         dependencies�[38;5;241m.�[39mdifference_update(current_phase)

E           �[1;32m    207�[0m �[38;5;66;03m# This captures the output dtypes of operators like LambdaOp where�[39;00m

E           �[1;32m    208�[0m �[38;5;66;03m# the dtype can't be determined without running the transform�[39;00m

E           �[0;32m--> 209�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43m_transform_impl�[49m�[43m(�[49m�[43mdataset�[49m�[43m,�[49m�[43m �[49m�[43mcapture_dtypes�[49m�[38;5;241;43m=�[39;49m�[38;5;28;43;01mTrue�[39;49;00m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43msample_dtypes�[49m�[43m(�[49m�[43m)�[49m

E           �[1;32m    210�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mgraph�[38;5;241m.�[39mconstruct_schema(dataset�[38;5;241m.�[39mschema, preserve_dtypes�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

E           �[1;32m    212�[0m �[38;5;28;01mreturn�[39;00m �[38;5;28mself�[39m

E

E           File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/io/dataset.py:1147�[0m, in �[0;36mDataset.sample_dtypes�[0;34m(self, n, annotate_lists)�[0m

E           �[1;32m   1140�[0m �[38;5;124;03m"""Return the real dtypes of the Dataset�[39;00m

E           �[1;32m   1141�[0m

E           �[1;32m   1142�[0m �[38;5;124;03mUse cached metadata if this operation was�[39;00m

E           �[1;32m   1143�[0m �[38;5;124;03malready performed. Otherwise, call down to the�[39;00m

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-09 14:54:07.133758: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-09 14:54:10.616012: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-09 14:54:10.616125: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-09 14:54:10.616943: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-09 14:54:10.617006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-09 14:54:10.617621: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-09 14:54:10.617673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-09 14:54:10.618270: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-09 14:54:10.618321: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filetltualpk.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        753    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11552   2380    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 862 passed, 13 skipped, 1433 warnings in 1766.19s (0:29:26) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins10773941165164568073.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit f11dd8afed1f8b59e40e47ebbd3e9621d1201bc5, no merge conflicts.
Running as SYSTEM
Setting status of f11dd8afed1f8b59e40e47ebbd3e9621d1201bc5 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1794/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse f11dd8afed1f8b59e40e47ebbd3e9621d1201bc5^{commit} # timeout=10
Checking out Revision f11dd8afed1f8b59e40e47ebbd3e9621d1201bc5 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f f11dd8afed1f8b59e40e47ebbd3e9621d1201bc5 # timeout=10
Commit message: "update ETL, update to new api in MLP and BiLSTM"
 > git rev-list --no-walk 644b568e69199b92fc5597a2ac165ea46fdebcc0 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins10718997691870515236.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
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Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+42.gf11dd8af.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.5,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.5,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+42.gf11dd8af,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3851801049'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-v4s1wpsj
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-v4s1wpsj
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit c1ddc198bc1b0c39b5008a4ec07f2b7f02fd22c1
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.5.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (0.55.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (21.3)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (3.19.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.2.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.3.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (4.64.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.10.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (7.0.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (0.4.3)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.0.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (5.8.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.0.4)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (8.1.3)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (6.2)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (65.4.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+8.gc1ddc19) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (4.0.0)

[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-k9bnnzf0

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-k9bnnzf0

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2+3.gb6f9a67)

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+8.gc1ddc19)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.55.1)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 876 items


tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py .....................           [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7ff7e8120a30>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7ff7e8120a30>

cell = {'cell_type': 'code', 'execution_count': 15, 'id': '65f5c222', 'metadata': {'execution': {'iopub.status.busy': '2022-1...in(DATA_FOLDER, "train/"), output_files=2)\nworkflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"))'}

cell_index = 29

exec_reply = {'buffers': [], 'content': {'ename': 'TypeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '3a69c1e9-5766-4c82-...e, 'engine': '3a69c1e9-5766-4c82-98c7-3975bd014dd8', 'started': '2022-11-09T17:15:19.558272Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           # fit data

E           workflow.fit(train)

E

E           # transform and save data

E           workflow.transform(train).to_parquet(os.path.join(DATA_FOLDER, "train/"), output_files=2)

E           workflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"))

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mTypeError�[0m                                 Traceback (most recent call last)

E           Cell �[0;32mIn [15], line 2�[0m

E           �[1;32m      1�[0m �[38;5;66;03m# fit data�[39;00m

E           �[0;32m----> 2�[0m �[43mworkflow�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m)�[49m

E           �[1;32m      4�[0m �[38;5;66;03m# transform and save data�[39;00m

E           �[1;32m      5�[0m workflow�[38;5;241m.�[39mtransform(train)�[38;5;241m.�[39mto_parquet(os�[38;5;241m.�[39mpath�[38;5;241m.�[39mjoin(DATA_FOLDER, �[38;5;124m"�[39m�[38;5;124mtrain/�[39m�[38;5;124m"�[39m), output_files�[38;5;241m=�[39m�[38;5;241m2�[39m)

E

E           File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/nvtabular/workflow/workflow.py:209�[0m, in �[0;36mWorkflow.fit�[0;34m(self, dataset)�[0m

E           �[1;32m    205�[0m         dependencies�[38;5;241m.�[39mdifference_update(current_phase)

E           �[1;32m    207�[0m �[38;5;66;03m# This captures the output dtypes of operators like LambdaOp where�[39;00m

E           �[1;32m    208�[0m �[38;5;66;03m# the dtype can't be determined without running the transform�[39;00m

E           �[0;32m--> 209�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43m_transform_impl�[49m�[43m(�[49m�[43mdataset�[49m�[43m,�[49m�[43m �[49m�[43mcapture_dtypes�[49m�[38;5;241;43m=�[39;49m�[38;5;28;43;01mTrue�[39;49;00m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43msample_dtypes�[49m�[43m(�[49m�[43m)�[49m

E           �[1;32m    210�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mgraph�[38;5;241m.�[39mconstruct_schema(dataset�[38;5;241m.�[39mschema, preserve_dtypes�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

E           �[1;32m    212�[0m �[38;5;28;01mreturn�[39;00m �[38;5;28mself�[39m

E

E           File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/io/dataset.py:1147�[0m, in �[0;36mDataset.sample_dtypes�[0;34m(self, n, annotate_lists)�[0m

E           �[1;32m   1140�[0m �[38;5;124;03m"""Return the real dtypes of the Dataset�[39;00m

E           �[1;32m   1141�[0m

E           �[1;32m   1142�[0m �[38;5;124;03mUse cached metadata if this operation was�[39;00m

E           �[1;32m   1143�[0m �[38;5;124;03malready performed. Otherwise, call down to the�[39;00m

E           �[1;32m   1144�[0m �[38;5;124;03munderlying engine for sampling logic.�[39;00m

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-09 17:15:14.071112: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-09 17:15:17.431681: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-09 17:15:17.431803: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-09 17:15:17.433409: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-09 17:15:17.433572: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-09 17:15:17.434707: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-09 17:15:17.434826: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-09 17:15:17.435927: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-09 17:15:17.436066: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file81y_0rr.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag_.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        753    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11552   2380    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 862 passed, 13 skipped, 1433 warnings in 1669.84s (0:27:49) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins5819987376212459844.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit c0be6da89438367ffeee100d459b8aa94e446f24, no merge conflicts.
Running as SYSTEM
Setting status of c0be6da89438367ffeee100d459b8aa94e446f24 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1831/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse c0be6da89438367ffeee100d459b8aa94e446f24^{commit} # timeout=10
Checking out Revision c0be6da89438367ffeee100d459b8aa94e446f24 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f c0be6da89438367ffeee100d459b8aa94e446f24 # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk ba38df0f93157f1a9d90e4a9e5264075b755e089 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins3874824065527651633.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
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Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+47.gc0be6da8.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.8,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.8,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+47.gc0be6da8,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.990,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2819078963'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-pdgknkcq
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-pdgknkcq
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.12.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.8.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (3.1.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.4)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+11.geb606d5) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=dfb1c39a1deb2c118c9c3d1ddafa9e24dd34e61444207640534e8a37ec56d66d
  Stored in directory: /tmp/pip-ephem-wheel-cache-ajhe7lcn/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-cqe6lp3t
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-cqe6lp3t
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+11.geb606d5)
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=7065e0e65fa11b7225c51ba3a2279743c89f8ec75e71784fb062b825d54a4b67
  Stored in directory: /tmp/pip-ephem-wheel-cache-3tzgnblu/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 876 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py .....................           [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7fbbe0483a90>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7fbbe0483a90>

cell = {'cell_type': 'code', 'execution_count': 16, 'id': '5ba81642', 'metadata': {'execution': {'iopub.status.busy': '2022-1....sort_values('date_first').reset_index(drop=True)\ndf.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))'}

cell_index = 31

exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '62e42477-9961-48...e, 'engine': '62e42477-9961-48bb-b82f-ddfb4df1a49b', 'started': '2022-11-14T14:09:20.106132Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           df = get_lib().read_parquet(

E               glob.glob(

E                   os.path.join(DATA_FOLDER, "train/.parquet")

E               )

E           )

E           df = df.sort_values('date_first').reset_index(drop=True)

E           df.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mRuntimeError�[0m                              Traceback (most recent call last)

E           Cell �[0;32mIn [16], line 1�[0m

E           �[0;32m----> 1�[0m df �[38;5;241m=�[39m �[43mget_lib�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mread_parquet�[49m�[43m(�[49m

E           �[1;32m      2�[0m �[43m    �[49m�[43mglob�[49m�[38;5;241;43m.�[39;49m�[43mglob�[49m�[43m(�[49m

E           �[1;32m      3�[0m �[43m        �[49m�[43mos�[49m�[38;5;241;43m.�[39;49m�[43mpath�[49m�[38;5;241;43m.�[39;49m�[43mjoin�[49m�[43m(�[49m�[43mDATA_FOLDER�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mtrain/.parquet�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m

E           �[1;32m      4�[0m �[43m    �[49m�[43m)�[49m

E           �[1;32m      5�[0m �[43m)�[49m

E           �[1;32m      6�[0m df �[38;5;241m=�[39m df�[38;5;241m.�[39msort_values(�[38;5;124m'�[39m�[38;5;124mdate_first�[39m�[38;5;124m'�[39m)�[38;5;241m.�[39mreset_index(drop�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

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E           File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/io/parquet.py:470�[0m, in �[0;36mread_parquet�[0;34m(filepath_or_buffer, engine, columns, filters, row_groups, skiprows, num_rows, strings_to_categorical, use_pandas_metadata, use_python_file_object, categorical_partitions, open_file_options, args, **kwargs)�[0m

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-14 14:09:10.688433: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-14 14:09:14.113666: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-14 14:09:14.113778: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-14 14:09:14.114602: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-14 14:09:14.114655: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-14 14:09:14.115295: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-14 14:09:14.115345: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-14 14:09:14.115974: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-14 14:09:14.116031: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filevx25w7_f.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        753    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11572   2400    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 862 passed, 13 skipped, 1433 warnings in 1690.43s (0:28:10) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins8870580853522479077.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit e4f14f0d9a9893f67aa15b96b4207f095612cb4c, no merge conflicts.
Running as SYSTEM
Setting status of e4f14f0d9a9893f67aa15b96b4207f095612cb4c to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1832/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse e4f14f0d9a9893f67aa15b96b4207f095612cb4c^{commit} # timeout=10
Checking out Revision e4f14f0d9a9893f67aa15b96b4207f095612cb4c (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f e4f14f0d9a9893f67aa15b96b4207f095612cb4c # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk c0be6da89438367ffeee100d459b8aa94e446f24 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins7773881631705626350.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+49.ge4f14f0d.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.8,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.8,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+49.ge4f14f0d,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.990,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='4027849918'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-4o1lzc8k
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-4o1lzc8k
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.12.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (3.1.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.4.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.7.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.4)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.8.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+11.geb606d5) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2.8.2)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=65e34117cf6c1967b4654f38772c31fbcbea4c1ad82342c40007dcfa7fb92991
  Stored in directory: /tmp/pip-ephem-wheel-cache-fesb9k4a/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-w_z541qo
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-w_z541qo
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+11.geb606d5)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=3979d720e6640a3687dea1e102a6a2feff3188077db0c035bb5ceb65f3709e9d
  Stored in directory: /tmp/pip-ephem-wheel-cache-5zh33fax/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 877 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 29%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 49%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f2de4073d00>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f2de4073d00>

cell = {'cell_type': 'code', 'execution_count': 16, 'id': '5ba81642', 'metadata': {'execution': {'iopub.status.busy': '2022-1....sort_values('date_first').reset_index(drop=True)\ndf.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))'}

cell_index = 31

exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '9a622a86-10e8-49...e, 'engine': '9a622a86-10e8-49d2-b9f6-2c3a3652359e', 'started': '2022-11-14T14:40:41.409906Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           df = get_lib().read_parquet(

E               glob.glob(

E                   os.path.join(DATA_FOLDER, "train/.parquet")

E               )

E           )

E           df = df.sort_values('date_first').reset_index(drop=True)

E           df.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mRuntimeError�[0m                              Traceback (most recent call last)

E           Cell �[0;32mIn [16], line 1�[0m

E           �[0;32m----> 1�[0m df �[38;5;241m=�[39m �[43mget_lib�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mread_parquet�[49m�[43m(�[49m

E           �[1;32m      2�[0m �[43m    �[49m�[43mglob�[49m�[38;5;241;43m.�[39;49m�[43mglob�[49m�[43m(�[49m

E           �[1;32m      3�[0m �[43m        �[49m�[43mos�[49m�[38;5;241;43m.�[39;49m�[43mpath�[49m�[38;5;241;43m.�[39;49m�[43mjoin�[49m�[43m(�[49m�[43mDATA_FOLDER�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mtrain/.parquet�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m

E           �[1;32m      4�[0m �[43m    �[49m�[43m)�[49m

E           �[1;32m      5�[0m �[43m)�[49m

E           �[1;32m      6�[0m df �[38;5;241m=�[39m df�[38;5;241m.�[39msort_values(�[38;5;124m'�[39m�[38;5;124mdate_first�[39m�[38;5;124m'�[39m)�[38;5;241m.�[39mreset_index(drop�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-14 14:40:31.672574: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-14 14:40:35.239374: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-14 14:40:35.239485: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-14 14:40:35.240397: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-14 14:40:35.240457: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-14 14:40:35.241067: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-14 14:40:35.241119: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-14 14:40:35.241727: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-14 14:40:35.241779: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filep8r3t25b.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11575   2399    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 863 passed, 13 skipped, 1436 warnings in 1743.76s (0:29:03) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins15060169443107138385.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 4bbc2e70a325e34d2caeca720ff7a9e088dffe15, no merge conflicts.
Running as SYSTEM
Setting status of 4bbc2e70a325e34d2caeca720ff7a9e088dffe15 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1834/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 4bbc2e70a325e34d2caeca720ff7a9e088dffe15^{commit} # timeout=10
Checking out Revision 4bbc2e70a325e34d2caeca720ff7a9e088dffe15 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 4bbc2e70a325e34d2caeca720ff7a9e088dffe15 # timeout=10
Commit message: "update nb"
 > git rev-list --no-walk 2c14312ecf9c63e2e08a148b4f757de095b063bb # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins4175192373987339955.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+50.g4bbc2e70.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.8,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.8,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+50.g4bbc2e70,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3760052940'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-5lffnblh
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-5lffnblh
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.12.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.8.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (8.1.3)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (3.1.2)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+11.geb606d5) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=cd5048e81c24e9f95151ca59ef6aa589ffd073ca2b6742a5d1bf309edae7c44f
  Stored in directory: /tmp/pip-ephem-wheel-cache-uiwc51nc/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-e82azzfl
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-e82azzfl
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+11.geb606d5)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=2d065849108d186cf0bc1599b71c5526d6571b68387682ddbb076894e0a588d5
  Stored in directory: /tmp/pip-ephem-wheel-cache-4gy9e383/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 877 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 29%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 49%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f5cccc2bc10>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f5cccc2bc10>

cell = {'cell_type': 'code', 'execution_count': 16, 'id': '5ba81642', 'metadata': {'execution': {'iopub.status.busy': '2022-1....sort_values('date_first').reset_index(drop=True)\ndf.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))'}

cell_index = 31

exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'bee5da1f-c2ba-4c...e, 'engine': 'bee5da1f-c2ba-4cb8-bc68-a03762731310', 'started': '2022-11-14T22:05:37.329556Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           df = get_lib().read_parquet(

E               glob.glob(

E                   os.path.join(DATA_FOLDER, "train/.parquet")

E               )

E           )

E           df = df.sort_values('date_first').reset_index(drop=True)

E           df.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mRuntimeError�[0m                              Traceback (most recent call last)

E           Cell �[0;32mIn [16], line 1�[0m

E           �[0;32m----> 1�[0m df �[38;5;241m=�[39m �[43mget_lib�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mread_parquet�[49m�[43m(�[49m

E           �[1;32m      2�[0m �[43m    �[49m�[43mglob�[49m�[38;5;241;43m.�[39;49m�[43mglob�[49m�[43m(�[49m

E           �[1;32m      3�[0m �[43m        �[49m�[43mos�[49m�[38;5;241;43m.�[39;49m�[43mpath�[49m�[38;5;241;43m.�[39;49m�[43mjoin�[49m�[43m(�[49m�[43mDATA_FOLDER�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mtrain/.parquet�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m

E           �[1;32m      4�[0m �[43m    �[49m�[43m)�[49m

E           �[1;32m      5�[0m �[43m)�[49m

E           �[1;32m      6�[0m df �[38;5;241m=�[39m df�[38;5;241m.�[39msort_values(�[38;5;124m'�[39m�[38;5;124mdate_first�[39m�[38;5;124m'�[39m)�[38;5;241m.�[39mreset_index(drop�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-14 22:05:28.002882: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-14 22:05:31.363515: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-14 22:05:31.363617: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-14 22:05:31.364944: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-14 22:05:31.365103: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-14 22:05:31.366251: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-14 22:05:31.366373: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-14 22:05:31.367468: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-14 22:05:31.367587: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_fileec5gwzvk.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11575   2399    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 863 passed, 13 skipped, 1436 warnings in 1677.68s (0:27:57) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins9035937119678634131.sh

@viswa-nvidia viswa-nvidia mentioned this pull request Nov 15, 2022
Closed
6 tasks
@rnyak rnyak changed the title [Draft] session-based example using dressipi dataset and XLNet architecture Session-based example using dressipi dataset and XLNet architecture Nov 15, 2022
@rnyak rnyak added the help wanted Extra attention is needed label Nov 15, 2022
@nvidia-merlin-bot
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GitHub pull request #849 of commit 930146caa956b51c56acc3f27e3f670da608a697, no merge conflicts.
Running as SYSTEM
Setting status of 930146caa956b51c56acc3f27e3f670da608a697 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1845/ and message: 'Pending'
Using context: Jenkins
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 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
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 > git --version # timeout=10
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 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 930146caa956b51c56acc3f27e3f670da608a697^{commit} # timeout=10
Checking out Revision 930146caa956b51c56acc3f27e3f670da608a697 (detached)
 > git config core.sparsecheckout # timeout=10
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Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk 39e9ddf8bcbb21f9ce2771f07d3fa7d079b120c8 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins17458250003018182311.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
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Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+53.g930146ca.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.9,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.9,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+53.g930146ca,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2734884007'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-qg8ponlw
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-qg8ponlw
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.12.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.4)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.8.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.4.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (8.1.3)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+11.geb606d5) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=821a0b08a3535242e1fb156d48cf49affd730b0d3722a9be99a90222700751fc
  Stored in directory: /tmp/pip-ephem-wheel-cache-5qcalv9v/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-ky026ie7
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-ky026ie7
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+11.geb606d5)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=74d0446d04121c342e7f560aeaf8b407c96cc96ebf850990deab2f9046aa026b
  Stored in directory: /tmp/pip-ephem-wheel-cache-_nb2pjd9/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 878 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 29%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 30%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f87f8611ac0>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f87f8611ac0>

cell = {'cell_type': 'code', 'execution_count': 16, 'id': '5ba81642', 'metadata': {'execution': {'iopub.status.busy': '2022-1....sort_values('date_first').reset_index(drop=True)\ndf.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))'}

cell_index = 31

exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'c76ccd78-d629-43...e, 'engine': 'c76ccd78-d629-4323-a1ad-1e6b50418343', 'started': '2022-11-15T23:39:04.229728Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           df = get_lib().read_parquet(

E               glob.glob(

E                   os.path.join(DATA_FOLDER, "train/.parquet")

E               )

E           )

E           df = df.sort_values('date_first').reset_index(drop=True)

E           df.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mRuntimeError�[0m                              Traceback (most recent call last)

E           Cell �[0;32mIn [16], line 1�[0m

E           �[0;32m----> 1�[0m df �[38;5;241m=�[39m �[43mget_lib�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mread_parquet�[49m�[43m(�[49m

E           �[1;32m      2�[0m �[43m    �[49m�[43mglob�[49m�[38;5;241;43m.�[39;49m�[43mglob�[49m�[43m(�[49m

E           �[1;32m      3�[0m �[43m        �[49m�[43mos�[49m�[38;5;241;43m.�[39;49m�[43mpath�[49m�[38;5;241;43m.�[39;49m�[43mjoin�[49m�[43m(�[49m�[43mDATA_FOLDER�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mtrain/.parquet�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m

E           �[1;32m      4�[0m �[43m    �[49m�[43m)�[49m

E           �[1;32m      5�[0m �[43m)�[49m

E           �[1;32m      6�[0m df �[38;5;241m=�[39m df�[38;5;241m.�[39msort_values(�[38;5;124m'�[39m�[38;5;124mdate_first�[39m�[38;5;124m'�[39m)�[38;5;241m.�[39mreset_index(drop�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

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E           File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/io/parquet.py:470�[0m, in �[0;36mread_parquet�[0;34m(filepath_or_buffer, engine, columns, filters, row_groups, skiprows, num_rows, strings_to_categorical, use_pandas_metadata, use_python_file_object, categorical_partitions, open_file_options, args, **kwargs)�[0m

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-15 23:38:54.854637: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-15 23:38:58.227455: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-15 23:38:58.227561: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-15 23:38:58.228381: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-15 23:38:58.228443: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-15 23:38:58.229088: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-15 23:38:58.229137: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-15 23:38:58.229763: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-15 23:38:58.229814: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file10dbnmhk.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11575   2400    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 864 passed, 13 skipped, 1438 warnings in 1675.29s (0:27:55) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins12516141345922957339.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 9997afdfc44417a0f3a08a963a5f2a751641c123, no merge conflicts.
Running as SYSTEM
Setting status of 9997afdfc44417a0f3a08a963a5f2a751641c123 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1846/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 9997afdfc44417a0f3a08a963a5f2a751641c123^{commit} # timeout=10
Checking out Revision 9997afdfc44417a0f3a08a963a5f2a751641c123 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 9997afdfc44417a0f3a08a963a5f2a751641c123 # timeout=10
Commit message: "update transformer model"
 > git rev-list --no-walk 930146caa956b51c56acc3f27e3f670da608a697 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins2771277517546710593.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
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Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+54.g9997afdf.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.9,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.9,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+54.g9997afdf,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='1396596191'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-_53c0g3i
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-_53c0g3i
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (8.1.3)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (3.1.2)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+11.geb606d5) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=214d8ac42ae4ef326f6eceb6a80c1ef576cb6b4786287a746453652fdd997940
  Stored in directory: /tmp/pip-ephem-wheel-cache-x5jc17wy/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-qg2d4kx9
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-qg2d4kx9
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+11.geb606d5)
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)
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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=57b215f173c50a7de10eddc7d6e82361b4b8164cb9a5137fc85ade2c0779a917
  Stored in directory: /tmp/pip-ephem-wheel-cache-w0v8yoo1/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 878 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 29%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 30%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f22b80a0cd0>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f22b80a0cd0>

cell = {'cell_type': 'code', 'execution_count': 16, 'id': '5ba81642', 'metadata': {'execution': {'iopub.status.busy': '2022-1....sort_values('date_first').reset_index(drop=True)\ndf.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))'}

cell_index = 31

exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '4d65a846-8a67-42...e, 'engine': '4d65a846-8a67-4245-b8e9-8857e5a6ef18', 'started': '2022-11-16T00:08:39.246299Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           df = get_lib().read_parquet(

E               glob.glob(

E                   os.path.join(DATA_FOLDER, "train/.parquet")

E               )

E           )

E           df = df.sort_values('date_first').reset_index(drop=True)

E           df.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mRuntimeError�[0m                              Traceback (most recent call last)

E           Cell �[0;32mIn [16], line 1�[0m

E           �[0;32m----> 1�[0m df �[38;5;241m=�[39m �[43mget_lib�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mread_parquet�[49m�[43m(�[49m

E           �[1;32m      2�[0m �[43m    �[49m�[43mglob�[49m�[38;5;241;43m.�[39;49m�[43mglob�[49m�[43m(�[49m

E           �[1;32m      3�[0m �[43m        �[49m�[43mos�[49m�[38;5;241;43m.�[39;49m�[43mpath�[49m�[38;5;241;43m.�[39;49m�[43mjoin�[49m�[43m(�[49m�[43mDATA_FOLDER�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mtrain/.parquet�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m

E           �[1;32m      4�[0m �[43m    �[49m�[43m)�[49m

E           �[1;32m      5�[0m �[43m)�[49m

E           �[1;32m      6�[0m df �[38;5;241m=�[39m df�[38;5;241m.�[39msort_values(�[38;5;124m'�[39m�[38;5;124mdate_first�[39m�[38;5;124m'�[39m)�[38;5;241m.�[39mreset_index(drop�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-16 00:08:29.843803: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-16 00:08:33.237825: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-16 00:08:33.237933: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-16 00:08:33.238791: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-16 00:08:33.238849: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-16 00:08:33.239445: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-16 00:08:33.239496: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-16 00:08:33.240275: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-16 00:08:33.240329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file3ye_cllj.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11575   2400    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 864 passed, 13 skipped, 1438 warnings in 1675.81s (0:27:55) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins2323149362254738311.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 088d4557d963d58ae3707e0792bf8ee2e2694d4b, no merge conflicts.
Running as SYSTEM
Setting status of 088d4557d963d58ae3707e0792bf8ee2e2694d4b to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1847/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 088d4557d963d58ae3707e0792bf8ee2e2694d4b^{commit} # timeout=10
Checking out Revision 088d4557d963d58ae3707e0792bf8ee2e2694d4b (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 088d4557d963d58ae3707e0792bf8ee2e2694d4b # timeout=10
Commit message: "fix transformer error"
 > git rev-list --no-walk 9997afdfc44417a0f3a08a963a5f2a751641c123 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins12982868784417956842.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
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Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
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Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
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Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+55.g088d4557.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.9,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.9,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+55.g088d4557,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='852743331'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-qcwc2u9k
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-qcwc2u9k
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.4.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (3.1.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.4)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (8.1.3)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.8.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+11.geb606d5) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=2114952970c9051d48a9c417adc31cdfccb55a270c400d6d9174fae9a7e9b4a4
  Stored in directory: /tmp/pip-ephem-wheel-cache-h0v29sy9/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-uv0qpes4
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-uv0qpes4
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+11.geb606d5)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=a5f4b021a922c9ae66391d4cf542afd82666bb1a050b1fd1c4bbf6e1bb2cf474
  Stored in directory: /tmp/pip-ephem-wheel-cache-lno842_4/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 878 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 22%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 28%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 29%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 29%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 30%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 30%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 40%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 43%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

tests/unit/tf/models/test_base.py s.........................             [ 49%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 53%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 63%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f37b41378b0>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f37b41378b0>

cell = {'cell_type': 'code', 'execution_count': 16, 'id': '5ba81642', 'metadata': {'execution': {'iopub.status.busy': '2022-1....sort_values('date_first').reset_index(drop=True)\ndf.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))'}

cell_index = 31

exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'e3b74537-142e-40...e, 'engine': 'e3b74537-142e-403e-99b3-44dc9b7eb0d3', 'started': '2022-11-16T00:38:17.758486Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           df = get_lib().read_parquet(

E               glob.glob(

E                   os.path.join(DATA_FOLDER, "train/.parquet")

E               )

E           )

E           df = df.sort_values('date_first').reset_index(drop=True)

E           df.to_parquet(os.path.join(DATA_FOLDER, "train_sorted.parquet"))

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mRuntimeError�[0m                              Traceback (most recent call last)

E           Cell �[0;32mIn [16], line 1�[0m

E           �[0;32m----> 1�[0m df �[38;5;241m=�[39m �[43mget_lib�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mread_parquet�[49m�[43m(�[49m

E           �[1;32m      2�[0m �[43m    �[49m�[43mglob�[49m�[38;5;241;43m.�[39;49m�[43mglob�[49m�[43m(�[49m

E           �[1;32m      3�[0m �[43m        �[49m�[43mos�[49m�[38;5;241;43m.�[39;49m�[43mpath�[49m�[38;5;241;43m.�[39;49m�[43mjoin�[49m�[43m(�[49m�[43mDATA_FOLDER�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mtrain/.parquet�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m

E           �[1;32m      4�[0m �[43m    �[49m�[43m)�[49m

E           �[1;32m      5�[0m �[43m)�[49m

E           �[1;32m      6�[0m df �[38;5;241m=�[39m df�[38;5;241m.�[39msort_values(�[38;5;124m'�[39m�[38;5;124mdate_first�[39m�[38;5;124m'�[39m)�[38;5;241m.�[39mreset_index(drop�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-16 00:38:08.389909: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-16 00:38:11.752825: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-16 00:38:11.752932: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-16 00:38:11.753774: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-16 00:38:11.753827: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-16 00:38:11.754437: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-16 00:38:11.754487: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-16 00:38:11.755113: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-16 00:38:11.755161: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file2wmzo7j2.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11575   2400    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 864 passed, 13 skipped, 1438 warnings in 1682.41s (0:28:02) =====

/usr/local/lib/python3.8/dist-packages/coverage/data.py:130: CoverageWarning: Data file '/var/jenkins_home/workspace/merlin_models/models/.coverage.10.20.17.231.3777.408053' doesn't seem to be a coverage data file: cannot unpack non-iterable NoneType object

data._warn(str(exc))

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins4177420172665763549.sh

bschifferer
bschifferer approved these changes Nov 22, 2022
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Looks great! I added one small comment to use the dmodel parameter for the first MLP block as well

@nvidia-merlin-bot
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GitHub pull request #849 of commit 4f5112de5f693675ba37c37940a47e458b0b7a72, no merge conflicts.
Running as SYSTEM
Setting status of 4f5112de5f693675ba37c37940a47e458b0b7a72 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1922/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 4f5112de5f693675ba37c37940a47e458b0b7a72^{commit} # timeout=10
Checking out Revision 4f5112de5f693675ba37c37940a47e458b0b7a72 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 4f5112de5f693675ba37c37940a47e458b0b7a72 # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk 42363d8b0e089586d1d1a3746801a36e68dc0d68 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins10844477794211307891.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
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Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
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Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+70.g4f5112de.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+70.g4f5112de,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2326016832'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-rlj8xgcg
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-rlj8xgcg
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=a66611f12acce01d8e78f74f6182b3f93b2bdb568ed94c33623295ad08f250db
  Stored in directory: /tmp/pip-ephem-wheel-cache-dq_kdrxl/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-1c0n87a9
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-1c0n87a9
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.8 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.8.0+16.g04ff522)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (1.8.1)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=ddc4979ab967d84d4afe7d912401c7d678b28687d5921bb75b13c7a3b2c54307
  Stored in directory: /tmp/pip-ephem-wheel-cache-9cz5ml26/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=6b004247302cb8fcc6f30fe0b849b20adc56cfd4c8cfbdcc5da20dcbdc5b7b99
  Stored in directory: /tmp/pip-ephem-wheel-cache-9cz5ml26/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 883 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 121 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 87 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 59 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filear30_p5h.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/.local/lib/python3.8/site-packages/distributed/node.py:180: UserWarning: Port 8787 is already in use.

Perhaps you already have a cluster running?

Hosting the HTTP server on port 34661 instead

warnings.warn(


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11581   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 870 passed, 13 skipped, 1453 warnings in 1845.09s (0:30:45) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins8059346956794685439.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 7517fca6ecef3f411e360793ed51f709563e8633, no merge conflicts.
Running as SYSTEM
Setting status of 7517fca6ecef3f411e360793ed51f709563e8633 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1930/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 7517fca6ecef3f411e360793ed51f709563e8633^{commit} # timeout=10
Checking out Revision 7517fca6ecef3f411e360793ed51f709563e8633 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 7517fca6ecef3f411e360793ed51f709563e8633 # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk 60c68dd8311911b00b1e5ddd0317d6e5f0be9951 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins11408462300914969896.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
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Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
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Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+72.g7517fca6.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+72.g7517fca6,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2408053124'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-u3ojvdat
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-u3ojvdat
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.2.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (3.19.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.7.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.8.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.4.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+12.g025f10d) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=0ee4a421512674480b1ea7b1bbd5deee7f889703ea3f35325197c5163c6751fb
  Stored in directory: /tmp/pip-ephem-wheel-cache-3rvpz1_1/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-0_dryk0k
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-0_dryk0k
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit dec7bacd4c215093e2d27b8abcb566dc0e9e1359
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+7.gdec7bacd) (0.9.0+12.g025f10d)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.1 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+7.gdec7bacd) (1.8.1)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+7.gdec7bacd-cp38-cp38-linux_x86_64.whl size=257588 sha256=f89de9cc33e47158095c2377b1c9aff689ccf8affeba44b01c72b3be9ce2edfe
  Stored in directory: /tmp/pip-ephem-wheel-cache-uh320v7i/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=e1004bbe63f2f37966c244017adcbe22237bf563970d37387cc3ffb7f342f8a2
  Stored in directory: /tmp/pip-ephem-wheel-cache-uh320v7i/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+7.gdec7bacd
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 884 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 32%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

...........................................                              [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 121 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 87 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 59 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filel718gfy4.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11581   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 871 passed, 13 skipped, 1452 warnings in 1861.93s (0:31:01) ==========

/usr/local/lib/python3.8/dist-packages/coverage/data.py:130: CoverageWarning: Data file '/var/jenkins_home/workspace/merlin_models/models/.coverage.10.20.17.231.15818.769283' doesn't seem to be a coverage data file: cannot unpack non-iterable NoneType object

data._warn(str(exc))

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins15026770635802348566.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit f0f164d3fc0e166de87e082988f6d5cb37428b2c, no merge conflicts.
Running as SYSTEM
Setting status of f0f164d3fc0e166de87e082988f6d5cb37428b2c to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1932/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse f0f164d3fc0e166de87e082988f6d5cb37428b2c^{commit} # timeout=10
Checking out Revision f0f164d3fc0e166de87e082988f6d5cb37428b2c (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f f0f164d3fc0e166de87e082988f6d5cb37428b2c # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk 6ffb409f9964ee68176bb99978b34afaa1090102 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins271187011286243050.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
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Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+74.gf0f164d3.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+74.gf0f164d3,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2886572089'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-dlaeqh41
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-dlaeqh41
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.5.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (3.19.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.2.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.12.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.8.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.7.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.4.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+12.g025f10d) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=52827f685eda03422ee77d398f4213647a892f41df0a5267a339fb836bd34ec6
  Stored in directory: /tmp/pip-ephem-wheel-cache-a145hfh1/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-t_mcwjj8
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-t_mcwjj8
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit dec7bacd4c215093e2d27b8abcb566dc0e9e1359
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+7.gdec7bacd) (1.8.1)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.5 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+7.gdec7bacd) (0.9.0+12.g025f10d)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+7.gdec7bacd-cp38-cp38-linux_x86_64.whl size=257588 sha256=7a43322ce21d15b241ff68487c542863b44a0ee7a2d7766aaad64ef320e3378a
  Stored in directory: /tmp/pip-ephem-wheel-cache-1ls7cepn/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=88a9fed3b6a6fca04e064aa60702cd032e01c803f62bd3f1091d4e5999a1630d
  Stored in directory: /tmp/pip-ephem-wheel-cache-1ls7cepn/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+7.gdec7bacd
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py F [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_________________ test_usecase_accelerate_training_by_lazyadam _________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f5af0e83100>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
@pytest.mark.skipif(not HAS_GPU, reason="No GPU available")
def test_usecase_accelerate_training_by_lazyadam(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py:25:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f5af0e83100>

cell = {'cell_type': 'code', 'execution_count': 7, 'id': '0500ad25-29e0-40c8-85bc-6e3864107c6a', 'metadata': {'execution': {'...e_train_function_3861]']}], 'source': 'model1.compile(optimizer="adam")\nmodel1.fit(train, batch_size=1024, epochs=1)'}

cell_index = 12

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'd4e84b...e, 'engine': 'd4e84bdd-66e3-487c-b1b1-b4ebb95fccfc', 'started': '2022-11-22T21:30:02.166296Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model1.compile(optimizer="adam")

E           model1.fit(train, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [7], line 2�[0m

E           �[1;32m      1�[0m model1�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39m�[38;5;124m"�[39m�[38;5;124madam�[39m�[38;5;124m"�[39m)

E           �[0;32m----> 2�[0m �[43mmodel1�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

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E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

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E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

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E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

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E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

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E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16291/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16291/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3861]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16291/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16291/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3861]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-22 21:29:55.268561: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-22 21:29:59.394686: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-22 21:29:59.394787: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-22 21:29:59.395655: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-22 21:29:59.395712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-22 21:29:59.396257: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-22 21:29:59.396309: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-22 21:29:59.396909: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-22 21:29:59.396959: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-22 21:30:16.396625: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 33095680/17069309952

2022-11-22 21:30:16.396720: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4116656444

MaxInUse:                   4116803644

NumAllocs:                         240

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 21:30:16.396762: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 21:30:16.396783: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 21:30:16.396801: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 21:30:16.396818: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 21:30:16.396836: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 21:30:16.396853: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-11-22 21:30:16.396870: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 6

2022-11-22 21:30:16.396887: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-22 21:30:16.396904: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 21:30:16.396921: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 21:30:16.396938: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-11-22 21:30:16.396955: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 21:30:16.396972: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 21:30:16.397028: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 21:30:16.397048: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 21:30:16.397065: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 21:30:16.397081: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 4

2022-11-22 21:30:16.397098: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-22 21:30:16.397115: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 4

2022-11-22 21:30:16.397132: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 21:30:16.397149: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-11-22 21:30:16.397166: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-11-22 21:30:16.397183: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-11-22 21:30:16.397200: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-22 21:30:16.397216: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-11-22 21:30:16.397233: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 21:30:16.397281: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 21:30:16.398875: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 33095680/17069309952

2022-11-22 21:30:16.398920: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4118064828

MaxInUse:                   4118064828

NumAllocs:                         243

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 21:30:16.398956: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 21:30:16.398975: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 21:30:16.398992: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 21:30:16.399010: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 21:30:16.399027: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 21:30:16.399044: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-11-22 21:30:16.399061: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 7

2022-11-22 21:30:16.399078: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-22 21:30:16.399095: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 21:30:16.399111: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 21:30:16.399128: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-11-22 21:30:16.399151: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 21:30:16.399168: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 21:30:16.399185: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 21:30:16.399202: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 21:30:16.399219: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 21:30:16.399262: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-22 21:30:16.399282: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 4

2022-11-22 21:30:16.399299: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 4

2022-11-22 21:30:16.399316: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 21:30:16.399333: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-11-22 21:30:16.399350: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-11-22 21:30:16.399366: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-11-22 21:30:16.399383: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-22 21:30:16.399400: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-11-22 21:30:16.399417: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 21:30:16.399441: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

_______________ test_usecase_incremental_training_layer_freezing _______________


tb = <testbook.client.TestbookNotebookClient object at 0x7f5bac09c820>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_incremental_training_layer_freezing(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py:22:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f5bac09c820>

cell = {'cell_type': 'code', 'execution_count': 8, 'id': '791e06ec-c0cb-4c0f-9e41-7e5c8fa1dc4e', 'metadata': {'execution': {'...: 'model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))\nmodel.fit(day_1, batch_size=1024, epochs=1)'}

cell_index = 13

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '7eb7e9...e, 'engine': '7eb7e96c-8c51-4cb8-ab49-e35287916eaf', 'started': '2022-11-22T21:32:27.786221Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))

E           model.fit(day_1, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [8], line 2�[0m

E           �[1;32m      1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))

E           �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py:1127�[0m, in �[0;36mfunc_graph_from_py_func..autograph_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m   1125�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint:disable=broad-except�[39;00m

E           �[1;32m   1126�[0m   �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(e, �[38;5;124m"�[39m�[38;5;124mag_error_metadata�[39m�[38;5;124m"�[39m):

E           �[0;32m-> 1127�[0m     �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mag_error_metadata�[38;5;241m.�[39mto_exception(e)

E           �[1;32m   1128�[0m   �[38;5;28;01melse�[39;00m:

E           �[1;32m   1129�[0m     �[38;5;28;01mraise�[39;00m

E

E           �[0;31mResourceExhaustedError�[0m: in user code:

E

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function  *

E                   return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function  **

E                   outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step  **

E                   outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                   self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                   return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 646, in apply_gradients

E                   self._create_all_weights(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 860, in _create_all_weights

E                   self._create_slots(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 124, in _create_slots

E                   self.add_slot(var, 'v')

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 946, in add_slot

E                   weight = tf.Variable(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/initializers/initializers_v2.py", line 152, in call

E                   return tf.zeros(shape, dtype)

E

E               ResourceExhaustedError: OOM when allocating tensor with shape[3078307,88] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0 [Op:Fill]

E

E           ResourceExhaustedError: in user code:

E

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function  *

E                   return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function  **

E                   outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step  **

E                   outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                   self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                   return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 646, in apply_gradients

E                   self._create_all_weights(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 860, in _create_all_weights

E                   self._create_slots(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 124, in _create_slots

E                   self.add_slot(var, 'v')

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 946, in add_slot

E                   weight = tf.Variable(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/initializers/initializers_v2.py", line 152, in call

E                   return tf.zeros(shape, dtype)

E

E               ResourceExhaustedError: OOM when allocating tensor with shape[3078307,88] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0 [Op:Fill]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-22 21:32:20.809178: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-22 21:32:24.952269: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-22 21:32:24.952375: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-22 21:32:24.953214: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-22 21:32:24.953273: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-22 21:32:24.953861: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-22 21:32:24.953914: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-22 21:32:24.955036: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-22 21:32:24.955182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-22 21:32:36.728153: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 30998528/17069309952

2022-11-22 21:32:36.728197: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      2854898870

MaxInUse:                   3529965729

NumAllocs:                         233

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 21:32:36.728220: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 21:32:36.728228: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 2

2022-11-22 21:32:36.728235: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 26

2022-11-22 21:32:36.728240: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 3

2022-11-22 21:32:36.728246: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 6

2022-11-22 21:32:36.728251: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 6

2022-11-22 21:32:36.728257: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 21:32:36.728262: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 5

2022-11-22 21:32:36.728268: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 21:32:36.728273: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 3

2022-11-22 21:32:36.728279: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 5

2022-11-22 21:32:36.728285: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 21:32:36.728290: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-22 21:32:36.728316: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 5

2022-11-22 21:32:36.728324: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 60720, 1

2022-11-22 21:32:36.728329: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 1

2022-11-22 21:32:36.728335: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-11-22 21:32:36.728340: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 2

2022-11-22 21:32:36.728346: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 21:32:36.728351: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-22 21:32:36.728357: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 3

2022-11-22 21:32:36.728362: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 3

2022-11-22 21:32:36.728368: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 2

2022-11-22 21:32:36.728373: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-11-22 21:32:36.728379: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-11-22 21:32:36.728384: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-22 21:32:36.728390: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 2

2022-11-22 21:32:36.728395: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 2

2022-11-22 21:32:36.728429: W tensorflow/core/framework/op_kernel.cc:1745] OP_REQUIRES failed at constant_op.cc:175 : RESOURCE_EXHAUSTED: OOM when allocating tensor with shape[3078307,88] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_fileus5pt8bq.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     54    87%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     32    89%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    103    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      7    90%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11583   2403    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 2 failed, 871 passed, 13 skipped, 1460 warnings in 1830.91s (0:30:30) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins6939229614436759319.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 06beaff5086901fdb5dbf40c5f790e7b3b9014e5, no merge conflicts.
Running as SYSTEM
Setting status of 06beaff5086901fdb5dbf40c5f790e7b3b9014e5 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1933/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 06beaff5086901fdb5dbf40c5f790e7b3b9014e5^{commit} # timeout=10
Checking out Revision 06beaff5086901fdb5dbf40c5f790e7b3b9014e5 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 06beaff5086901fdb5dbf40c5f790e7b3b9014e5 # timeout=10
Commit message: "update mlp blocks"
 > git rev-list --no-walk f0f164d3fc0e166de87e082988f6d5cb37428b2c # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins13041600580180809399.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+75.g06beaff5.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+75.g06beaff5,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='1796617896'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-4lcvci_a
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-4lcvci_a
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.2.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (3.19.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (0.4.3)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.8.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.4.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+12.g025f10d) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2.8.2)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=4942af86060c58f940c6575866b2d233e9e7a649a8a14b7a51ebee335b1c1a94
  Stored in directory: /tmp/pip-ephem-wheel-cache-sacw1ata/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-gho6re39
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-gho6re39
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit dec7bacd4c215093e2d27b8abcb566dc0e9e1359
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+7.gdec7bacd) (0.9.0+12.g025f10d)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.2 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+7.gdec7bacd) (1.8.1)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+7.gdec7bacd-cp38-cp38-linux_x86_64.whl size=257588 sha256=c147e7a47d124938e1ed9bf4bfba9be83d05cc6564815867d898a4e41fc86c63
  Stored in directory: /tmp/pip-ephem-wheel-cache-qdkb_lfz/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=76f8311622555ba6c155e55b3c3a35e6ec7bc721e9972b8122a590b2bf75a294
  Stored in directory: /tmp/pip-ephem-wheel-cache-qdkb_lfz/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+7.gdec7bacd
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file21nw30gk.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11583   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 873 passed, 13 skipped, 1460 warnings in 1862.14s (0:31:02) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins11723189988539157054.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 7e446c0139bbe92d519a36d59e1f09c620696ac0, no merge conflicts.
Running as SYSTEM
Setting status of 7e446c0139bbe92d519a36d59e1f09c620696ac0 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1934/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 7e446c0139bbe92d519a36d59e1f09c620696ac0^{commit} # timeout=10
Checking out Revision 7e446c0139bbe92d519a36d59e1f09c620696ac0 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 7e446c0139bbe92d519a36d59e1f09c620696ac0 # timeout=10
Commit message: "Delete ecommerce-session-based-next-item-prediction-for-fashion.ipynb"
 > git rev-list --no-walk 06beaff5086901fdb5dbf40c5f790e7b3b9014e5 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins10509902437678550823.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
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Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+76.g7e446c01.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+76.g7e446c01,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='4194767101'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-vbayhxm4
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-vbayhxm4
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.2.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.5.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (3.19.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (0.4.3)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.12.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.8.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.4.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+12.g025f10d) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=83388b35fd7ecf6e74503398b2c4aac3eb94e1b66c73ccf74897e7fb3e4f5c29
  Stored in directory: /tmp/pip-ephem-wheel-cache-98__q1dq/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-7r4pmvum
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-7r4pmvum
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit dec7bacd4c215093e2d27b8abcb566dc0e9e1359
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+7.gdec7bacd) (0.9.0+12.g025f10d)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 952.4 kB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+7.gdec7bacd) (1.8.1)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+7.gdec7bacd-cp38-cp38-linux_x86_64.whl size=257588 sha256=f69eb4bd99b36450902af16720eb713c38f9684feabf60efe6c3ceb5e27e1796
  Stored in directory: /tmp/pip-ephem-wheel-cache-9bsnkfz0/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=6afd44032cf479ba80bb60d252cde675db1716231584fa0afd7c0c042a2de1a4
  Stored in directory: /tmp/pip-ephem-wheel-cache-9bsnkfz0/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+7.gdec7bacd
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py F [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_________________ test_usecase_accelerate_training_by_lazyadam _________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f9a7c1ee130>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
@pytest.mark.skipif(not HAS_GPU, reason="No GPU available")
def test_usecase_accelerate_training_by_lazyadam(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py:25:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f9a7c1ee130>

cell = {'cell_type': 'code', 'execution_count': 7, 'id': '0500ad25-29e0-40c8-85bc-6e3864107c6a', 'metadata': {'execution': {'...e_train_function_3861]']}], 'source': 'model1.compile(optimizer="adam")\nmodel1.fit(train, batch_size=1024, epochs=1)'}

cell_index = 12

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '03efa6...e, 'engine': '03efa641-5990-47a7-bb9e-e396dd8938d4', 'started': '2022-11-22T22:39:47.043720Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model1.compile(optimizer="adam")

E           model1.fit(train, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [7], line 2�[0m

E           �[1;32m      1�[0m model1�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39m�[38;5;124m"�[39m�[38;5;124madam�[39m�[38;5;124m"�[39m)

E           �[0;32m----> 2�[0m �[43mmodel1�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

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E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

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E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

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E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

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E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

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E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_13901/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_17/mul_4'

E           Detected at node 'Adam/Adam/update_17/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_13901/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_17/mul_4'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3861]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_13901/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_17/mul_4'

E           Detected at node 'Adam/Adam/update_17/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_13901/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_17/mul_4'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3861]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-22 22:39:40.096939: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-22 22:39:44.201070: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-22 22:39:44.201182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-22 22:39:44.201890: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-22 22:39:44.201947: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-22 22:39:44.202530: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-22 22:39:44.202579: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-22 22:39:44.203165: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-22 22:39:44.203219: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-22 22:40:02.013343: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 4784128/17069309952

2022-11-22 22:40:02.013407: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4363218036

MaxInUse:                   4363218036

NumAllocs:                         243

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:40:02.013431: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:40:02.013441: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:40:02.013448: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 22:40:02.013454: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 7

2022-11-22 22:40:02.013460: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:40:02.013466: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-11-22 22:40:02.013472: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 7

2022-11-22 22:40:02.013478: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 22:40:02.013484: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:40:02.013490: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 4

2022-11-22 22:40:02.013497: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-11-22 22:40:02.013503: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:40:02.013509: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 22:40:02.013538: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 22:40:02.013546: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 22:40:02.013552: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 22:40:02.013558: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 22:40:02.013564: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 4

2022-11-22 22:40:02.013570: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 3

2022-11-22 22:40:02.013576: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 22:40:02.013582: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-11-22 22:40:02.013589: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-22 22:40:02.013595: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 22:40:02.013601: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:40:02.013607: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-22 22:40:02.013613: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:40:02.013639: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 22:40:02.014392: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 39970560 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 4784128/17069309952

2022-11-22 22:40:02.014413: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4371867676

MaxInUse:                   4371867676

NumAllocs:                         247

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:40:02.014428: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:40:02.014436: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:40:02.014442: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 22:40:02.014448: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 22:40:02.014454: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:40:02.014460: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-11-22 22:40:02.014466: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 8

2022-11-22 22:40:02.014472: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 22:40:02.014478: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:40:02.014484: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 4

2022-11-22 22:40:02.014490: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-11-22 22:40:02.014496: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:40:02.014502: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 22:40:02.014508: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 22:40:02.014514: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 22:40:02.014520: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 22:40:02.014538: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 22:40:02.014546: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 4

2022-11-22 22:40:02.014552: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-22 22:40:02.014557: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 22:40:02.014563: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-11-22 22:40:02.014569: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-22 22:40:02.014575: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 22:40:02.014581: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:40:02.014587: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-22 22:40:02.014593: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:40:02.014602: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 22:40:02.015081: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 4784128/17069309952

2022-11-22 22:40:02.015097: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4371867676

MaxInUse:                   4371867676

NumAllocs:                         247

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:40:02.015110: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:40:02.015116: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:40:02.015122: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 22:40:02.015128: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 22:40:02.015134: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:40:02.015140: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-11-22 22:40:02.015146: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 8

2022-11-22 22:40:02.015152: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 22:40:02.015158: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:40:02.015164: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 4

2022-11-22 22:40:02.015170: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-11-22 22:40:02.015176: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:40:02.015182: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 22:40:02.015188: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 22:40:02.015194: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 22:40:02.015200: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 22:40:02.015206: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 22:40:02.015212: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 4

2022-11-22 22:40:02.015227: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-22 22:40:02.015235: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 22:40:02.015241: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-11-22 22:40:02.015247: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-22 22:40:02.015253: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 22:40:02.015258: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:40:02.015264: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-22 22:40:02.015270: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:40:02.015279: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 22:40:02.015804: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 56589504 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 4784128/17069309952

2022-11-22 22:40:02.015822: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4388093756

MaxInUse:                   4388093756

NumAllocs:                         252

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:40:02.015834: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:40:02.015841: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:40:02.015847: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 22:40:02.015853: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 22:40:02.015859: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:40:02.015865: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 8

2022-11-22 22:40:02.015871: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 9

2022-11-22 22:40:02.015877: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 22:40:02.015883: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:40:02.015889: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 4

2022-11-22 22:40:02.015895: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-22 22:40:02.015901: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:40:02.015907: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 22:40:02.015913: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 22:40:02.015919: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 22:40:02.015925: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 22:40:02.015931: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 22:40:02.015937: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-22 22:40:02.015943: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-22 22:40:02.015949: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 22:40:02.015955: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-22 22:40:02.015971: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-22 22:40:02.015978: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 22:40:02.015984: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:40:02.015990: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-22 22:40:02.015996: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:40:02.016005: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 22:40:02.016486: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 135407776 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 4784128/17069309952

2022-11-22 22:40:02.016503: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4388093756

MaxInUse:                   4388093756

NumAllocs:                         252

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:40:02.016514: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:40:02.016521: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:40:02.016527: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 22:40:02.016533: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 22:40:02.016539: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:40:02.016545: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 8

2022-11-22 22:40:02.016550: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 9

2022-11-22 22:40:02.016556: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 22:40:02.016562: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:40:02.016568: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 4

2022-11-22 22:40:02.016574: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-22 22:40:02.016580: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:40:02.016586: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 22:40:02.016592: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 22:40:02.016598: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 22:40:02.016604: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 22:40:02.016610: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 22:40:02.016616: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-22 22:40:02.016622: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-22 22:40:02.016628: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 22:40:02.016634: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-22 22:40:02.016640: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-22 22:40:02.016646: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 22:40:02.016652: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:40:02.016667: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-22 22:40:02.016674: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:40:02.016682: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 22:40:02.017228: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 18678720 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 4784128/17069309952

2022-11-22 22:40:02.017245: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4396692416

MaxInUse:                   4396692416

NumAllocs:                         261

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:40:02.017258: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:40:02.017265: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:40:02.017271: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-22 22:40:02.017277: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 22:40:02.017283: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:40:02.017289: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10

2022-11-22 22:40:02.017295: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 9

2022-11-22 22:40:02.017301: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-22 22:40:02.017307: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:40:02.017313: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-22 22:40:02.017318: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-22 22:40:02.017324: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:40:02.017330: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5

2022-11-22 22:40:02.017336: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 22:40:02.017342: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 22:40:02.017348: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 22:40:02.017355: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-22 22:40:02.017361: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-22 22:40:02.017367: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-22 22:40:02.017372: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-22 22:40:02.017378: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-22 22:40:02.017384: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-22 22:40:02.017390: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 22:40:02.017396: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:40:02.017402: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-22 22:40:02.017408: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:40:02.017426: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

_______________ test_usecase_incremental_training_layer_freezing _______________


tb = <testbook.client.TestbookNotebookClient object at 0x7f9a9414e730>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_incremental_training_layer_freezing(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py:22:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f9a9414e730>

cell = {'cell_type': 'code', 'execution_count': 8, 'id': '791e06ec-c0cb-4c0f-9e41-7e5c8fa1dc4e', 'metadata': {'execution': {'...: 'model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))\nmodel.fit(day_1, batch_size=1024, epochs=1)'}

cell_index = 13

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'ddb31d...e, 'engine': 'ddb31d68-4a53-4a4b-a1d6-3a228fbd6f10', 'started': '2022-11-22T22:42:14.157276Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))

E           model.fit(day_1, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [8], line 2�[0m

E           �[1;32m      1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))

E           �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

E           �[0;32m---> 54�[0m   tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,

E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

E           �[1;32m     56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:

E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_18299/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_18299/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_4007]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_18299/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_18299/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_4007]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-22 22:42:07.177244: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-22 22:42:11.320715: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-22 22:42:11.320827: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-22 22:42:11.321530: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-22 22:42:11.321582: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13873 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-22 22:42:11.322203: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-22 22:42:11.322253: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13873 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-22 22:42:11.322827: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-22 22:42:11.322876: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13873 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-22 22:42:28.389566: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-11-22 22:42:28.389622: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4540644232

MaxInUse:                   4540644232

NumAllocs:                         278

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:42:28.389646: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:42:28.389656: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:42:28.389664: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36

2022-11-22 22:42:28.389670: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 22:42:28.389677: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:42:28.389683: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 9

2022-11-22 22:42:28.389689: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 6

2022-11-22 22:42:28.389696: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5

2022-11-22 22:42:28.389703: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:42:28.389709: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 22:42:28.389715: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-11-22 22:42:28.389722: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6

2022-11-22 22:42:28.389728: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:42:28.389758: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5

2022-11-22 22:42:28.389767: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6

2022-11-22 22:42:28.389773: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 1

2022-11-22 22:42:28.389780: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-11-22 22:42:28.389786: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3

2022-11-22 22:42:28.389792: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 4

2022-11-22 22:42:28.389799: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-22 22:42:28.389805: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 4

2022-11-22 22:42:28.389811: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 3

2022-11-22 22:42:28.389818: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 3

2022-11-22 22:42:28.389824: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5

2022-11-22 22:42:28.389830: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-22 22:42:28.389837: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:42:28.389843: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 5

2022-11-22 22:42:28.389849: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:42:28.389876: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 22:42:28.390564: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-11-22 22:42:28.390585: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4548070920

MaxInUse:                   4548070920

NumAllocs:                         281

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 22:42:28.390601: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 22:42:28.390608: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 22:42:28.390615: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36

2022-11-22 22:42:28.390621: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 22:42:28.390628: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 22:42:28.390634: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 9

2022-11-22 22:42:28.390640: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 7

2022-11-22 22:42:28.390647: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5

2022-11-22 22:42:28.390653: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 22:42:28.390659: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 22:42:28.390666: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-22 22:42:28.390672: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6

2022-11-22 22:42:28.390678: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 22:42:28.390685: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5

2022-11-22 22:42:28.390703: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6

2022-11-22 22:42:28.390710: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 1

2022-11-22 22:42:28.390717: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-11-22 22:42:28.390723: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3

2022-11-22 22:42:28.390730: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 4

2022-11-22 22:42:28.390736: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-22 22:42:28.390742: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 4

2022-11-22 22:42:28.390749: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 22:42:28.390755: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 3

2022-11-22 22:42:28.390761: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5

2022-11-22 22:42:28.390768: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-22 22:42:28.390774: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 22:42:28.390780: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 5

2022-11-22 22:42:28.390787: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 22:42:28.390796: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file762zy6kj.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     39    90%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     54    87%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     32    89%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    103    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      7    90%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11583   2401    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 2 failed, 871 passed, 13 skipped, 1460 warnings in 1864.75s (0:31:04) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins9125561622571182553.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit acbb41b1116d0bf91ff54a3c87a92b32af93ec44, no merge conflicts.
Running as SYSTEM
Setting status of acbb41b1116d0bf91ff54a3c87a92b32af93ec44 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1935/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse acbb41b1116d0bf91ff54a3c87a92b32af93ec44^{commit} # timeout=10
Checking out Revision acbb41b1116d0bf91ff54a3c87a92b32af93ec44 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f acbb41b1116d0bf91ff54a3c87a92b32af93ec44 # timeout=10
Commit message: "update mlp blocks"
 > git rev-list --no-walk 7e446c0139bbe92d519a36d59e1f09c620696ac0 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins17722287682663216953.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+77.gacbb41b1.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+77.gacbb41b1,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='1443403892'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-lm7hg4ih
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-lm7hg4ih
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (3.19.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.5.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.2.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+12.g025f10d) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=7e56f4bde91ef48dd5e3e18f290a9dc3ef0d7b266c0d3f9d359ae5c6a81468df
  Stored in directory: /tmp/pip-ephem-wheel-cache-fjzt305b/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-ki6i_uai
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-ki6i_uai
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit dec7bacd4c215093e2d27b8abcb566dc0e9e1359
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+7.gdec7bacd) (0.9.0+12.g025f10d)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.1 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+7.gdec7bacd) (1.8.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (21.3)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (4.64.1)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (3.19.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.10.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2022.5.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (7.0.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.2.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.3.5)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+7.gdec7bacd) (1.20.3)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.2.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (6.2)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (3.1.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.7.0)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (6.0.1)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+7.gdec7bacd-cp38-cp38-linux_x86_64.whl size=257588 sha256=399ba97676f6a8e2a72da7977cf5e9455789edf8a3ec2cdcb9829305add9ab18
  Stored in directory: /tmp/pip-ephem-wheel-cache-jnemeowk/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=afb656655cba039895543be54021d8221007aaf453e9653227df52e7d04b2515
  Stored in directory: /tmp/pip-ephem-wheel-cache-jnemeowk/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+7.gdec7bacd
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py F [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_________________ test_usecase_accelerate_training_by_lazyadam _________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f3bd033beb0>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
@pytest.mark.skipif(not HAS_GPU, reason="No GPU available")
def test_usecase_accelerate_training_by_lazyadam(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py:25:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f3bd033beb0>

cell = {'cell_type': 'code', 'execution_count': 7, 'id': '0500ad25-29e0-40c8-85bc-6e3864107c6a', 'metadata': {'execution': {'...e_train_function_3861]']}], 'source': 'model1.compile(optimizer="adam")\nmodel1.fit(train, batch_size=1024, epochs=1)'}

cell_index = 12

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'bf419e...e, 'engine': 'bf419e8d-3fc0-46b3-9ffb-7c74aea5cc99', 'started': '2022-11-22T23:15:07.490806Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model1.compile(optimizer="adam")

E           model1.fit(train, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [7], line 2�[0m

E           �[1;32m      1�[0m model1�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39m�[38;5;124m"�[39m�[38;5;124madam�[39m�[38;5;124m"�[39m)

E           �[0;32m----> 2�[0m �[43mmodel1�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

E           �[0;32m---> 54�[0m   tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,

E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

E           �[1;32m     56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:

E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16185/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16185/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3861]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16185/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_16185/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3861]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-22 23:15:00.547992: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-22 23:15:04.700664: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-22 23:15:04.700773: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-22 23:15:04.701584: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-22 23:15:04.701642: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-22 23:15:04.702243: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-22 23:15:04.702294: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-22 23:15:04.702852: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-22 23:15:04.702899: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-22 23:15:21.650894: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-11-22 23:15:21.650966: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4088916020

MaxInUse:                   4089063088

NumAllocs:                         232

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 23:15:21.650985: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 23:15:21.650994: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 23:15:21.651001: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-11-22 23:15:21.651007: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 7

2022-11-22 23:15:21.651014: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 23:15:21.651020: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-11-22 23:15:21.651026: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 6

2022-11-22 23:15:21.651032: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 23:15:21.651039: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 23:15:21.651045: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 23:15:21.651051: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 3

2022-11-22 23:15:21.651057: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 23:15:21.651064: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-22 23:15:21.651093: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 23:15:21.651100: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 23:15:21.651107: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 23:15:21.651113: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 23:15:21.651119: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-22 23:15:21.651125: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 3

2022-11-22 23:15:21.651132: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 3

2022-11-22 23:15:21.651138: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 3

2022-11-22 23:15:21.651144: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-11-22 23:15:21.651151: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-11-22 23:15:21.651157: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-22 23:15:21.651163: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-11-22 23:15:21.651169: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 23:15:21.651200: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 23:15:21.657200: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-11-22 23:15:21.657225: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4515614520

MaxInUse:                   4515614520

NumAllocs:                         249

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 23:15:21.657247: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 23:15:21.657256: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 23:15:21.657263: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-22 23:15:21.657269: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 7

2022-11-22 23:15:21.657275: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 23:15:21.657282: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-11-22 23:15:21.657288: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 7

2022-11-22 23:15:21.657294: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-22 23:15:21.657300: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 23:15:21.657307: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 23:15:21.657313: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-11-22 23:15:21.657319: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 23:15:21.657325: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5

2022-11-22 23:15:21.657332: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 23:15:21.657338: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-22 23:15:21.657345: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 23:15:21.657362: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 4

2022-11-22 23:15:21.657370: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-22 23:15:21.657377: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 4

2022-11-22 23:15:21.657383: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 3

2022-11-22 23:15:21.657389: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-11-22 23:15:21.657395: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5

2022-11-22 23:15:21.657402: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 23:15:21.657408: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 23:15:21.657414: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 5

2022-11-22 23:15:21.657420: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 23:15:21.657430: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

_______________ test_usecase_incremental_training_layer_freezing _______________


tb = <testbook.client.TestbookNotebookClient object at 0x7f3bd031e6a0>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_incremental_training_layer_freezing(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py:22:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f3bd031e6a0>

cell = {'cell_type': 'code', 'execution_count': 8, 'id': '791e06ec-c0cb-4c0f-9e41-7e5c8fa1dc4e', 'metadata': {'execution': {'...: 'model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))\nmodel.fit(day_1, batch_size=1024, epochs=1)'}

cell_index = 13

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'f234b0...e, 'engine': 'f234b033-baf6-4c0c-9357-44fa5e28ca25', 'started': '2022-11-22T23:17:31.950941Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))

E           model.fit(day_1, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [8], line 2�[0m

E           �[1;32m      1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))

E           �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

E           �[0;32m---> 54�[0m   tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,

E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

E           �[1;32m     56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:

E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_17153/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_17153/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_4007]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_17153/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_17153/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_19/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_4007]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-22 23:17:24.941326: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-22 23:17:29.102562: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-22 23:17:29.102663: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-22 23:17:29.103495: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-22 23:17:29.103554: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-22 23:17:29.104146: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-22 23:17:29.104197: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-22 23:17:29.104850: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-22 23:17:29.104899: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-22 23:17:46.298756: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 30998528/17069309952

2022-11-22 23:17:46.298812: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4232355172

MaxInUse:                   4232355172

NumAllocs:                         268

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 23:17:46.298830: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 23:17:46.298838: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 23:17:46.298844: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 35

2022-11-22 23:17:46.298851: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 23:17:46.298857: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 23:17:46.298863: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 6

2022-11-22 23:17:46.298869: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 7

2022-11-22 23:17:46.298875: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 23:17:46.298881: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 23:17:46.298888: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 4

2022-11-22 23:17:46.298894: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 3

2022-11-22 23:17:46.298900: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6

2022-11-22 23:17:46.298906: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 23:17:46.298938: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-22 23:17:46.298947: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6

2022-11-22 23:17:46.298953: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 1

2022-11-22 23:17:46.298959: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-11-22 23:17:46.298965: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3

2022-11-22 23:17:46.298971: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 4

2022-11-22 23:17:46.298977: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-22 23:17:46.298983: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 4

2022-11-22 23:17:46.298990: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-11-22 23:17:46.298996: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-11-22 23:17:46.299002: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-22 23:17:46.299008: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4

2022-11-22 23:17:46.299014: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-11-22 23:17:46.299021: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-11-22 23:17:46.299027: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 23:17:46.299049: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-22 23:17:46.304814: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 30998528/17069309952

2022-11-22 23:17:46.304840: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4647799624

MaxInUse:                   4647799624

NumAllocs:                         293

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 23:17:46.304857: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 23:17:46.304865: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-22 23:17:46.304872: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36

2022-11-22 23:17:46.304879: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-22 23:17:46.304886: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-22 23:17:46.304893: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10

2022-11-22 23:17:46.304899: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10

2022-11-22 23:17:46.304906: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5

2022-11-22 23:17:46.304912: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-22 23:17:46.304919: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-22 23:17:46.304925: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-22 23:17:46.304932: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6

2022-11-22 23:17:46.304938: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 23:17:46.304945: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5

2022-11-22 23:17:46.304964: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6

2022-11-22 23:17:46.304972: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 1

2022-11-22 23:17:46.304979: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-11-22 23:17:46.304986: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3

2022-11-22 23:17:46.304992: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-22 23:17:46.304998: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-22 23:17:46.305005: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-22 23:17:46.305012: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-22 23:17:46.305018: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-22 23:17:46.305025: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5

2022-11-22 23:17:46.305032: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-22 23:17:46.305038: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 5

2022-11-22 23:17:46.305045: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 5

2022-11-22 23:17:46.305052: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-22 23:17:46.305062: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filejnt_g_jb.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     54    87%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     32    89%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    103    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      7    90%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11583   2403    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 2 failed, 871 passed, 13 skipped, 1460 warnings in 1850.89s (0:30:50) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins2102441647632675997.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit dff99ff9ca6f3b40551434919e9508967284927f, no merge conflicts.
Running as SYSTEM
Setting status of dff99ff9ca6f3b40551434919e9508967284927f to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1936/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse dff99ff9ca6f3b40551434919e9508967284927f^{commit} # timeout=10
Checking out Revision dff99ff9ca6f3b40551434919e9508967284927f (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f dff99ff9ca6f3b40551434919e9508967284927f # timeout=10
Commit message: "fix typo"
 > git rev-list --no-walk acbb41b1116d0bf91ff54a3c87a92b32af93ec44 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins3961798536982193.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+78.gdff99ff9.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+78.gdff99ff9,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='4279243378'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-kftwduqx
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-kftwduqx
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (3.19.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.5.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.12.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.8.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+12.g025f10d) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=17ecfb0a2c53551b3b96a82a2ae97e7fd827c1a5334601f110c0f15735c8a860
  Stored in directory: /tmp/pip-ephem-wheel-cache-asnczgnq/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-9nwffy3v
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-9nwffy3v
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit dec7bacd4c215093e2d27b8abcb566dc0e9e1359
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+7.gdec7bacd) (1.8.1)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 12.7 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+7.gdec7bacd) (0.9.0+12.g025f10d)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (7.0.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.3.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (3.19.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (21.3)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2022.5.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.10.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (4.64.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2022.3.0)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+7.gdec7bacd) (1.20.3)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (0.12.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (3.1.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (8.1.3)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+7.gdec7bacd) (2.4.0)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+7.gdec7bacd-cp38-cp38-linux_x86_64.whl size=257588 sha256=8a63b25dade6dabb5c0a62131705a6c62fec2bed82ff28480d59df15e86de3d2
  Stored in directory: /tmp/pip-ephem-wheel-cache-okrzvaez/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=aab437dd329a986ef22d9f0c91d2c009512e9b7bf4f154508b2abd21a2017655
  Stored in directory: /tmp/pip-ephem-wheel-cache-okrzvaez/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+7.gdec7bacd
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py F [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_________________ test_usecase_accelerate_training_by_lazyadam _________________


tb = <testbook.client.TestbookNotebookClient object at 0x7fa7b42a6190>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
@pytest.mark.skipif(not HAS_GPU, reason="No GPU available")
def test_usecase_accelerate_training_by_lazyadam(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py:25:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7fa7b42a6190>

cell = {'cell_type': 'code', 'execution_count': 7, 'id': '0500ad25-29e0-40c8-85bc-6e3864107c6a', 'metadata': {'execution': {'...pu_async_0 [Op:Fill]\n']}], 'source': 'model1.compile(optimizer="adam")\nmodel1.fit(train, batch_size=1024, epochs=1)'}

cell_index = 12

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '8e2cd8...e, 'engine': '8e2cd85c-e1e3-4d37-9028-a96cb24052fe', 'started': '2022-11-22T23:51:07.214332Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model1.compile(optimizer="adam")

E           model1.fit(train, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [7], line 2�[0m

E           �[1;32m      1�[0m model1�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39m�[38;5;124m"�[39m�[38;5;124madam�[39m�[38;5;124m"�[39m)

E           �[0;32m----> 2�[0m �[43mmodel1�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py:1127�[0m, in �[0;36mfunc_graph_from_py_func..autograph_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m   1125�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint:disable=broad-except�[39;00m

E           �[1;32m   1126�[0m   �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(e, �[38;5;124m"�[39m�[38;5;124mag_error_metadata�[39m�[38;5;124m"�[39m):

E           �[0;32m-> 1127�[0m     �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mag_error_metadata�[38;5;241m.�[39mto_exception(e)

E           �[1;32m   1128�[0m   �[38;5;28;01melse�[39;00m:

E           �[1;32m   1129�[0m     �[38;5;28;01mraise�[39;00m

E

E           �[0;31mResourceExhaustedError�[0m: in user code:

E

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function  *

E                   return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function  **

E                   outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step  **

E                   outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                   self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                   return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 646, in apply_gradients

E                   self._create_all_weights(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 860, in _create_all_weights

E                   self._create_slots(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 124, in _create_slots

E                   self.add_slot(var, 'v')

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 946, in add_slot

E                   weight = tf.Variable(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/initializers/initializers_v2.py", line 152, in call

E                   return tf.zeros(shape, dtype)

E

E               ResourceExhaustedError: OOM when allocating tensor with shape[3078307,88] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0 [Op:Fill]

E

E           ResourceExhaustedError: in user code:

E

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function  *

E                   return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function  **

E                   outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step  **

E                   outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 724, in train_step

E                   self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                   return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 646, in apply_gradients

E                   self._create_all_weights(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 860, in _create_all_weights

E                   self._create_slots(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 124, in _create_slots

E                   self.add_slot(var, 'v')

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 946, in add_slot

E                   weight = tf.Variable(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/initializers/initializers_v2.py", line 152, in call

E                   return tf.zeros(shape, dtype)

E

E               ResourceExhaustedError: OOM when allocating tensor with shape[3078307,88] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0 [Op:Fill]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-22 23:51:00.213925: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-22 23:51:04.454786: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-22 23:51:04.454890: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-22 23:51:04.455770: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-22 23:51:04.455830: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-22 23:51:04.456399: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-22 23:51:04.456450: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-22 23:51:04.457078: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-22 23:51:04.457127: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-22 23:51:16.168276: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 5832704/17069309952

2022-11-22 23:51:16.168326: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      2854623870

MaxInUse:                   3530052209

NumAllocs:                         209

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-22 23:51:16.168352: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-22 23:51:16.168361: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 2

2022-11-22 23:51:16.168368: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 24

2022-11-22 23:51:16.168374: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 3

2022-11-22 23:51:16.168380: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 6

2022-11-22 23:51:16.168386: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 6

2022-11-22 23:51:16.168392: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-22 23:51:16.168398: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 5

2022-11-22 23:51:16.168404: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-22 23:51:16.168410: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 3

2022-11-22 23:51:16.168416: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-22 23:51:16.168422: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-22 23:51:16.168428: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-22 23:51:16.168458: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 2

2022-11-22 23:51:16.168466: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 147200, 1

2022-11-22 23:51:16.168472: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-22 23:51:16.168478: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-22 23:51:16.168484: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-22 23:51:16.168489: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 3

2022-11-22 23:51:16.168495: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 3

2022-11-22 23:51:16.168501: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 2

2022-11-22 23:51:16.168507: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-11-22 23:51:16.168513: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-11-22 23:51:16.168519: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-22 23:51:16.168525: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 2

2022-11-22 23:51:16.168531: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 2

2022-11-22 23:51:16.168565: W tensorflow/core/framework/op_kernel.cc:1745] OP_REQUIRES failed at constant_op.cc:175 : RESOURCE_EXHAUSTED: OOM when allocating tensor with shape[3078307,88] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file8rjpwwkm.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11583   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 872 passed, 13 skipped, 1460 warnings in 1836.14s (0:30:36) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins12352358108783039628.sh

@rnyak
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rnyak commented Nov 23, 2022

rerun tests

@nvidia-merlin-bot
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Click to view CI Results
GitHub pull request #849 of commit dff99ff9ca6f3b40551434919e9508967284927f, no merge conflicts.
Running as SYSTEM
Setting status of dff99ff9ca6f3b40551434919e9508967284927f to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1938/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse dff99ff9ca6f3b40551434919e9508967284927f^{commit} # timeout=10
Checking out Revision dff99ff9ca6f3b40551434919e9508967284927f (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f dff99ff9ca6f3b40551434919e9508967284927f # timeout=10
Commit message: "fix typo"
 > git rev-list --no-walk 66261ae483da683ee9eb69c7dbe646c1bcf52be5 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins16125901191100661011.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+78.gdff99ff9.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.15,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.15,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+78.gdff99ff9,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='237082515'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-xkrtj7g2
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-xkrtj7g2
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
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Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (3.19.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
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Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.0)
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Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
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Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
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Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+12.g025f10d) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (2.8.2)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=5a92eb1b36435725c91ddba3e8138a551e411fd40067fc7ff63ffd76367ee86d
  Stored in directory: /tmp/pip-ephem-wheel-cache-2d64btk4/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-aze2g_j4
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-aze2g_j4
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit fc7f0b2620ae311db13ee8180cbf7226ef09d6de
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+8.gfc7f0b26) (1.8.1)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+8.gfc7f0b26) (0.9.0+12.g025f10d)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.5 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2022.5.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (7.0.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (3.19.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.3.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (0.55.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (4.64.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.10.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2022.3.0)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+8.gfc7f0b26) (1.20.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (0.4.3)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2.2.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.7.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (3.1.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2.4.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (8.1.3)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (5.8.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (6.2)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2.8.2)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+8.gfc7f0b26) (6.0.1)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+8.gfc7f0b26-cp38-cp38-linux_x86_64.whl size=257586 sha256=b83a5e914d2497eab16c73617dc11b7b1d5bfe563407837fed6c071c0b7ce16a
  Stored in directory: /tmp/pip-ephem-wheel-cache-83ocvr_r/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=4e235a05aedd97f9823ca0d2ee90ef05fd4999635f3953d388bffb5120f8ab92
  Stored in directory: /tmp/pip-ephem-wheel-cache-83ocvr_r/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+8.gfc7f0b26
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

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tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

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tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

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tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filekbfrdet3.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11583   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 873 passed, 13 skipped, 1460 warnings in 1830.49s (0:30:30) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins3143713641531579790.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 49ab368bb7a926f60bddf68427827f41bb4e7ffe, no merge conflicts.
Running as SYSTEM
Setting status of 49ab368bb7a926f60bddf68427827f41bb4e7ffe to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1943/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 49ab368bb7a926f60bddf68427827f41bb4e7ffe^{commit} # timeout=10
Checking out Revision 49ab368bb7a926f60bddf68427827f41bb4e7ffe (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 49ab368bb7a926f60bddf68427827f41bb4e7ffe # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk d3c86fd85479c549cd61e3d23a37dbaa2cb47597 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins11207080786361180622.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+80.g49ab368b.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.15,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.15,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+80.g49ab368b,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='841901509'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-cj8kj0g5
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-cj8kj0g5
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 025f10da5f96c9ae470ee31133801da05fabfbf9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (1.3.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.2.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (0.55.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (7.0.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (21.3)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+12.g025f10d) (2022.5.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+12.g025f10d) (1.10.0)
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Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (0.4.3)
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Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.2.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (1.0.4)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (8.1.3)
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Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (3.1.2)
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Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (6.2)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+12.g025f10d) (65.5.1)
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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.52.0)
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+12.g025f10d) (1.15.0)
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Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+12.g025f10d) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+12.g025f10d) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+12.g025f10d-py3-none-any.whl size=118882 sha256=6e7fcc9f38165ca99674fb5249414fb6eca355f6be5cc7f23640d03a35140b47
  Stored in directory: /tmp/pip-ephem-wheel-cache-37p5gr90/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+12.g025f10d
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-iuhmldhl
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-iuhmldhl
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ceef1cae713c283070496ec3483d13f0be5d258b
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+9.gceef1cae) (1.8.1)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.3.tar.gz (48 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 48.3/48.3 kB 1.8 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+9.gceef1cae) (0.9.0+12.g025f10d)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.3.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.2.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (0.55.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (7.0.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (21.3)
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Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.10.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (3.19.5)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+9.gceef1cae) (1.20.3)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2.2.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.0.4)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (8.1.3)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (5.8.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (3.1.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.7.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+9.gceef1cae) (6.0.1)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+9.gceef1cae-cp38-cp38-linux_x86_64.whl size=257587 sha256=045f598d53eef1e29737083c606eaeb16152184bdef048e0fd82b1a7a31e1868
  Stored in directory: /tmp/pip-ephem-wheel-cache-10zw8w3n/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.3-py3-none-any.whl size=37647 sha256=d05feafce0c6dc4746ddad8a2d4f2db98e159ed2371182dca27833e8e0dcf1d3
  Stored in directory: /tmp/pip-ephem-wheel-cache-10zw8w3n/wheels/1c/a3/4a/0feebb30e0c8cb7ba7046544390b43c7017a2195232f5305a1
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.3 nvtabular-1.6.0+9.gceef1cae
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________


tb = <testbook.client.TestbookNotebookClient object at 0x7f9d31c55df0>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f9d31c55df0>

cell = {'cell_type': 'code', 'execution_count': 40, 'id': '7dfa4858-d87c-43db-a6fa-c02a55e83941', 'metadata': {'execution': {...25]']}], 'source': 'history = model_bi_lstm.fit(\n    loader,\n    validation_data=val_loader,\n    epochs=EPOCHS,\n)'}

cell_index = 83

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '06da88...e, 'engine': '06da88c9-c050-444d-8ed6-349642113d50', 'started': '2022-11-23T16:33:58.081567Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           history = model_bi_lstm.fit(

E               loader,

E               validation_data=val_loader,

E               epochs=EPOCHS,

E           )

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [40], line 1�[0m

E           �[0;32m----> 1�[0m history �[38;5;241m=�[39m �[43mmodel_bi_lstm�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m

E           �[1;32m      2�[0m �[43m    �[49m�[43mloader�[49m�[43m,�[49m

E           �[1;32m      3�[0m �[43m    �[49m�[43mvalidation_data�[49m�[38;5;241;43m=�[39;49m�[43mval_loader�[49m�[43m,�[49m

E           �[1;32m      4�[0m �[43m    �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[43mEPOCHS�[49m�[43m,�[49m

E           �[1;32m      5�[0m �[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

E           �[0;32m---> 54�[0m   tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,

E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

E           �[1;32m     56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:

E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'cond/TopKV2' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_20880/3477623819.py", line 1, in 

E                 history = model_bi_lstm.fit(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 726, in train_step

E                 metrics = self.train_compute_metrics(outputs, self.compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 788, in train_compute_metrics

E                 if self._should_compute_train_metrics_for_batch:

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 789, in train_compute_metrics

E                 return self.compute_metrics(outputs, compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 829, in compute_metrics

E                 compiled_metrics.update_state(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/compile_utils.py", line 501, in update_state

E                 metric_obj.update_state(y_t, y_p, sample_weight=mask)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/metrics_utils.py", line 70, in decorated

E                 update_op = update_state_fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/metrics/base_metric.py", line 140, in update_state_fn

E                 return ag_update_state(*args, **kwargs)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/metrics/topk.py", line 431, in update_state

E                 y_pred, y_true, label_relevant_counts_from_targets = extract_topk(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py", line 186, in extract_topk

E                 topk_predictions, topk_indices = tf.math.top_k(predictions, k)

E           Node: 'cond/TopKV2'

E           Detected at node 'cond/TopKV2' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_20880/3477623819.py", line 1, in 

E                 history = model_bi_lstm.fit(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 726, in train_step

E                 metrics = self.train_compute_metrics(outputs, self.compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 788, in train_compute_metrics

E                 if self._should_compute_train_metrics_for_batch:

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 789, in train_compute_metrics

E                 return self.compute_metrics(outputs, compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 829, in compute_metrics

E                 compiled_metrics.update_state(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/compile_utils.py", line 501, in update_state

E                 metric_obj.update_state(y_t, y_p, sample_weight=mask)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/metrics_utils.py", line 70, in decorated

E                 update_op = update_state_fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/metrics/base_metric.py", line 140, in update_state_fn

E                 return ag_update_state(*args, **kwargs)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/metrics/topk.py", line 431, in update_state

E                 y_pred, y_true, label_relevant_counts_from_targets = extract_topk(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py", line 186, in extract_topk

E                 topk_predictions, topk_indices = tf.math.top_k(predictions, k)

E           Node: 'cond/TopKV2'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  OOM when allocating tensor with shape[55017727] and type int8 on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

E           	 [[{{node cond/TopKV2}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[gradient_tape/model_1/parallel_block_3/sequential_block_4/bidirectional/backward_lstm/RaggedToTensor/strided_slice/_132]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  OOM when allocating tensor with shape[55017727] and type int8 on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

E           	 [[{{node cond/TopKV2}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_18725]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'cond/TopKV2' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_20880/3477623819.py", line 1, in 

E                 history = model_bi_lstm.fit(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 726, in train_step

E                 metrics = self.train_compute_metrics(outputs, self.compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 788, in train_compute_metrics

E                 if self._should_compute_train_metrics_for_batch:

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 789, in train_compute_metrics

E                 return self.compute_metrics(outputs, compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 829, in compute_metrics

E                 compiled_metrics.update_state(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/compile_utils.py", line 501, in update_state

E                 metric_obj.update_state(y_t, y_p, sample_weight=mask)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/metrics_utils.py", line 70, in decorated

E                 update_op = update_state_fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/metrics/base_metric.py", line 140, in update_state_fn

E                 return ag_update_state(*args, **kwargs)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/metrics/topk.py", line 431, in update_state

E                 y_pred, y_true, label_relevant_counts_from_targets = extract_topk(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py", line 186, in extract_topk

E                 topk_predictions, topk_indices = tf.math.top_k(predictions, k)

E           Node: 'cond/TopKV2'

E           Detected at node 'cond/TopKV2' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_20880/3477623819.py", line 1, in 

E                 history = model_bi_lstm.fit(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 910, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 726, in train_step

E                 metrics = self.train_compute_metrics(outputs, self.compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 788, in train_compute_metrics

E                 if self._should_compute_train_metrics_for_batch:

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 789, in train_compute_metrics

E                 return self.compute_metrics(outputs, compiled_metrics)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 829, in compute_metrics

E                 compiled_metrics.update_state(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/compile_utils.py", line 501, in update_state

E                 metric_obj.update_state(y_t, y_p, sample_weight=mask)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/metrics_utils.py", line 70, in decorated

E                 update_op = update_state_fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/metrics/base_metric.py", line 140, in update_state_fn

E                 return ag_update_state(*args, **kwargs)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/metrics/topk.py", line 431, in update_state

E                 y_pred, y_true, label_relevant_counts_from_targets = extract_topk(

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py", line 186, in extract_topk

E                 topk_predictions, topk_indices = tf.math.top_k(predictions, k)

E           Node: 'cond/TopKV2'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  OOM when allocating tensor with shape[55017727] and type int8 on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

E           	 [[{{node cond/TopKV2}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[gradient_tape/model_1/parallel_block_3/sequential_block_4/bidirectional/backward_lstm/RaggedToTensor/strided_slice/_132]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  OOM when allocating tensor with shape[55017727] and type int8 on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

E           	 [[{{node cond/TopKV2}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_18725]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-23 16:33:31.956519: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-23 16:33:35.462571: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-23 16:33:35.462682: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-23 16:33:35.463582: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-23 16:33:35.463640: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-23 16:33:35.464221: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-23 16:33:35.464273: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-23 16:33:35.464859: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-23 16:33:35.464911: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-23 16:33:58.534161: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8500

2022-11-23 16:34:08.076764: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 55017727 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 29949952/17069309952

2022-11-23 16:34:08.076818: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                       295098860

MaxInUse:                    325822651

NumAllocs:                       10166

MaxAllocSize:                 55017727

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-23 16:34:08.076844: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-23 16:34:08.076853: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 8

2022-11-23 16:34:08.076860: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 97

2022-11-23 16:34:08.076866: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 18

2022-11-23 16:34:08.076872: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 1

2022-11-23 16:34:08.076878: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 400, 6

2022-11-23 16:34:08.076885: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 416, 1

2022-11-23 16:34:08.076891: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 7

2022-11-23 16:34:08.076897: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1024, 14

2022-11-23 16:34:08.076903: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-23 16:34:08.076909: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1088, 1

2022-11-23 16:34:08.076915: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1280, 6

2022-11-23 16:34:08.076946: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3328, 6

2022-11-23 16:34:08.076954: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4096, 2

2022-11-23 16:34:08.076960: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7748, 2

2022-11-23 16:34:08.076966: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8192, 2

2022-11-23 16:34:08.076972: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 12252, 1

2022-11-23 16:34:08.076978: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15152, 3

2022-11-23 16:34:08.076984: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15160, 3

2022-11-23 16:34:08.076990: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15336, 3

2022-11-23 16:34:08.076996: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15344, 3

2022-11-23 16:34:08.077003: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15424, 3

2022-11-23 16:34:08.077009: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15488, 3

2022-11-23 16:34:08.077015: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15496, 4

2022-11-23 16:34:08.077021: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15536, 3

2022-11-23 16:34:08.077027: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15568, 3

2022-11-23 16:34:08.077033: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15664, 3

2022-11-23 16:34:08.077039: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15704, 3

2022-11-23 16:34:08.077045: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15808, 3

2022-11-23 16:34:08.077051: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15856, 3

2022-11-23 16:34:08.077057: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 26864, 6

2022-11-23 16:34:08.077063: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32640, 1

2022-11-23 16:34:08.077069: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 6

2022-11-23 16:34:08.077076: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 6

2022-11-23 16:34:08.077082: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 196608, 4

2022-11-23 16:34:08.077088: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 262144, 11

2022-11-23 16:34:08.077094: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 278528, 3

2022-11-23 16:34:08.077100: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 294912, 10

2022-11-23 16:34:08.077106: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 362496, 2

2022-11-23 16:34:08.077112: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 409600, 3

2022-11-23 16:34:08.077118: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 786432, 2

2022-11-23 16:34:08.077124: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1572864, 1

2022-11-23 16:34:08.077130: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 2479376, 2

2022-11-23 16:34:08.077136: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3538944, 4

2022-11-23 16:34:08.077142: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 6877184, 10

2022-11-23 16:34:08.077149: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 27508736, 5

2022-11-23 16:34:08.077155: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 55017472, 1

2022-11-23 16:34:08.077185: W tensorflow/core/framework/op_kernel.cc:1745] OP_REQUIRES failed at topk_op.cc:102 : RESOURCE_EXHAUSTED: OOM when allocating tensor with shape[55017727] and type int8 on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

_______________ test_usecase_incremental_training_layer_freezing _______________


tb = <testbook.client.TestbookNotebookClient object at 0x7f9d31be3820>


@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_incremental_training_layer_freezing(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )





  tb.execute()





tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py:22:




../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)




self = <testbook.client.TestbookNotebookClient object at 0x7f9d31be3820>

cell = {'cell_type': 'code', 'execution_count': 8, 'id': '791e06ec-c0cb-4c0f-9e41-7e5c8fa1dc4e', 'metadata': {'execution': {'...: 'model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))\nmodel.fit(day_1, batch_size=1024, epochs=1)'}

cell_index = 13

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '23f376...e, 'engine': '23f3769a-77e2-438d-947b-7e56e1e9f754', 'started': '2022-11-23T16:34:27.746427Z', 'status': 'error'}, ...}


async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:





      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)





E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))

E           model.fit(day_1, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [8], line 2�[0m

E           �[1;32m      1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))

E           �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1142�[0m, in �[0;36mModel._maybe_build�[0;34m(self, inputs)�[0m

E           �[1;32m   1140�[0m             child�[38;5;241m.�[39m_feature_shapes �[38;5;241m=�[39m feature_shapes

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:1160�[0m, in �[0;36mModel.build�[0;34m(self, input_shape)�[0m

E           �[1;32m   1158�[0m �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mblocks:

E           �[1;32m   1159�[0m     �[38;5;28;01mtry�[39;00m:

E           �[0;32m-> 1160�[0m         layer�[38;5;241m.�[39mbuild(input_shape)

E           �[1;32m   1161�[0m     �[38;5;28;01mexcept�[39;00m �[38;5;167;01mTypeError�[39;00m:

E           �[1;32m   1162�[0m         t, v, tb �[38;5;241m=�[39m sys�[38;5;241m.�[39mexc_info()

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:595�[0m, in �[0;36mParallelBlock.build�[0;34m(self, input_shape)�[0m

E           �[1;32m    591�[0m �[38;5;28;01mfor�[39;00m name, layer �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mparallel_dict�[38;5;241m.�[39mitems():

E           �[1;32m    592�[0m     layer_input_shape �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_maybe_filter_layer_inputs_using_schema(

E           �[1;32m    593�[0m         name, layer, input_shape

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E           �[1;32m    596�[0m     layer_out_shape �[38;5;241m=�[39m layer�[38;5;241m.�[39mcompute_output_shape(layer_input_shape)

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E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:110�[0m, in �[0;36mModelBlock.build�[0;34m(self, input_shapes)�[0m

E           �[1;32m    109�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mbuild�[39m(�[38;5;28mself�[39m, input_shapes):

E           �[0;32m--> 110�[0m     �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mblock�[49m�[38;5;241;43m.�[39;49m�[43mbuild�[49m�[43m(�[49m�[43minput_shapes�[49m�[43m)�[49m

E           �[1;32m    112�[0m     �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m�[38;5;241m.�[39mbuild, �[38;5;124m"�[39m�[38;5;124m_is_default�[39m�[38;5;124m"�[39m):

E           �[1;32m    113�[0m         �[38;5;28mself�[39m�[38;5;241m.�[39m_build_input_shape �[38;5;241m=�[39m input_shapes

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:129�[0m, in �[0;36mSequentialBlock.build�[0;34m(self, input_shape)�[0m

E           �[1;32m    121�[0m �[38;5;124;03m"""Builds the sequential block�[39;00m

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E           �[1;32m    126�[0m �[38;5;124;03m    The input shape, by default None�[39;00m

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E           �[1;32m    128�[0m �[38;5;28mself�[39m�[38;5;241m.�[39m_maybe_propagate_context(input_shape)

E           �[0;32m--> 129�[0m �[43mbuild_sequentially�[49m�[43m(�[49m�[38;5;28;43mself�[39;49m�[43m,�[49m�[43m �[49m�[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mlayers�[49m�[43m,�[49m�[43m �[49m�[43minput_shape�[49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:846�[0m, in �[0;36mbuild_sequentially�[0;34m(self, layers, input_shape)�[0m

E           �[1;32m    844�[0m �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m layers:

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E           �[1;32m    847�[0m     �[38;5;28;01mexcept�[39;00m �[38;5;167;01mTypeError�[39;00m:

E           �[1;32m    848�[0m         t, v, tb �[38;5;241m=�[39m sys�[38;5;241m.�[39mexc_info()

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:595�[0m, in �[0;36mParallelBlock.build�[0;34m(self, input_shape)�[0m

E           �[1;32m    591�[0m �[38;5;28;01mfor�[39;00m name, layer �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mparallel_dict�[38;5;241m.�[39mitems():

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E           �[1;32m    593�[0m         name, layer, input_shape

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E           �[1;32m    596�[0m     layer_out_shape �[38;5;241m=�[39m layer�[38;5;241m.�[39mcompute_output_shape(layer_input_shape)

E           �[1;32m    597�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mautomatic_pruning �[38;5;129;01mand�[39;00m layer_out_shape �[38;5;241m==�[39m {}:

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/core/combinators.py:595�[0m, in �[0;36mParallelBlock.build�[0;34m(self, input_shape)�[0m

E           �[1;32m    591�[0m �[38;5;28;01mfor�[39;00m name, layer �[38;5;129;01min�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mparallel_dict�[38;5;241m.�[39mitems():

E           �[1;32m    592�[0m     layer_input_shape �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39m_maybe_filter_layer_inputs_using_schema(

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E           �[1;32m    596�[0m     layer_out_shape �[38;5;241m=�[39m layer�[38;5;241m.�[39mcompute_output_shape(layer_input_shape)

E           �[1;32m    597�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mautomatic_pruning �[38;5;129;01mand�[39;00m layer_out_shape �[38;5;241m==�[39m {}:

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:364�[0m, in �[0;36mEmbeddingTable.build�[0;34m(self, input_shapes)�[0m

E           �[1;32m    362�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mbuild�[39m(�[38;5;28mself�[39m, input_shapes):

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E           �[1;32m    365�[0m     �[38;5;28;01mreturn�[39;00m �[38;5;28msuper�[39m(EmbeddingTable, �[38;5;28mself�[39m)�[38;5;241m.�[39mbuild(input_shapes)

E

E           �[0;31mResourceExhaustedError�[0m: failed to allocate memory [Op:Mul]

E           ResourceExhaustedError: failed to allocate memory [Op:Mul]


../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-23 16:34:20.645206: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-23 16:34:24.880703: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-23 16:34:24.880809: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-23 16:34:24.881687: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-23 16:34:24.881741: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-23 16:34:24.882368: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-23 16:34:24.882419: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-23 16:34:24.883048: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-23 16:34:24.883098: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13849 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-23 16:34:28.272826: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 6881280/17069309952

2022-11-23 16:34:28.272878: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      1362837605

MaxInUse:                   1362837605

NumAllocs:                         100

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0


2022-11-23 16:34:28.272891: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-23 16:34:28.272900: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 1

2022-11-23 16:34:28.272906: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 16

2022-11-23 16:34:28.272912: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 2

2022-11-23 16:34:28.272917: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 2

2022-11-23 16:34:28.272923: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 2

2022-11-23 16:34:28.272929: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 1

2022-11-23 16:34:28.272934: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 1

2022-11-23 16:34:28.272940: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 1

2022-11-23 16:34:28.272946: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-23 16:34:28.272951: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 1

2022-11-23 16:34:28.272957: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 60720, 1

2022-11-23 16:34:28.272963: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 1

2022-11-23 16:34:28.272992: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 1

2022-11-23 16:34:28.272999: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 1

2022-11-23 16:34:28.273005: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 1

2022-11-23 16:34:28.273011: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 1

2022-11-23 16:34:28.273016: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 1

2022-11-23 16:34:28.273022: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 1

2022-11-23 16:34:28.273028: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 1

2022-11-23 16:34:28.273033: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 1

2022-11-23 16:34:28.273039: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 1

2022-11-23 16:34:28.273071: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file2lg69bc4.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     52    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         64     20    69%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    102    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11587   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 2 failed, 871 passed, 13 skipped, 1460 warnings in 1863.66s (0:31:03) =====

/usr/local/lib/python3.8/dist-packages/coverage/data.py:130: CoverageWarning: Data file '/var/jenkins_home/workspace/merlin_models/models/.coverage.10.20.17.231.19463.804813' doesn't seem to be a coverage data file: cannot unpack non-iterable NoneType object

data._warn(str(exc))

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins3098769999297859636.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit edb7f9ca77ed37bcc236b2ccf41793daa9a9de46, no merge conflicts.
Running as SYSTEM
Setting status of edb7f9ca77ed37bcc236b2ccf41793daa9a9de46 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1947/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse edb7f9ca77ed37bcc236b2ccf41793daa9a9de46^{commit} # timeout=10
Checking out Revision edb7f9ca77ed37bcc236b2ccf41793daa9a9de46 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f edb7f9ca77ed37bcc236b2ccf41793daa9a9de46 # timeout=10
Commit message: "Merge branch 'main' into session_based"
 > git rev-list --no-walk 89869a3ee4aa2ebd1e5781194aaff1f001aaf341 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins15922620596059607354.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+82.gedb7f9ca.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.15,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.15,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==6.0.0,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+82.gedb7f9ca,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.10.0,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==3.0.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3283035622'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-ux_cyed2
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-ux_cyed2
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 78f1f0b0952fd14b76913b0dd258565c06694abe
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (0.55.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.10.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (3.19.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (4.64.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (0.4.3)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+13.g78f1f0b-py3-none-any.whl size=118889 sha256=caa6867d4333fb5d03acb5dd59454c8aa209c15b2940a7712a1543176f915f65
  Stored in directory: /tmp/pip-ephem-wheel-cache-vtukby5p/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+13.g78f1f0b
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-9np92ym3
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-9np92ym3
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ff186c6fac1bca957d4edd76e8e81c77ca6a649e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.3.tar.gz (48 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 48.3/48.3 kB 55.7 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+10.gff186c6f) (0.9.0+13.g78f1f0b)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+10.gff186c6f) (1.8.1)
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Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (0.55.1)
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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (21.3)
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Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (5.4.1)
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Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (5.8.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (6.2)
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Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (3.1.2)
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Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (2.4.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (0.38.1)
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Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (4.0.0)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+10.gff186c6f-cp38-cp38-linux_x86_64.whl size=257603 sha256=7683522da43d107a31ce6fdb99c35b7a72bbc06c26d87766df44ddd9eda99fc4
  Stored in directory: /tmp/pip-ephem-wheel-cache-uyknugeu/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.3-py3-none-any.whl size=37647 sha256=3fe0dd0aa1653e7df07cd91e3b2722257c90e8f16f28665a184c805309969e30
  Stored in directory: /tmp/pip-ephem-wheel-cache-uyknugeu/wheels/1c/a3/4a/0feebb30e0c8cb7ba7046544390b43c7017a2195232f5305a1
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.3 nvtabular-1.6.0+10.gff186c6f
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

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tests/unit/tf/transforms/test_features.py s............................. [ 77%]

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tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filedvk4xmh5.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         64     20    69%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11587   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 873 passed, 13 skipped, 1460 warnings in 1812.97s (0:30:12) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins148400977272062921.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #849 of commit 386675cc0354221b930395ec948d24bfc00b9627, no merge conflicts.
Running as SYSTEM
Setting status of 386675cc0354221b930395ec948d24bfc00b9627 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1948/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse 386675cc0354221b930395ec948d24bfc00b9627^{commit} # timeout=10
Checking out Revision 386675cc0354221b930395ec948d24bfc00b9627 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 386675cc0354221b930395ec948d24bfc00b9627 # timeout=10
Commit message: "modify unit test"
 > git rev-list --no-walk edb7f9ca77ed37bcc236b2ccf41793daa9a9de46 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins6060359792095089393.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+83.g386675cc.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.15,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.15,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==6.0.0,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+83.g386675cc,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.10.0,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==3.0.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2438111435'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-1mywe4s5
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-1mywe4s5
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 78f1f0b0952fd14b76913b0dd258565c06694abe
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (4.64.1)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.5.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (3.19.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.10.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.3.5)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (0.12.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (6.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (3.1.2)
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Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+13.g78f1f0b-py3-none-any.whl size=118889 sha256=425d676f7e96344a4fed8a55e43b5ab13f662818f1768bba35a91cd1cea7b644
  Stored in directory: /tmp/pip-ephem-wheel-cache-pm5ozvlr/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+13.g78f1f0b
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-qka61r03
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-qka61r03
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ff186c6fac1bca957d4edd76e8e81c77ca6a649e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.3.tar.gz (48 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 48.3/48.3 kB 1.7 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+10.gff186c6f) (1.8.1)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (65.5.1)
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Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (0.2.1)
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Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (6.0.1)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+10.gff186c6f-cp38-cp38-linux_x86_64.whl size=257603 sha256=145e6067571b43b46417b46401fe9b30085f86b384c68f32a97558c57b15f6ae
  Stored in directory: /tmp/pip-ephem-wheel-cache-qdawu5by/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.3-py3-none-any.whl size=37647 sha256=b27ded66b71c4cb806ac9cbfd28c51d508a6db5d8e86e16bb072a01e370f07a6
  Stored in directory: /tmp/pip-ephem-wheel-cache-qdawu5by/wheels/1c/a3/4a/0feebb30e0c8cb7ba7046544390b43c7017a2195232f5305a1
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.3 nvtabular-1.6.0+10.gff186c6f
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filezi3067um.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         64     20    69%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11587   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 873 passed, 13 skipped, 1460 warnings in 1828.68s (0:30:28) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins3881583830834184228.sh

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GitHub pull request #849 of commit f81fb5eb794ae6fcf58ee258460a9ba30995886a, no merge conflicts.
Running as SYSTEM
Setting status of f81fb5eb794ae6fcf58ee258460a9ba30995886a to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1949/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/849/*:refs/remotes/origin/pr/849/* # timeout=10
 > git rev-parse f81fb5eb794ae6fcf58ee258460a9ba30995886a^{commit} # timeout=10
Checking out Revision f81fb5eb794ae6fcf58ee258460a9ba30995886a (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f f81fb5eb794ae6fcf58ee258460a9ba30995886a # timeout=10
Commit message: "Merge branch 'session_based' of https://github.com/NVIDIA-Merlin/Models into HEAD"
 > git rev-list --no-walk 386675cc0354221b930395ec948d24bfc00b9627 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins1815345078322023215.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+85.gf81fb5eb.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.15,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.15,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==6.0.0,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+85.gf81fb5eb,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.10.0,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==3.0.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='438568485'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-l9paenpo
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-l9paenpo
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 78f1f0b0952fd14b76913b0dd258565c06694abe
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (7.0.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (4.64.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (21.3)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.5.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.10.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.2.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.3.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (3.19.5)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (0.12.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (5.8.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.0.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.7.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+13.g78f1f0b) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+13.g78f1f0b) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+13.g78f1f0b) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+13.g78f1f0b) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+13.g78f1f0b) (2.8.2)
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Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+13.g78f1f0b-py3-none-any.whl size=118889 sha256=b44c416bda0a8148af8290067d44caf3e0b3e374e9fc795eb93f3dcd57d5c0ad
  Stored in directory: /tmp/pip-ephem-wheel-cache-zd4v0kog/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+13.g78f1f0b
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-ce0wocvc
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-ce0wocvc
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ff186c6fac1bca957d4edd76e8e81c77ca6a649e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+10.gff186c6f) (0.9.0+13.g78f1f0b)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.3.tar.gz (48 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 48.3/48.3 kB 1.6 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+10.gff186c6f) (1.8.1)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (65.5.1)
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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.52.0)
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Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (0.2.1)
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Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+10.gff186c6f) (4.0.0)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+10.gff186c6f-cp38-cp38-linux_x86_64.whl size=257603 sha256=c437ee01dae03fdac67666dc49afd7a61a4315349a6e68599136b0c6ef5c2481
  Stored in directory: /tmp/pip-ephem-wheel-cache-h5jp2rtf/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.3-py3-none-any.whl size=37647 sha256=baf459b910a2caf8940031414ee55588b5f63508826308a8b3c07017fda175e8
  Stored in directory: /tmp/pip-ephem-wheel-cache-h5jp2rtf/wheels/1c/a3/4a/0feebb30e0c8cb7ba7046544390b43c7017a2195232f5305a1
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.3 nvtabular-1.6.0+10.gff186c6f
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 886 items

tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 25%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 29%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

.............................................                            [ 62%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 93%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]


=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "


../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,


../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,


tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 89 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(


tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))


tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_fileaao2_a50.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)


tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):


tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(


tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)


tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)


tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))


tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(


tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}


tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")


tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()


tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.


tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)


-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html


---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover


merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         64     20    69%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%


TOTAL                                                                11587   2394    79%


=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 873 passed, 13 skipped, 1460 warnings in 1834.08s (0:30:34) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins10851340946100971131.sh

@rnyak rnyak merged commit 0352a2d into main Nov 24, 2022
@rnyak rnyak deleted the session_based branch November 24, 2022 00:48
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@bschifferer bschifferer bschifferer approved these changes

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