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select by tags #1115

Merged
merged 6 commits into from
Sep 14, 2021
Merged

select by tags #1115

merged 6 commits into from
Sep 14, 2021

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GitHub pull request #1115 of commit bae330897df078f6dff970c95e3920ba3b537f57, no merge conflicts.
Running as SYSTEM
Setting status of bae330897df078f6dff970c95e3920ba3b537f57 to PENDING with url http://10.20.13.93:8080/job/nvtabular_tests/3438/ and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/nvtabular_tests
using credential nvidia-merlin-bot
Cloning the remote Git repository
Cloning repository https://github.com/NVIDIA/NVTabular.git
 > git init /var/jenkins_home/workspace/nvtabular_tests/nvtabular # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > 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/NVTabular.git +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/1115/*:refs/remotes/origin/pr/1115/* # timeout=10
 > git rev-parse bae330897df078f6dff970c95e3920ba3b537f57^{commit} # timeout=10
Checking out Revision bae330897df078f6dff970c95e3920ba3b537f57 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f bae330897df078f6dff970c95e3920ba3b537f57 # timeout=10
Commit message: "selectoor accepts tags"
 > git rev-list --no-walk 0421082f5403fa71c788b0ec83444adcf59e3eba # timeout=10
First time build. Skipping changelog.
[nvtabular_tests] $ /bin/bash /tmp/jenkins7807485497794514821.sh
Installing NVTabular
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: pip in /var/jenkins_home/.local/lib/python3.8/site-packages (21.2.4)
Requirement already satisfied: setuptools in /var/jenkins_home/.local/lib/python3.8/site-packages (58.0.4)
Requirement already satisfied: wheel in /var/jenkins_home/.local/lib/python3.8/site-packages (0.37.0)
Requirement already satisfied: pybind11 in /var/jenkins_home/.local/lib/python3.8/site-packages (2.7.1)
running develop
running egg_info
creating nvtabular.egg-info
writing nvtabular.egg-info/PKG-INFO
writing dependency_links to nvtabular.egg-info/dependency_links.txt
writing requirements to nvtabular.egg-info/requires.txt
writing top-level names to nvtabular.egg-info/top_level.txt
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*.h' under directory 'cpp'
warning: no files found matching '*.cu' under directory 'cpp'
warning: no files found matching '*.cuh' under directory 'cpp'
adding license file 'LICENSE'
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
running build_ext
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.8 -c flagcheck.cpp -o flagcheck.o -std=c++17
building 'nvtabular_cpp' extension
creating build
creating build/temp.linux-x86_64-3.8
creating build/temp.linux-x86_64-3.8/cpp
creating build/temp.linux-x86_64-3.8/cpp/nvtabular
creating build/temp.linux-x86_64-3.8/cpp/nvtabular/inference
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+50.gbae3308 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+50.gbae3308 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+50.gbae3308 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/categorify.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+50.gbae3308 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/fill.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -std=c++17 -fvisibility=hidden -g0
creating build/lib.linux-x86_64-3.8
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -o build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so
copying build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so -> 
Generating nvtabular/inference/triton/model_config_pb2.py from nvtabular/inference/triton/model_config.proto
Creating /var/jenkins_home/.local/lib/python3.8/site-packages/nvtabular.egg-link (link to .)
nvtabular 0.6.0+50.gbae3308 is already the active version in easy-install.pth

Installed /var/jenkins_home/workspace/nvtabular_tests/nvtabular
Processing dependencies for nvtabular==0.6.0+50.gbae3308
Searching for protobuf==3.17.3
Best match: protobuf 3.17.3
Adding protobuf 3.17.3 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for tensorflow-metadata==1.2.0
Best match: tensorflow-metadata 1.2.0
Processing tensorflow_metadata-1.2.0-py3.8.egg
tensorflow-metadata 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow_metadata-1.2.0-py3.8.egg
Searching for pyarrow==4.0.1
Best match: pyarrow 4.0.1
Adding pyarrow 4.0.1 to easy-install.pth file
Installing plasma_store script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for tqdm==4.61.2
Best match: tqdm 4.61.2
Processing tqdm-4.61.2-py3.8.egg
tqdm 4.61.2 is already the active version in easy-install.pth
Installing tqdm script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tqdm-4.61.2-py3.8.egg
Searching for numba==0.54.0
Best match: numba 0.54.0
Processing numba-0.54.0-py3.8-linux-x86_64.egg
numba 0.54.0 is already the active version in easy-install.pth
Installing pycc script to /var/jenkins_home/.local/bin
Installing numba script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg
Searching for pandas==1.2.5
Best match: pandas 1.2.5
Processing pandas-1.2.5-py3.8-linux-x86_64.egg
pandas 1.2.5 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg
Searching for distributed==2021.4.1
Best match: distributed 2021.4.1
Processing distributed-2021.4.1-py3.8.egg
distributed 2021.4.1 is already the active version in easy-install.pth
Installing dask-ssh script to /var/jenkins_home/.local/bin
Installing dask-scheduler script to /var/jenkins_home/.local/bin
Installing dask-worker script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/distributed-2021.4.1-py3.8.egg
Searching for dask==2021.4.1
Best match: dask 2021.4.1
Processing dask-2021.4.1-py3.8.egg
dask 2021.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg
Searching for PyYAML==5.4.1
Best match: PyYAML 5.4.1
Processing PyYAML-5.4.1-py3.8-linux-x86_64.egg
PyYAML 5.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg
Searching for six==1.15.0
Best match: six 1.15.0
Adding six 1.15.0 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for googleapis-common-protos==1.53.0
Best match: googleapis-common-protos 1.53.0
Processing googleapis_common_protos-1.53.0-py3.8.egg
googleapis-common-protos 1.53.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/googleapis_common_protos-1.53.0-py3.8.egg
Searching for absl-py==0.12.0
Best match: absl-py 0.12.0
Processing absl_py-0.12.0-py3.8.egg
absl-py 0.12.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/absl_py-0.12.0-py3.8.egg
Searching for numpy==1.20.2
Best match: numpy 1.20.2
Adding numpy 1.20.2 to easy-install.pth file
Installing f2py script to /var/jenkins_home/.local/bin
Installing f2py3 script to /var/jenkins_home/.local/bin
Installing f2py3.8 script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for setuptools==58.0.4
Best match: setuptools 58.0.4
Adding setuptools 58.0.4 to easy-install.pth file

Using /var/jenkins_home/.local/lib/python3.8/site-packages
Searching for llvmlite==0.37.0
Best match: llvmlite 0.37.0
Processing llvmlite-0.37.0-py3.8-linux-x86_64.egg
llvmlite 0.37.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/llvmlite-0.37.0-py3.8-linux-x86_64.egg
Searching for pytz==2021.1
Best match: pytz 2021.1
Adding pytz 2021.1 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for python-dateutil==2.8.2
Best match: python-dateutil 2.8.2
Adding python-dateutil 2.8.2 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for zict==2.0.0
Best match: zict 2.0.0
Processing zict-2.0.0-py3.8.egg
zict 2.0.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg
Searching for tornado==6.1
Best match: tornado 6.1
Processing tornado-6.1-py3.8-linux-x86_64.egg
tornado 6.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tornado-6.1-py3.8-linux-x86_64.egg
Searching for toolz==0.11.1
Best match: toolz 0.11.1
Processing toolz-0.11.1-py3.8.egg
toolz 0.11.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/toolz-0.11.1-py3.8.egg
Searching for tblib==1.7.0
Best match: tblib 1.7.0
Processing tblib-1.7.0-py3.8.egg
tblib 1.7.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg
Searching for sortedcontainers==2.4.0
Best match: sortedcontainers 2.4.0
Processing sortedcontainers-2.4.0-py3.8.egg
sortedcontainers 2.4.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg
Searching for psutil==5.8.0
Best match: psutil 5.8.0
Processing psutil-5.8.0-py3.8-linux-x86_64.egg
psutil 5.8.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg
Searching for msgpack==1.0.2
Best match: msgpack 1.0.2
Processing msgpack-1.0.2-py3.8-linux-x86_64.egg
msgpack 1.0.2 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/msgpack-1.0.2-py3.8-linux-x86_64.egg
Searching for cloudpickle==1.6.0
Best match: cloudpickle 1.6.0
Processing cloudpickle-1.6.0-py3.8.egg
cloudpickle 1.6.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/cloudpickle-1.6.0-py3.8.egg
Searching for click==8.0.1
Best match: click 8.0.1
Processing click-8.0.1-py3.8.egg
click 8.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/click-8.0.1-py3.8.egg
Searching for partd==1.2.0
Best match: partd 1.2.0
Processing partd-1.2.0-py3.8.egg
partd 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg
Searching for fsspec==2021.8.1
Best match: fsspec 2021.8.1
Processing fsspec-2021.8.1-py3.8.egg
fsspec 2021.8.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/fsspec-2021.8.1-py3.8.egg
Searching for HeapDict==1.0.1
Best match: HeapDict 1.0.1
Processing HeapDict-1.0.1-py3.8.egg
HeapDict 1.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg
Searching for locket==0.2.1
Best match: locket 0.2.1
Processing locket-0.2.1-py3.8.egg
locket 0.2.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg
Finished processing dependencies for nvtabular==0.6.0+50.gbae3308
Running black --check
All done! ✨ 🍰 ✨
125 files would be left unchanged.
Running flake8
Running isort
Skipped 2 files
Running bandit
Running pylint
************* Module nvtabular.ops.categorify
nvtabular/ops/categorify.py:468:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)
************* Module nvtabular.ops.fill
nvtabular/ops/fill.py:67:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)


Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

Running flake8-nb
Building docs
make: Entering directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
make: Leaving directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/nvtabular_tests/nvtabular, configfile: pyproject.toml
plugins: cov-2.12.1, forked-1.3.0, xdist-2.3.0
collected 1455 items / 1 skipped / 1454 selected

tests/unit/test_dask_nvt.py FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF [ 3%]
FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF....FFFFFFFFFFFF [ 7%]
tests/unit/test_io.py .............................F.F.F.F.F.F.Build timed out (after 60 minutes). Marking the build as failed.
Terminated
Build was aborted
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/NVTabular/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[nvtabular_tests] $ /bin/bash /tmp/jenkins2529784359973355911.sh

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GitHub pull request #1115 of commit 78886b73f5139e2ecb1c1c256aa994ead5f7cfdf, no merge conflicts.
Running as SYSTEM
Setting status of 78886b73f5139e2ecb1c1c256aa994ead5f7cfdf to PENDING with url http://10.20.13.93:8080/job/nvtabular_tests/3440/ and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/nvtabular_tests
using credential nvidia-merlin-bot
Cloning the remote Git repository
Cloning repository https://github.com/NVIDIA/NVTabular.git
 > git init /var/jenkins_home/workspace/nvtabular_tests/nvtabular # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > 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/NVTabular.git +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/1115/*:refs/remotes/origin/pr/1115/* # timeout=10
 > git rev-parse 78886b73f5139e2ecb1c1c256aa994ead5f7cfdf^{commit} # timeout=10
Checking out Revision 78886b73f5139e2ecb1c1c256aa994ead5f7cfdf (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 78886b73f5139e2ecb1c1c256aa994ead5f7cfdf # timeout=10
Commit message: "slect by tag plumbing complete"
 > git rev-list --no-walk 5deb1b582d81a09cebdd9831a31de390c5573be4 # timeout=10
First time build. Skipping changelog.
[nvtabular_tests] $ /bin/bash /tmp/jenkins3757083044892544167.sh
Installing NVTabular
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: pip in /var/jenkins_home/.local/lib/python3.8/site-packages (21.2.4)
Requirement already satisfied: setuptools in /var/jenkins_home/.local/lib/python3.8/site-packages (58.0.4)
Requirement already satisfied: wheel in /var/jenkins_home/.local/lib/python3.8/site-packages (0.37.0)
Requirement already satisfied: pybind11 in /var/jenkins_home/.local/lib/python3.8/site-packages (2.7.1)
running develop
running egg_info
creating nvtabular.egg-info
writing nvtabular.egg-info/PKG-INFO
writing dependency_links to nvtabular.egg-info/dependency_links.txt
writing requirements to nvtabular.egg-info/requires.txt
writing top-level names to nvtabular.egg-info/top_level.txt
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*.h' under directory 'cpp'
warning: no files found matching '*.cu' under directory 'cpp'
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adding license file 'LICENSE'
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
running build_ext
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.8 -c flagcheck.cpp -o flagcheck.o -std=c++17
building 'nvtabular_cpp' extension
creating build
creating build/temp.linux-x86_64-3.8
creating build/temp.linux-x86_64-3.8/cpp
creating build/temp.linux-x86_64-3.8/cpp/nvtabular
creating build/temp.linux-x86_64-3.8/cpp/nvtabular/inference
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+51.g78886b7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+51.g78886b7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+51.g78886b7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/categorify.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+51.g78886b7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/fill.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -std=c++17 -fvisibility=hidden -g0
creating build/lib.linux-x86_64-3.8
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -o build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so
copying build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so -> 
Generating nvtabular/inference/triton/model_config_pb2.py from nvtabular/inference/triton/model_config.proto
Creating /var/jenkins_home/.local/lib/python3.8/site-packages/nvtabular.egg-link (link to .)
nvtabular 0.6.0+51.g78886b7 is already the active version in easy-install.pth

Installed /var/jenkins_home/workspace/nvtabular_tests/nvtabular
Processing dependencies for nvtabular==0.6.0+51.g78886b7
Searching for protobuf==3.17.3
Best match: protobuf 3.17.3
Adding protobuf 3.17.3 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
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Best match: tensorflow-metadata 1.2.0
Processing tensorflow_metadata-1.2.0-py3.8.egg
tensorflow-metadata 1.2.0 is already the active version in easy-install.pth

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Best match: pyarrow 4.0.1
Adding pyarrow 4.0.1 to easy-install.pth file
Installing plasma_store script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
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Best match: tqdm 4.61.2
Processing tqdm-4.61.2-py3.8.egg
tqdm 4.61.2 is already the active version in easy-install.pth
Installing tqdm script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tqdm-4.61.2-py3.8.egg
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Best match: numba 0.54.0
Processing numba-0.54.0-py3.8-linux-x86_64.egg
numba 0.54.0 is already the active version in easy-install.pth
Installing pycc script to /var/jenkins_home/.local/bin
Installing numba script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg
Searching for pandas==1.2.5
Best match: pandas 1.2.5
Processing pandas-1.2.5-py3.8-linux-x86_64.egg
pandas 1.2.5 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg
Searching for distributed==2021.4.1
Best match: distributed 2021.4.1
Processing distributed-2021.4.1-py3.8.egg
distributed 2021.4.1 is already the active version in easy-install.pth
Installing dask-ssh script to /var/jenkins_home/.local/bin
Installing dask-scheduler script to /var/jenkins_home/.local/bin
Installing dask-worker script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/distributed-2021.4.1-py3.8.egg
Searching for dask==2021.4.1
Best match: dask 2021.4.1
Processing dask-2021.4.1-py3.8.egg
dask 2021.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg
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Best match: PyYAML 5.4.1
Processing PyYAML-5.4.1-py3.8-linux-x86_64.egg
PyYAML 5.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg
Searching for six==1.15.0
Best match: six 1.15.0
Adding six 1.15.0 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
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Processing googleapis_common_protos-1.53.0-py3.8.egg
googleapis-common-protos 1.53.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/googleapis_common_protos-1.53.0-py3.8.egg
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Best match: absl-py 0.12.0
Processing absl_py-0.12.0-py3.8.egg
absl-py 0.12.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/absl_py-0.12.0-py3.8.egg
Searching for numpy==1.20.2
Best match: numpy 1.20.2
Adding numpy 1.20.2 to easy-install.pth file
Installing f2py script to /var/jenkins_home/.local/bin
Installing f2py3 script to /var/jenkins_home/.local/bin
Installing f2py3.8 script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for setuptools==58.0.4
Best match: setuptools 58.0.4
Adding setuptools 58.0.4 to easy-install.pth file

Using /var/jenkins_home/.local/lib/python3.8/site-packages
Searching for llvmlite==0.37.0
Best match: llvmlite 0.37.0
Processing llvmlite-0.37.0-py3.8-linux-x86_64.egg
llvmlite 0.37.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/llvmlite-0.37.0-py3.8-linux-x86_64.egg
Searching for pytz==2021.1
Best match: pytz 2021.1
Adding pytz 2021.1 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for python-dateutil==2.8.2
Best match: python-dateutil 2.8.2
Adding python-dateutil 2.8.2 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for zict==2.0.0
Best match: zict 2.0.0
Processing zict-2.0.0-py3.8.egg
zict 2.0.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg
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Best match: tornado 6.1
Processing tornado-6.1-py3.8-linux-x86_64.egg
tornado 6.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tornado-6.1-py3.8-linux-x86_64.egg
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Best match: toolz 0.11.1
Processing toolz-0.11.1-py3.8.egg
toolz 0.11.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/toolz-0.11.1-py3.8.egg
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Best match: tblib 1.7.0
Processing tblib-1.7.0-py3.8.egg
tblib 1.7.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg
Searching for sortedcontainers==2.4.0
Best match: sortedcontainers 2.4.0
Processing sortedcontainers-2.4.0-py3.8.egg
sortedcontainers 2.4.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg
Searching for psutil==5.8.0
Best match: psutil 5.8.0
Processing psutil-5.8.0-py3.8-linux-x86_64.egg
psutil 5.8.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg
Searching for msgpack==1.0.2
Best match: msgpack 1.0.2
Processing msgpack-1.0.2-py3.8-linux-x86_64.egg
msgpack 1.0.2 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/msgpack-1.0.2-py3.8-linux-x86_64.egg
Searching for cloudpickle==1.6.0
Best match: cloudpickle 1.6.0
Processing cloudpickle-1.6.0-py3.8.egg
cloudpickle 1.6.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/cloudpickle-1.6.0-py3.8.egg
Searching for click==8.0.1
Best match: click 8.0.1
Processing click-8.0.1-py3.8.egg
click 8.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/click-8.0.1-py3.8.egg
Searching for partd==1.2.0
Best match: partd 1.2.0
Processing partd-1.2.0-py3.8.egg
partd 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg
Searching for fsspec==2021.8.1
Best match: fsspec 2021.8.1
Processing fsspec-2021.8.1-py3.8.egg
fsspec 2021.8.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/fsspec-2021.8.1-py3.8.egg
Searching for HeapDict==1.0.1
Best match: HeapDict 1.0.1
Processing HeapDict-1.0.1-py3.8.egg
HeapDict 1.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg
Searching for locket==0.2.1
Best match: locket 0.2.1
Processing locket-0.2.1-py3.8.egg
locket 0.2.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg
Finished processing dependencies for nvtabular==0.6.0+51.g78886b7
Running black --check
All done! ✨ 🍰 ✨
125 files would be left unchanged.
Running flake8
Running isort
Skipped 2 files
Running bandit
Running pylint
************* Module nvtabular.ops.categorify
nvtabular/ops/categorify.py:468:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)
************* Module nvtabular.ops.fill
nvtabular/ops/fill.py:67:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)


Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

Running flake8-nb
Building docs
make: Entering directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
make: Leaving directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/nvtabular_tests/nvtabular, configfile: pyproject.toml
plugins: cov-2.12.1, forked-1.3.0, xdist-2.3.0
collected 1461 items / 1 skipped / 1460 selected

tests/unit/test_dask_nvt.py ............................................ [ 3%]
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tests/unit/test_io.py .................................................. [ 11%]
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tests/unit/test_notebooks.py ...... [ 21%]
tests/unit/test_tf4rec.py . [ 21%]
tests/unit/test_tools.py ...................... [ 22%]
tests/unit/test_triton_inference.py .............................. [ 24%]
tests/unit/columns/test_column_schemas.py .............................. [ 26%]
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tests/unit/columns/test_column_selector.py .................... [ 31%]
tests/unit/framework_utils/test_tf_feature_columns.py . [ 31%]
tests/unit/framework_utils/test_tf_layers.py ........................... [ 33%]
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tests/unit/framework_utils/test_torch_layers.py . [ 36%]
tests/unit/loader/test_dataloader_backend.py . [ 37%]
tests/unit/loader/test_tf_dataloader.py ................................ [ 39%]
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tests/unit/loader/test_torch_dataloader.py ............................. [ 44%]
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tests/unit/ops/test_column_similarity.py ........................ [ 49%]
tests/unit/ops/test_ops.py ............................................. [ 52%]
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tests/unit/ops/test_ops_schema.py ...................................... [ 82%]
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tests/unit/workflow/test_cpu_workflow.py ...... [ 92%]
tests/unit/workflow/test_workflow.py ................................... [ 94%]
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tests/unit/workflow/test_workflow_node.py ........... [ 99%]
tests/unit/workflow/test_workflow_ops.py .. [ 99%]
tests/unit/workflow/test_workflow_schemas.py ....... [100%]

=============================== warnings summary ===============================
tests/unit/test_dask_nvt.py: 3 warnings
tests/unit/test_io.py: 24 warnings
tests/unit/test_tf4rec.py: 2 warnings
tests/unit/test_tools.py: 2 warnings
tests/unit/test_triton_inference.py: 5 warnings
tests/unit/loader/test_tf_dataloader.py: 48 warnings
tests/unit/loader/test_torch_dataloader.py: 14 warnings
tests/unit/ops/test_column_similarity.py: 7 warnings
tests/unit/ops/test_ops.py: 74 warnings
tests/unit/workflow/test_workflow.py: 31 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
/var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg/numba/cuda/compiler.py:865: NumbaPerformanceWarning: �[1mGrid size (1) < 2 * SM count (112) will likely result in GPU under utilization due to low occupancy.�[0m
warn(NumbaPerformanceWarning(msg))

tests/unit/test_io.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/init.py:38: DeprecationWarning: ColumnGroup is deprecated, use ColumnSelector instead
warnings.warn("ColumnGroup is deprecated, use ColumnSelector instead", DeprecationWarning)

tests/unit/test_io.py: 24 warnings
tests/unit/loader/test_torch_dataloader.py: 54 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/node.py:47: FutureWarning: The ["a", "b", "c"] >> ops.Operator syntax for creating a ColumnGroup has been deprecated in NVTabular 21.09 and will be removed in a future version.
warnings.warn(

tests/unit/test_io.py: 36 warnings
tests/unit/workflow/test_workflow.py: 44 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/workflow.py:89: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for execution. Please use the client argument to initialize a Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 52 warnings
tests/unit/workflow/test_workflow.py: 35 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dask.py:372: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for this write operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 20 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:477: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler is being used for this shuffle operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/ops/test_column_similarity.py: 12 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/column_similarity.py:109: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[name] = similarities

tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.1]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:118: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[f"{col}_filled"] = df[col].isna()

tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.1]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:119: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[col] = df[col].fillna(self.medians[col])

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
tests/unit/ops/test_ops.py::test_fill_missing[True-False-parquet]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/indexing.py:1637: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self._setitem_single_block(indexer, value, name)

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:54: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[f"{col}_filled"] = df[col].isna()

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:55: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[col] = df[col].fillna(self.fill_val)

tests/unit/ops/test_ops.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:190: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[tmp] = _arange(len(df), like_df=df, dtype="int32")

tests/unit/ops/test_ops.py::test_join_external[True-True-left-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-left-device-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-device-pandas-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:171: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
_ext.drop_duplicates(ignore_index=True, inplace=True)

tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-False]
tests/unit/ops/test_ops.py::test_groupby_op[id-True]
tests/unit/ops/test_ops.py::test_groupby_op[id-False]
/var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/core.py:6610: UserWarning: Insufficient elements for head. 1 elements requested, only 0 elements available. Try passing larger npartitions to head.
warnings.warn(msg.format(n, len(r)))

tests/unit/workflow/test_cpu_workflow.py: 78 warnings
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/frame.py:3191: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self[k1] = value[k2]

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

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Branch BrPart Cover Missing

examples/multi-gpu-movielens/torch_trainer.py 65 0 6 1 99% 32->36
nvtabular/init.py 18 0 0 0 100%
nvtabular/columns/init.py 2 0 0 0 100%
nvtabular/columns/schema.py 203 19 95 23 86% 43->59, 46, 48, 50-53, 55, 65, 80, 96->106, 100, 102, 120->122, 142, 169, 255->258, 265, 277->287, 281, 282->287, 285->287, 317, 324, 333, 336, 341->340
nvtabular/columns/selector.py 74 1 34 0 99% 121
nvtabular/dispatch.py 258 44 126 22 81% 35-38, 43-45, 51-61, 68-69, 100, 119, 130, 136, 141->143, 154, 177-180, 219, 222, 228, 244, 251, 282->287, 285, 288, 291->295, 328, 339-342, 369-372, 402, 406, 447, 471, 473, 480
nvtabular/framework_utils/init.py 0 0 0 0 100%
nvtabular/framework_utils/tensorflow/init.py 1 0 0 0 100%
nvtabular/framework_utils/tensorflow/feature_column_utils.py 134 78 90 15 39% 30, 99, 103, 114-130, 140, 143-158, 162, 166-167, 173-198, 207-217, 220-227, 229->233, 234, 239-279, 282
nvtabular/framework_utils/tensorflow/layers/init.py 4 0 0 0 100%
nvtabular/framework_utils/tensorflow/layers/embedding.py 153 12 85 6 91% 60, 68->49, 122, 179, 231-239, 335->343, 357->360, 363-364, 367
nvtabular/framework_utils/tensorflow/layers/interaction.py 47 25 20 1 43% 49, 74-103, 106-110, 113
nvtabular/framework_utils/tensorflow/layers/outer_product.py 30 24 10 0 15% 37-38, 41-60, 71-84, 87
nvtabular/framework_utils/torch/init.py 0 0 0 0 100%
nvtabular/framework_utils/torch/layers/init.py 2 0 0 0 100%
nvtabular/framework_utils/torch/layers/embeddings.py 32 2 14 2 91% 50, 91
nvtabular/framework_utils/torch/models.py 45 1 28 4 93% 57->61, 87->89, 93->96, 103
nvtabular/framework_utils/torch/utils.py 75 5 30 5 90% 51->53, 64, 71->76, 75, 118-120
nvtabular/inference/init.py 0 0 0 0 100%
nvtabular/inference/triton/init.py 302 131 130 13 58% 82-86, 140-190, 235-279, 310, 336-344, 352-359, 378, 400-416, 457-461, 499-509, 533-555, 559-626, 633->636, 636->632, 672-682, 691, 701, 722, 729, 735->738, 739
nvtabular/inference/triton/benchmarking_tools.py 52 52 10 0 0% 2-103
nvtabular/inference/triton/data_conversions.py 87 3 58 4 95% 32-33, 84
nvtabular/inference/triton/model.py 176 176 98 0 0% 27-332
nvtabular/inference/triton/model_config_pb2.py 299 0 2 0 100%
nvtabular/io/init.py 4 0 0 0 100%
nvtabular/io/avro.py 88 88 30 0 0% 16-189
nvtabular/io/csv.py 57 6 20 5 86% 22-23, 99, 103->107, 108, 110, 124
nvtabular/io/dask.py 183 8 72 11 93% 111, 114, 150, 398, 408, 425->428, 436, 440->442, 442->438, 447, 449
nvtabular/io/dataframe_engine.py 61 5 28 6 88% 19-20, 50, 69, 88->92, 92->97, 94->97, 97->116, 125
nvtabular/io/dataset.py 331 45 154 29 84% 45-46, 247, 249, 262, 271, 289-303, 406->476, 411-414, 419->429, 424-425, 436->434, 450->454, 465, 476->485, 536-537, 538->542, 585, 707, 709, 711, 717, 721-723, 725, 785-786, 813, 820-821, 827, 833, 928-929, 1045-1050, 1056, 1137
nvtabular/io/dataset_engine.py 23 1 0 0 96% 45
nvtabular/io/hugectr.py 45 2 24 2 91% 34, 74->97, 101
nvtabular/io/parquet.py 492 25 156 15 94% 33-34, 88-89, 92-100, 124->126, 213-215, 338-343, 381-386, 502->509, 570->575, 576-577, 697, 701, 705, 711, 743, 760, 764, 771->773, 881->exit, 891->896, 901->911, 916, 938
nvtabular/io/shuffle.py 31 6 16 5 77% 42, 44-45, 49, 59, 63
nvtabular/io/writer.py 175 13 68 5 92% 24-25, 51, 79, 125, 128, 212, 221, 224, 267, 288-290
nvtabular/io/writer_factory.py 18 2 8 2 85% 35, 60
nvtabular/loader/init.py 0 0 0 0 100%
nvtabular/loader/backend.py 327 13 138 10 95% 127, 142-143, 233->235, 245-249, 295-296, 335->339, 410, 414-415, 445, 550, 558
nvtabular/loader/tensorflow.py 155 22 50 7 85% 57, 65-68, 78, 88, 296, 332, 347-349, 378-380, 390-398, 401-404
nvtabular/loader/tf_utils.py 55 10 20 5 80% 29->32, 32->34, 39->41, 43, 50-51, 58-60, 66-70
nvtabular/loader/torch.py 81 13 16 2 78% 25-27, 30-36, 111, 149-150
nvtabular/ops/init.py 21 0 0 0 100%
nvtabular/ops/bucketize.py 37 10 18 3 69% 53-55, 59->exit, 62-65, 84-87, 94
nvtabular/ops/categorify.py 591 66 330 47 86% 232, 234, 249, 253, 261, 269, 271, 298, 317-318, 336, 347->351, 355-362, 443-444, 464-465, 474, 525->521, 547->549, 643, 661, 697, 775-776, 791-795, 796->760, 814, 822, 829->exit, 853, 856->859, 891, 896, 912->916, 923-926, 937, 941, 943, 950, 955-958, 1036, 1038, 1067->1090, 1073->1090, 1091-1096, 1133, 1151->1156, 1155, 1165->1162, 1170->1162, 1177, 1180, 1188-1198
nvtabular/ops/clip.py 18 2 6 3 79% 44, 52->54, 55
nvtabular/ops/column_similarity.py 118 25 38 5 74% 19-20, 78->exit, 108, 134, 198-199, 208-210, 218-234, 251->254, 255, 265
nvtabular/ops/data_stats.py 56 2 22 3 94% 91->93, 95, 97->87, 102
nvtabular/ops/difference_lag.py 31 1 8 1 95% 69->71, 94
nvtabular/ops/dropna.py 8 0 0 0 100%
nvtabular/ops/fill.py 86 15 34 2 78% 63-67, 84-87, 114, 140, 144, 155-158
nvtabular/ops/filter.py 20 1 6 1 92% 49
nvtabular/ops/groupby.py 114 3 68 4 96% 73, 84, 94->96, 106->111, 141
nvtabular/ops/hash_bucket.py 35 3 18 2 87% 72, 102, 108
nvtabular/ops/hashed_cross.py 36 4 15 3 86% 53, 66, 81, 91
nvtabular/ops/internal/init.py 3 0 0 0 100%
nvtabular/ops/internal/concat_columns.py 11 0 0 0 100%
nvtabular/ops/internal/identity.py 6 1 0 0 83% 42
nvtabular/ops/internal/subset_columns.py 13 1 0 0 92% 53
nvtabular/ops/join_external.py 89 7 36 6 90% 20-21, 113, 115, 117, 159, 176->178, 215
nvtabular/ops/join_groupby.py 101 7 36 4 92% 108, 115, 124, 131->130, 215-216, 219-220
nvtabular/ops/lambdaop.py 39 6 18 6 79% 59, 63, 77, 89, 94, 103
nvtabular/ops/list_slice.py 66 24 26 1 58% 21-22, 53-54, 104-118, 126-137
nvtabular/ops/logop.py 13 0 0 0 100%
nvtabular/ops/moments.py 65 0 20 0 100%
nvtabular/ops/normalize.py 81 10 14 1 86% 70, 78-79, 85, 118-119, 141-142, 146, 157
nvtabular/ops/operator.py 59 1 10 1 97% 102
nvtabular/ops/rename.py 36 3 20 3 89% 47, 81-83
nvtabular/ops/stat_operator.py 8 0 0 0 100%
nvtabular/ops/target_encoding.py 153 11 66 4 91% 167->171, 175->184, 232-233, 236-237, 249-255, 346->349, 362
nvtabular/tags.py 16 0 0 0 100%
nvtabular/tools/init.py 0 0 0 0 100%
nvtabular/tools/data_gen.py 236 1 62 1 99% 321
nvtabular/tools/dataset_inspector.py 50 7 18 1 79% 32-39
nvtabular/tools/inspector_script.py 46 46 0 0 0% 17-168
nvtabular/utils.py 102 43 46 8 52% 31-32, 36-37, 50, 61-62, 64-66, 69, 72, 78, 84, 90-126, 145, 149->153
nvtabular/worker.py 82 5 38 7 90% 24-25, 82->99, 91, 92->99, 99->102, 108, 110, 111->113
nvtabular/workflow/init.py 2 0 0 0 100%
nvtabular/workflow/node.py 229 18 110 10 89% 55, 93->98, 146, 248->252, 288, 302, 311, 329-334, 339, 388-389, 400->395, 439-444
nvtabular/workflow/workflow.py 217 16 112 8 92% 28-29, 47, 118, 141, 197, 224-226, 332, 347-348, 366-367, 493, 505

TOTAL 7079 1171 2831 335 81%
Coverage XML written to file coverage.xml

Required test coverage of 70% reached. Total coverage: 81.06%
=========================== short test summary info ============================
SKIPPED [1] ../../../../../usr/local/lib/python3.8/dist-packages/dask_cudf/io/tests/test_s3.py:16: could not import 's3fs': No module named 's3fs'
SKIPPED [8] tests/unit/test_io.py:514: could not import 'uavro': No module named 'uavro'
SKIPPED [1] tests/unit/loader/test_tf_dataloader.py:521: not working correctly in ci environment
========== 1452 passed, 10 skipped, 784 warnings in 913.45s (0:15:13) ==========
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/NVTabular/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[nvtabular_tests] $ /bin/bash /tmp/jenkins6292025853961722092.sh

@karlhigley karlhigley requested a review from benfred September 14, 2021 18:28
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GitHub pull request #1115 of commit 3af62e4edb9e645c8b677f1be66766a3ac336ed6, has merge conflicts.
Running as SYSTEM
!!! PR mergeability status has changed !!!  
PR now has NO merge conflicts
Setting status of 3af62e4edb9e645c8b677f1be66766a3ac336ed6 to PENDING with url http://10.20.13.93:8080/job/nvtabular_tests/3444/ and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/nvtabular_tests
using credential nvidia-merlin-bot
Cloning the remote Git repository
Cloning repository https://github.com/NVIDIA/NVTabular.git
 > git init /var/jenkins_home/workspace/nvtabular_tests/nvtabular # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > 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/NVTabular.git +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/1115/*:refs/remotes/origin/pr/1115/* # timeout=10
 > git rev-parse 3af62e4edb9e645c8b677f1be66766a3ac336ed6^{commit} # timeout=10
Checking out Revision 3af62e4edb9e645c8b677f1be66766a3ac336ed6 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 3af62e4edb9e645c8b677f1be66766a3ac336ed6 # timeout=10
Commit message: "all the way green select by taag"
 > git rev-list --no-walk 91d35722f1095d13d250132cdccb70d6b47cb235 # timeout=10
First time build. Skipping changelog.
[nvtabular_tests] $ /bin/bash /tmp/jenkins1807634015479966661.sh
Installing NVTabular
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: pip in /var/jenkins_home/.local/lib/python3.8/site-packages (21.2.4)
Requirement already satisfied: setuptools in /var/jenkins_home/.local/lib/python3.8/site-packages (58.0.4)
Requirement already satisfied: wheel in /var/jenkins_home/.local/lib/python3.8/site-packages (0.37.0)
Requirement already satisfied: pybind11 in /var/jenkins_home/.local/lib/python3.8/site-packages (2.7.1)
running develop
running egg_info
creating nvtabular.egg-info
writing nvtabular.egg-info/PKG-INFO
writing dependency_links to nvtabular.egg-info/dependency_links.txt
writing requirements to nvtabular.egg-info/requires.txt
writing top-level names to nvtabular.egg-info/top_level.txt
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*.h' under directory 'cpp'
warning: no files found matching '*.cu' under directory 'cpp'
warning: no files found matching '*.cuh' under directory 'cpp'
adding license file 'LICENSE'
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
running build_ext
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.8 -c flagcheck.cpp -o flagcheck.o -std=c++17
building 'nvtabular_cpp' extension
creating build
creating build/temp.linux-x86_64-3.8
creating build/temp.linux-x86_64-3.8/cpp
creating build/temp.linux-x86_64-3.8/cpp/nvtabular
creating build/temp.linux-x86_64-3.8/cpp/nvtabular/inference
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+52.g3af62e4 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+52.g3af62e4 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+52.g3af62e4 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/categorify.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+52.g3af62e4 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/fill.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -std=c++17 -fvisibility=hidden -g0
creating build/lib.linux-x86_64-3.8
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -o build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so
copying build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so -> 
Generating nvtabular/inference/triton/model_config_pb2.py from nvtabular/inference/triton/model_config.proto
Creating /var/jenkins_home/.local/lib/python3.8/site-packages/nvtabular.egg-link (link to .)
nvtabular 0.6.0+52.g3af62e4 is already the active version in easy-install.pth

Installed /var/jenkins_home/workspace/nvtabular_tests/nvtabular
Processing dependencies for nvtabular==0.6.0+52.g3af62e4
Searching for protobuf==3.17.3
Best match: protobuf 3.17.3
Adding protobuf 3.17.3 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for tensorflow-metadata==1.2.0
Best match: tensorflow-metadata 1.2.0
Processing tensorflow_metadata-1.2.0-py3.8.egg
tensorflow-metadata 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow_metadata-1.2.0-py3.8.egg
Searching for pyarrow==4.0.1
Best match: pyarrow 4.0.1
Adding pyarrow 4.0.1 to easy-install.pth file
Installing plasma_store script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for tqdm==4.61.2
Best match: tqdm 4.61.2
Processing tqdm-4.61.2-py3.8.egg
tqdm 4.61.2 is already the active version in easy-install.pth
Installing tqdm script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tqdm-4.61.2-py3.8.egg
Searching for numba==0.54.0
Best match: numba 0.54.0
Processing numba-0.54.0-py3.8-linux-x86_64.egg
numba 0.54.0 is already the active version in easy-install.pth
Installing pycc script to /var/jenkins_home/.local/bin
Installing numba script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg
Searching for pandas==1.2.5
Best match: pandas 1.2.5
Processing pandas-1.2.5-py3.8-linux-x86_64.egg
pandas 1.2.5 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg
Searching for distributed==2021.4.1
Best match: distributed 2021.4.1
Processing distributed-2021.4.1-py3.8.egg
distributed 2021.4.1 is already the active version in easy-install.pth
Installing dask-ssh script to /var/jenkins_home/.local/bin
Installing dask-scheduler script to /var/jenkins_home/.local/bin
Installing dask-worker script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/distributed-2021.4.1-py3.8.egg
Searching for dask==2021.4.1
Best match: dask 2021.4.1
Processing dask-2021.4.1-py3.8.egg
dask 2021.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg
Searching for PyYAML==5.4.1
Best match: PyYAML 5.4.1
Processing PyYAML-5.4.1-py3.8-linux-x86_64.egg
PyYAML 5.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg
Searching for six==1.15.0
Best match: six 1.15.0
Adding six 1.15.0 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for googleapis-common-protos==1.53.0
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Processing googleapis_common_protos-1.53.0-py3.8.egg
googleapis-common-protos 1.53.0 is already the active version in easy-install.pth

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Best match: absl-py 0.12.0
Processing absl_py-0.12.0-py3.8.egg
absl-py 0.12.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/absl_py-0.12.0-py3.8.egg
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Best match: numpy 1.20.2
Adding numpy 1.20.2 to easy-install.pth file
Installing f2py script to /var/jenkins_home/.local/bin
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Installing f2py3.8 script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for setuptools==58.0.4
Best match: setuptools 58.0.4
Adding setuptools 58.0.4 to easy-install.pth file

Using /var/jenkins_home/.local/lib/python3.8/site-packages
Searching for llvmlite==0.37.0
Best match: llvmlite 0.37.0
Processing llvmlite-0.37.0-py3.8-linux-x86_64.egg
llvmlite 0.37.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/llvmlite-0.37.0-py3.8-linux-x86_64.egg
Searching for pytz==2021.1
Best match: pytz 2021.1
Adding pytz 2021.1 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for python-dateutil==2.8.2
Best match: python-dateutil 2.8.2
Adding python-dateutil 2.8.2 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for zict==2.0.0
Best match: zict 2.0.0
Processing zict-2.0.0-py3.8.egg
zict 2.0.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg
Searching for tornado==6.1
Best match: tornado 6.1
Processing tornado-6.1-py3.8-linux-x86_64.egg
tornado 6.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tornado-6.1-py3.8-linux-x86_64.egg
Searching for toolz==0.11.1
Best match: toolz 0.11.1
Processing toolz-0.11.1-py3.8.egg
toolz 0.11.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/toolz-0.11.1-py3.8.egg
Searching for tblib==1.7.0
Best match: tblib 1.7.0
Processing tblib-1.7.0-py3.8.egg
tblib 1.7.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg
Searching for sortedcontainers==2.4.0
Best match: sortedcontainers 2.4.0
Processing sortedcontainers-2.4.0-py3.8.egg
sortedcontainers 2.4.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg
Searching for psutil==5.8.0
Best match: psutil 5.8.0
Processing psutil-5.8.0-py3.8-linux-x86_64.egg
psutil 5.8.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg
Searching for msgpack==1.0.2
Best match: msgpack 1.0.2
Processing msgpack-1.0.2-py3.8-linux-x86_64.egg
msgpack 1.0.2 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/msgpack-1.0.2-py3.8-linux-x86_64.egg
Searching for cloudpickle==1.6.0
Best match: cloudpickle 1.6.0
Processing cloudpickle-1.6.0-py3.8.egg
cloudpickle 1.6.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/cloudpickle-1.6.0-py3.8.egg
Searching for click==8.0.1
Best match: click 8.0.1
Processing click-8.0.1-py3.8.egg
click 8.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/click-8.0.1-py3.8.egg
Searching for partd==1.2.0
Best match: partd 1.2.0
Processing partd-1.2.0-py3.8.egg
partd 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg
Searching for fsspec==2021.8.1
Best match: fsspec 2021.8.1
Processing fsspec-2021.8.1-py3.8.egg
fsspec 2021.8.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/fsspec-2021.8.1-py3.8.egg
Searching for HeapDict==1.0.1
Best match: HeapDict 1.0.1
Processing HeapDict-1.0.1-py3.8.egg
HeapDict 1.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg
Searching for locket==0.2.1
Best match: locket 0.2.1
Processing locket-0.2.1-py3.8.egg
locket 0.2.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg
Finished processing dependencies for nvtabular==0.6.0+52.g3af62e4
Running black --check
All done! ✨ 🍰 ✨
125 files would be left unchanged.
Running flake8
Running isort
Skipped 2 files
Running bandit
Running pylint
************* Module nvtabular.ops.categorify
nvtabular/ops/categorify.py:468:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)
************* Module nvtabular.ops.fill
nvtabular/ops/fill.py:67:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)


Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

Running flake8-nb
Building docs
make: Entering directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
make: Leaving directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/nvtabular_tests/nvtabular, configfile: pyproject.toml
plugins: cov-2.12.1, forked-1.3.0, xdist-2.3.0
collected 1476 items / 1 skipped / 1475 selected

tests/unit/test_dask_nvt.py ............................................ [ 2%]
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tests/unit/test_io.py .................................................. [ 11%]
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tests/unit/test_notebooks.py ...... [ 20%]
tests/unit/test_tf4rec.py . [ 20%]
tests/unit/test_tools.py ...................... [ 22%]
tests/unit/test_triton_inference.py .............................. [ 24%]
tests/unit/columns/test_column_schemas.py .............................. [ 26%]
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tests/unit/columns/test_column_selector.py .................... [ 31%]
tests/unit/framework_utils/test_tf_feature_columns.py . [ 31%]
tests/unit/framework_utils/test_tf_layers.py ........................... [ 33%]
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tests/unit/framework_utils/test_torch_layers.py . [ 36%]
tests/unit/loader/test_dataloader_backend.py . [ 36%]
tests/unit/loader/test_tf_dataloader.py ................................ [ 38%]
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tests/unit/loader/test_torch_dataloader.py ............................. [ 43%]
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tests/unit/ops/test_column_similarity.py ........................ [ 48%]
tests/unit/ops/test_ops.py ............................................. [ 51%]
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tests/unit/ops/test_ops_schema.py ...................................... [ 81%]
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tests/unit/workflow/test_cpu_workflow.py ...... [ 91%]
tests/unit/workflow/test_workflow.py ................................... [ 93%]
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tests/unit/workflow/test_workflow_node.py ........... [ 98%]
tests/unit/workflow/test_workflow_ops.py .. [ 98%]
tests/unit/workflow/test_workflow_schemas.py ...................... [100%]

=================================== FAILURES ===================================
______________ test_dask_preproc_cpu[None-Shuffle.PER_WORKER-csv] ______________

client = <Client: 'tcp://127.0.0.1:44355' processes=2 threads=16, memory=125.83 GiB>
tmpdir = local('/tmp/pytest-of-jenkins/pytest-10/test_dask_preproc_cpu_None_Shu1')
datasets = {'cats': local('/tmp/pytest-of-jenkins/pytest-10/cats0'), 'csv': local('/tmp/pytest-of-jenkins/pytest-10/csv0'), 'csv-...ocal('/tmp/pytest-of-jenkins/pytest-10/csv-no-header0'), 'parquet': local('/tmp/pytest-of-jenkins/pytest-10/parquet0')}
engine = 'csv', shuffle = <Shuffle.PER_WORKER: 1>, cpu = None

@pytest.mark.parametrize("engine", ["parquet", "csv", "csv-no-header"])
@pytest.mark.parametrize("shuffle", [Shuffle.PER_WORKER, None])
@pytest.mark.parametrize("cpu", [None, True])
def test_dask_preproc_cpu(client, tmpdir, datasets, engine, shuffle, cpu):
    paths = glob.glob(str(datasets[engine]) + "/*." + engine.split("-")[0])
    if engine == "parquet":
        df1 = cudf.read_parquet(paths[0])[mycols_pq]
        df2 = cudf.read_parquet(paths[1])[mycols_pq]
    elif engine == "csv":
        df1 = cudf.read_csv(paths[0], header=0)[mycols_csv]
        df2 = cudf.read_csv(paths[1], header=0)[mycols_csv]
    else:
        df1 = cudf.read_csv(paths[0], names=allcols_csv)[mycols_csv]
        df2 = cudf.read_csv(paths[1], names=allcols_csv)[mycols_csv]
    df0 = cudf.concat([df1, df2], axis=0)

    if engine in ("parquet", "csv"):
        dataset = Dataset(paths, part_size="1MB", cpu=cpu)
    else:
        dataset = Dataset(paths, names=allcols_csv, part_size="1MB", cpu=cpu)

    # Simple transform (normalize)
    cat_names = ["name-string"]
    cont_names = ["x", "y", "id"]
    label_name = ["label"]
    conts = cont_names >> ops.FillMissing() >> ops.Normalize()
    workflow = Workflow(conts + cat_names + label_name, client=client)
    transformed = workflow.fit_transform(dataset)

    # Write out dataset
    output_path = os.path.join(tmpdir, "processed")
    transformed.to_parquet(output_path=output_path, shuffle=shuffle, out_files_per_proc=4)

    # Check the final result
    df_disk = dd_read_parquet(output_path, engine="pyarrow").compute()
  assert_eq(
        df0.sort_values(["id", "x"])[["name-string", "label"]],
        df_disk.sort_values(["id", "x"])[["name-string", "label"]],
        check_index=False,
    )

tests/unit/test_dask_nvt.py:274:


../../../.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/utils.py:828: in assert_eq
tm.assert_frame_equal(a, b, **kwargs)
pandas/_libs/testing.pyx:46: in pandas._libs.testing.assert_almost_equal
???


???
E AssertionError: DataFrame.iloc[:, 0] (column name="name-string") are different
E
E DataFrame.iloc[:, 0] (column name="name-string") values are different (0.04629 %)
E [index]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...]
E [left]: [Quinn, Oliver, Laura, Sarah, Oliver, Gary, Xavier, Zelda, Patricia, Oliver, Charlie, Hannah, Ray, Yvonne, Michael, Yvonne, Jerry, Michael, Xavier, Tim, Oliver, Quinn, Kevin, Ingrid, Jerry, Charlie, Sarah, Wendy, Alice, Ray, Yvonne, Charlie, Quinn, Xavier, Michael, Kevin, Tim, Kevin, Laura, Frank, Yvonne, Ingrid, Kevin, Ingrid, Patricia, Wendy, Wendy, Michael, Bob, Alice, Ingrid, Charlie, Edith, Gary, Xavier, Hannah, Hannah, Tim, Norbert, Gary, Yvonne, Bob, Frank, Jerry, Xavier, Patricia, Victor, Frank, Kevin, Sarah, Frank, Patricia, Ray, Xavier, Bob, Ray, Tim, Oliver, Quinn, Laura, Frank, Hannah, Ingrid, Michael, Oliver, Oliver, Tim, Yvonne, Oliver, Alice, Kevin, Laura, Jerry, Tim, Michael, Bob, Hannah, Jerry, Ursula, Alice, ...]
E [right]: [Quinn, Oliver, Laura, Sarah, Oliver, Gary, Xavier, Zelda, Patricia, Oliver, Charlie, Hannah, Ray, Yvonne, Michael, Yvonne, Jerry, Michael, Xavier, Tim, Oliver, Quinn, Kevin, Ingrid, Jerry, Charlie, Sarah, Wendy, Alice, Ray, Yvonne, Charlie, Quinn, Xavier, Michael, Kevin, Tim, Kevin, Laura, Frank, Yvonne, Ingrid, Kevin, Ingrid, Patricia, Wendy, Wendy, Michael, Bob, Alice, Ingrid, Charlie, Edith, Gary, Xavier, Hannah, Hannah, Tim, Norbert, Gary, Yvonne, Bob, Frank, Jerry, Xavier, Patricia, Victor, Frank, Kevin, Sarah, Frank, Patricia, Ray, Xavier, Bob, Ray, Tim, Oliver, Quinn, Laura, Frank, Hannah, Ingrid, Michael, Oliver, Oliver, Tim, Yvonne, Oliver, Alice, Kevin, Laura, Jerry, Tim, Michael, Bob, Hannah, Jerry, Ursula, Alice, ...]

pandas/_libs/testing.pyx:161: AssertionError
_________ test_dask_preproc_cpu[None-Shuffle.PER_WORKER-csv-no-header] _________

client = <Client: 'tcp://127.0.0.1:44355' processes=2 threads=16, memory=125.83 GiB>
tmpdir = local('/tmp/pytest-of-jenkins/pytest-10/test_dask_preproc_cpu_None_Shu2')
datasets = {'cats': local('/tmp/pytest-of-jenkins/pytest-10/cats0'), 'csv': local('/tmp/pytest-of-jenkins/pytest-10/csv0'), 'csv-...ocal('/tmp/pytest-of-jenkins/pytest-10/csv-no-header0'), 'parquet': local('/tmp/pytest-of-jenkins/pytest-10/parquet0')}
engine = 'csv-no-header', shuffle = <Shuffle.PER_WORKER: 1>, cpu = None

@pytest.mark.parametrize("engine", ["parquet", "csv", "csv-no-header"])
@pytest.mark.parametrize("shuffle", [Shuffle.PER_WORKER, None])
@pytest.mark.parametrize("cpu", [None, True])
def test_dask_preproc_cpu(client, tmpdir, datasets, engine, shuffle, cpu):
    paths = glob.glob(str(datasets[engine]) + "/*." + engine.split("-")[0])
    if engine == "parquet":
        df1 = cudf.read_parquet(paths[0])[mycols_pq]
        df2 = cudf.read_parquet(paths[1])[mycols_pq]
    elif engine == "csv":
        df1 = cudf.read_csv(paths[0], header=0)[mycols_csv]
        df2 = cudf.read_csv(paths[1], header=0)[mycols_csv]
    else:
        df1 = cudf.read_csv(paths[0], names=allcols_csv)[mycols_csv]
        df2 = cudf.read_csv(paths[1], names=allcols_csv)[mycols_csv]
    df0 = cudf.concat([df1, df2], axis=0)

    if engine in ("parquet", "csv"):
        dataset = Dataset(paths, part_size="1MB", cpu=cpu)
    else:
        dataset = Dataset(paths, names=allcols_csv, part_size="1MB", cpu=cpu)

    # Simple transform (normalize)
    cat_names = ["name-string"]
    cont_names = ["x", "y", "id"]
    label_name = ["label"]
    conts = cont_names >> ops.FillMissing() >> ops.Normalize()
    workflow = Workflow(conts + cat_names + label_name, client=client)
    transformed = workflow.fit_transform(dataset)

    # Write out dataset
    output_path = os.path.join(tmpdir, "processed")
    transformed.to_parquet(output_path=output_path, shuffle=shuffle, out_files_per_proc=4)

    # Check the final result
    df_disk = dd_read_parquet(output_path, engine="pyarrow").compute()
  assert_eq(
        df0.sort_values(["id", "x"])[["name-string", "label"]],
        df_disk.sort_values(["id", "x"])[["name-string", "label"]],
        check_index=False,
    )

tests/unit/test_dask_nvt.py:274:


../../../.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/utils.py:828: in assert_eq
tm.assert_frame_equal(a, b, **kwargs)
pandas/_libs/testing.pyx:46: in pandas._libs.testing.assert_almost_equal
???


???
E AssertionError: DataFrame.iloc[:, 0] (column name="name-string") are different
E
E DataFrame.iloc[:, 0] (column name="name-string") values are different (0.04629 %)
E [index]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...]
E [left]: [Quinn, Oliver, Laura, Sarah, Oliver, Gary, Xavier, Zelda, Patricia, Oliver, Charlie, Hannah, Ray, Yvonne, Michael, Yvonne, Jerry, Michael, Xavier, Tim, Oliver, Quinn, Kevin, Ingrid, Jerry, Charlie, Sarah, Wendy, Alice, Ray, Yvonne, Charlie, Quinn, Xavier, Michael, Kevin, Tim, Kevin, Laura, Frank, Yvonne, Ingrid, Kevin, Ingrid, Patricia, Wendy, Wendy, Michael, Bob, Alice, Ingrid, Charlie, Edith, Gary, Xavier, Hannah, Hannah, Tim, Norbert, Gary, Yvonne, Bob, Frank, Jerry, Xavier, Patricia, Victor, Frank, Kevin, Sarah, Frank, Patricia, Ray, Xavier, Bob, Ray, Tim, Oliver, Quinn, Laura, Frank, Hannah, Ingrid, Michael, Oliver, Oliver, Tim, Yvonne, Oliver, Alice, Kevin, Laura, Jerry, Tim, Michael, Bob, Hannah, Jerry, Ursula, Alice, ...]
E [right]: [Quinn, Oliver, Laura, Sarah, Oliver, Gary, Xavier, Zelda, Patricia, Oliver, Charlie, Hannah, Ray, Yvonne, Michael, Yvonne, Jerry, Michael, Xavier, Tim, Oliver, Quinn, Kevin, Ingrid, Jerry, Charlie, Sarah, Wendy, Alice, Ray, Yvonne, Charlie, Quinn, Xavier, Michael, Kevin, Tim, Kevin, Laura, Frank, Yvonne, Ingrid, Kevin, Ingrid, Patricia, Wendy, Wendy, Michael, Bob, Alice, Ingrid, Charlie, Edith, Gary, Xavier, Hannah, Hannah, Tim, Norbert, Gary, Yvonne, Bob, Frank, Jerry, Xavier, Patricia, Victor, Frank, Kevin, Sarah, Frank, Patricia, Ray, Xavier, Bob, Ray, Tim, Oliver, Quinn, Laura, Frank, Hannah, Ingrid, Michael, Oliver, Oliver, Tim, Yvonne, Oliver, Alice, Kevin, Laura, Jerry, Tim, Michael, Bob, Hannah, Jerry, Ursula, Alice, ...]

pandas/_libs/testing.pyx:161: AssertionError
_________ test_dask_preproc_cpu[True-Shuffle.PER_WORKER-csv-no-header] _________

client = <Client: 'tcp://127.0.0.1:44355' processes=2 threads=16, memory=125.83 GiB>
tmpdir = local('/tmp/pytest-of-jenkins/pytest-10/test_dask_preproc_cpu_True_Shu2')
datasets = {'cats': local('/tmp/pytest-of-jenkins/pytest-10/cats0'), 'csv': local('/tmp/pytest-of-jenkins/pytest-10/csv0'), 'csv-...ocal('/tmp/pytest-of-jenkins/pytest-10/csv-no-header0'), 'parquet': local('/tmp/pytest-of-jenkins/pytest-10/parquet0')}
engine = 'csv-no-header', shuffle = <Shuffle.PER_WORKER: 1>, cpu = True

@pytest.mark.parametrize("engine", ["parquet", "csv", "csv-no-header"])
@pytest.mark.parametrize("shuffle", [Shuffle.PER_WORKER, None])
@pytest.mark.parametrize("cpu", [None, True])
def test_dask_preproc_cpu(client, tmpdir, datasets, engine, shuffle, cpu):
    paths = glob.glob(str(datasets[engine]) + "/*." + engine.split("-")[0])
    if engine == "parquet":
        df1 = cudf.read_parquet(paths[0])[mycols_pq]
        df2 = cudf.read_parquet(paths[1])[mycols_pq]
    elif engine == "csv":
        df1 = cudf.read_csv(paths[0], header=0)[mycols_csv]
        df2 = cudf.read_csv(paths[1], header=0)[mycols_csv]
    else:
        df1 = cudf.read_csv(paths[0], names=allcols_csv)[mycols_csv]
        df2 = cudf.read_csv(paths[1], names=allcols_csv)[mycols_csv]
    df0 = cudf.concat([df1, df2], axis=0)

    if engine in ("parquet", "csv"):
        dataset = Dataset(paths, part_size="1MB", cpu=cpu)
    else:
        dataset = Dataset(paths, names=allcols_csv, part_size="1MB", cpu=cpu)

    # Simple transform (normalize)
    cat_names = ["name-string"]
    cont_names = ["x", "y", "id"]
    label_name = ["label"]
    conts = cont_names >> ops.FillMissing() >> ops.Normalize()
    workflow = Workflow(conts + cat_names + label_name, client=client)
    transformed = workflow.fit_transform(dataset)

    # Write out dataset
    output_path = os.path.join(tmpdir, "processed")
    transformed.to_parquet(output_path=output_path, shuffle=shuffle, out_files_per_proc=4)

    # Check the final result
    df_disk = dd_read_parquet(output_path, engine="pyarrow").compute()
  assert_eq(
        df0.sort_values(["id", "x"])[["name-string", "label"]],
        df_disk.sort_values(["id", "x"])[["name-string", "label"]],
        check_index=False,
    )

tests/unit/test_dask_nvt.py:274:


../../../.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/utils.py:828: in assert_eq
tm.assert_frame_equal(a, b, **kwargs)
pandas/_libs/testing.pyx:46: in pandas._libs.testing.assert_almost_equal
???


???
E AssertionError: DataFrame.iloc[:, 0] (column name="name-string") are different
E
E DataFrame.iloc[:, 0] (column name="name-string") values are different (0.04629 %)
E [index]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...]
E [left]: [Quinn, Oliver, Laura, Sarah, Oliver, Gary, Xavier, Zelda, Patricia, Oliver, Charlie, Hannah, Ray, Yvonne, Michael, Yvonne, Jerry, Michael, Xavier, Tim, Oliver, Quinn, Kevin, Ingrid, Jerry, Charlie, Sarah, Wendy, Alice, Ray, Yvonne, Charlie, Quinn, Xavier, Michael, Kevin, Tim, Kevin, Laura, Frank, Yvonne, Ingrid, Kevin, Ingrid, Patricia, Wendy, Wendy, Michael, Bob, Alice, Ingrid, Charlie, Edith, Gary, Xavier, Hannah, Hannah, Tim, Norbert, Gary, Yvonne, Bob, Frank, Jerry, Xavier, Patricia, Victor, Frank, Kevin, Sarah, Frank, Patricia, Ray, Xavier, Bob, Ray, Tim, Oliver, Quinn, Laura, Frank, Hannah, Ingrid, Michael, Oliver, Oliver, Tim, Yvonne, Oliver, Alice, Kevin, Laura, Jerry, Tim, Michael, Bob, Hannah, Jerry, Ursula, Alice, ...]
E [right]: [Quinn, Oliver, Laura, Sarah, Oliver, Gary, Xavier, Zelda, Patricia, Oliver, Charlie, Hannah, Ray, Yvonne, Michael, Yvonne, Jerry, Michael, Xavier, Tim, Oliver, Quinn, Kevin, Ingrid, Jerry, Charlie, Sarah, Wendy, Alice, Ray, Yvonne, Charlie, Quinn, Xavier, Michael, Kevin, Tim, Kevin, Laura, Frank, Yvonne, Ingrid, Kevin, Ingrid, Patricia, Wendy, Wendy, Michael, Bob, Alice, Ingrid, Charlie, Edith, Gary, Xavier, Hannah, Hannah, Tim, Norbert, Gary, Yvonne, Bob, Frank, Jerry, Xavier, Patricia, Victor, Frank, Kevin, Sarah, Frank, Patricia, Ray, Xavier, Bob, Ray, Tim, Oliver, Quinn, Laura, Frank, Hannah, Ingrid, Michael, Oliver, Oliver, Tim, Yvonne, Oliver, Alice, Kevin, Laura, Jerry, Tim, Michael, Bob, Hannah, Jerry, Ursula, Alice, ...]

pandas/_libs/testing.pyx:161: AssertionError
=============================== warnings summary ===============================
tests/unit/test_dask_nvt.py: 3 warnings
tests/unit/test_io.py: 24 warnings
tests/unit/test_tf4rec.py: 2 warnings
tests/unit/test_tools.py: 2 warnings
tests/unit/test_triton_inference.py: 5 warnings
tests/unit/loader/test_tf_dataloader.py: 48 warnings
tests/unit/loader/test_torch_dataloader.py: 14 warnings
tests/unit/ops/test_column_similarity.py: 7 warnings
tests/unit/ops/test_ops.py: 74 warnings
tests/unit/workflow/test_workflow.py: 31 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
/var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg/numba/cuda/compiler.py:865: NumbaPerformanceWarning: �[1mGrid size (1) < 2 * SM count (112) will likely result in GPU under utilization due to low occupancy.�[0m
warn(NumbaPerformanceWarning(msg))

tests/unit/test_io.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/init.py:38: DeprecationWarning: ColumnGroup is deprecated, use ColumnSelector instead
warnings.warn("ColumnGroup is deprecated, use ColumnSelector instead", DeprecationWarning)

tests/unit/test_io.py: 24 warnings
tests/unit/loader/test_torch_dataloader.py: 54 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/node.py:47: FutureWarning: The ["a", "b", "c"] >> ops.Operator syntax for creating a ColumnGroup has been deprecated in NVTabular 21.09 and will be removed in a future version.
warnings.warn(

tests/unit/test_io.py: 36 warnings
tests/unit/workflow/test_workflow.py: 44 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/workflow.py:89: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for execution. Please use the client argument to initialize a Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 52 warnings
tests/unit/workflow/test_workflow.py: 35 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dask.py:372: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for this write operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 20 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:477: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler is being used for this shuffle operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.1]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:125: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[f"{col}_filled"] = df[col].isna()

tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.1]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:126: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[col] = df[col].fillna(self.medians[col])

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
tests/unit/ops/test_ops.py::test_fill_missing[True-False-parquet]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/indexing.py:1637: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self._setitem_single_block(indexer, value, name)

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:54: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[f"{col}_filled"] = df[col].isna()

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:55: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[col] = df[col].fillna(self.fill_val)

tests/unit/ops/test_ops.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:190: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[tmp] = _arange(len(df), like_df=df, dtype="int32")

tests/unit/ops/test_ops.py::test_join_external[True-True-left-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-left-device-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-device-pandas-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:171: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
_ext.drop_duplicates(ignore_index=True, inplace=True)

tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-False]
tests/unit/ops/test_ops.py::test_groupby_op[id-True]
tests/unit/ops/test_ops.py::test_groupby_op[id-False]
/var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/core.py:6610: UserWarning: Insufficient elements for head. 1 elements requested, only 0 elements available. Try passing larger npartitions to head.
warnings.warn(msg.format(n, len(r)))

tests/unit/workflow/test_cpu_workflow.py: 78 warnings
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/frame.py:3191: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self[k1] = value[k2]

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

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Branch BrPart Cover Missing

examples/multi-gpu-movielens/torch_trainer.py 65 0 6 1 99% 32->36
nvtabular/init.py 18 0 0 0 100%
nvtabular/columns/init.py 2 0 0 0 100%
nvtabular/columns/schema.py 203 19 95 23 86% 43->59, 46, 48, 50-53, 55, 65, 80, 96->106, 100, 102, 120->122, 142, 169, 255->258, 265, 277->287, 281, 282->287, 285->287, 317, 324, 333, 336, 341->340
nvtabular/columns/selector.py 74 1 34 0 99% 121
nvtabular/dispatch.py 258 44 126 22 81% 35-38, 43-45, 51-61, 68-69, 100, 119, 130, 136, 141->143, 154, 177-180, 219, 222, 228, 244, 251, 282->287, 285, 288, 291->295, 328, 339-342, 369-372, 402, 406, 447, 471, 473, 480
nvtabular/framework_utils/init.py 0 0 0 0 100%
nvtabular/framework_utils/tensorflow/init.py 1 0 0 0 100%
nvtabular/framework_utils/tensorflow/feature_column_utils.py 134 78 90 15 39% 30, 99, 103, 114-130, 140, 143-158, 162, 166-167, 173-198, 207-217, 220-227, 229->233, 234, 239-279, 282
nvtabular/framework_utils/tensorflow/layers/init.py 4 0 0 0 100%
nvtabular/framework_utils/tensorflow/layers/embedding.py 153 12 85 6 91% 60, 68->49, 122, 179, 231-239, 335->343, 357->360, 363-364, 367
nvtabular/framework_utils/tensorflow/layers/interaction.py 47 25 20 1 43% 49, 74-103, 106-110, 113
nvtabular/framework_utils/tensorflow/layers/outer_product.py 30 24 10 0 15% 37-38, 41-60, 71-84, 87
nvtabular/framework_utils/torch/init.py 0 0 0 0 100%
nvtabular/framework_utils/torch/layers/init.py 2 0 0 0 100%
nvtabular/framework_utils/torch/layers/embeddings.py 32 2 14 2 91% 50, 91
nvtabular/framework_utils/torch/models.py 45 1 28 4 93% 57->61, 87->89, 93->96, 103
nvtabular/framework_utils/torch/utils.py 75 5 30 5 90% 51->53, 64, 71->76, 75, 118-120
nvtabular/inference/init.py 0 0 0 0 100%
nvtabular/inference/triton/init.py 302 131 130 13 58% 82-86, 140-190, 235-279, 310, 336-344, 352-359, 378, 400-416, 457-461, 499-509, 533-555, 559-626, 633->636, 636->632, 672-682, 691, 701, 722, 729, 735->738, 739
nvtabular/inference/triton/benchmarking_tools.py 52 52 10 0 0% 2-103
nvtabular/inference/triton/data_conversions.py 87 3 58 4 95% 32-33, 84
nvtabular/inference/triton/model.py 176 176 98 0 0% 27-332
nvtabular/inference/triton/model_config_pb2.py 299 0 2 0 100%
nvtabular/io/init.py 4 0 0 0 100%
nvtabular/io/avro.py 88 88 30 0 0% 16-189
nvtabular/io/csv.py 57 6 20 5 86% 22-23, 99, 103->107, 108, 110, 124
nvtabular/io/dask.py 183 8 72 11 93% 111, 114, 150, 398, 408, 425->428, 436, 440->442, 442->438, 447, 449
nvtabular/io/dataframe_engine.py 61 5 28 6 88% 19-20, 50, 69, 88->92, 92->97, 94->97, 97->116, 125
nvtabular/io/dataset.py 331 45 154 29 84% 45-46, 247, 249, 262, 271, 289-303, 406->476, 411-414, 419->429, 424-425, 436->434, 450->454, 465, 476->485, 536-537, 538->542, 585, 707, 709, 711, 717, 721-723, 725, 785-786, 813, 820-821, 827, 833, 928-929, 1045-1050, 1056, 1137
nvtabular/io/dataset_engine.py 23 1 0 0 96% 45
nvtabular/io/hugectr.py 45 2 24 2 91% 34, 74->97, 101
nvtabular/io/parquet.py 492 25 156 15 94% 33-34, 88-89, 92-100, 124->126, 213-215, 338-343, 381-386, 502->509, 570->575, 576-577, 697, 701, 705, 711, 743, 760, 764, 771->773, 881->exit, 891->896, 901->911, 916, 938
nvtabular/io/shuffle.py 31 6 16 5 77% 42, 44-45, 49, 59, 63
nvtabular/io/writer.py 175 13 68 5 92% 24-25, 51, 79, 125, 128, 212, 221, 224, 267, 288-290
nvtabular/io/writer_factory.py 18 2 8 2 85% 35, 60
nvtabular/loader/init.py 0 0 0 0 100%
nvtabular/loader/backend.py 327 13 138 10 95% 127, 142-143, 233->235, 245-249, 295-296, 335->339, 410, 414-415, 445, 550, 558
nvtabular/loader/tensorflow.py 155 22 50 7 85% 57, 65-68, 78, 88, 296, 332, 347-349, 378-380, 390-398, 401-404
nvtabular/loader/tf_utils.py 55 10 20 5 80% 29->32, 32->34, 39->41, 43, 50-51, 58-60, 66-70
nvtabular/loader/torch.py 81 13 16 2 78% 25-27, 30-36, 111, 149-150
nvtabular/ops/init.py 21 0 0 0 100%
nvtabular/ops/bucketize.py 37 10 18 3 69% 53-55, 59->exit, 62-65, 84-87, 94
nvtabular/ops/categorify.py 591 66 330 47 86% 232, 234, 249, 253, 261, 269, 271, 298, 317-318, 336, 347->351, 355-362, 443-444, 464-465, 474, 525->521, 547->549, 643, 661, 697, 775-776, 791-795, 796->760, 814, 822, 829->exit, 853, 856->859, 891, 896, 912->916, 923-926, 937, 941, 943, 950, 955-958, 1036, 1038, 1067->1090, 1073->1090, 1091-1096, 1133, 1151->1156, 1155, 1165->1162, 1170->1162, 1177, 1180, 1188-1198
nvtabular/ops/clip.py 18 2 6 3 79% 44, 52->54, 55
nvtabular/ops/column_similarity.py 118 25 38 5 74% 19-20, 78->exit, 108, 134, 198-199, 208-210, 218-234, 251->254, 255, 265
nvtabular/ops/data_stats.py 56 2 22 3 94% 91->93, 95, 97->87, 102
nvtabular/ops/difference_lag.py 31 1 8 1 95% 69->71, 94
nvtabular/ops/dropna.py 8 0 0 0 100%
nvtabular/ops/fill.py 91 12 36 3 82% 63-67, 93, 121, 147, 151, 162-165
nvtabular/ops/filter.py 20 1 6 1 92% 49
nvtabular/ops/groupby.py 119 3 70 4 96% 73, 84, 94->96, 106->111, 141
nvtabular/ops/hash_bucket.py 35 3 18 2 87% 72, 102, 108
nvtabular/ops/hashed_cross.py 36 4 15 3 86% 53, 66, 81, 91
nvtabular/ops/internal/init.py 3 0 0 0 100%
nvtabular/ops/internal/concat_columns.py 11 0 0 0 100%
nvtabular/ops/internal/identity.py 6 1 0 0 83% 42
nvtabular/ops/internal/subset_columns.py 13 1 0 0 92% 53
nvtabular/ops/join_external.py 89 7 36 6 90% 20-21, 113, 115, 117, 159, 176->178, 215
nvtabular/ops/join_groupby.py 101 7 36 4 92% 108, 115, 124, 131->130, 215-216, 219-220
nvtabular/ops/lambdaop.py 39 6 18 6 79% 59, 63, 77, 89, 94, 103
nvtabular/ops/list_slice.py 66 24 26 1 58% 21-22, 53-54, 104-118, 126-137
nvtabular/ops/logop.py 13 0 0 0 100%
nvtabular/ops/moments.py 65 0 20 0 100%
nvtabular/ops/normalize.py 81 10 14 1 86% 70, 78-79, 85, 118-119, 141-142, 146, 157
nvtabular/ops/operator.py 64 1 12 1 97% 111
nvtabular/ops/rename.py 41 3 22 3 90% 47, 88-90
nvtabular/ops/stat_operator.py 8 0 0 0 100%
nvtabular/ops/target_encoding.py 153 11 66 4 91% 167->171, 175->184, 232-233, 236-237, 249-255, 346->349, 362
nvtabular/tags.py 16 0 0 0 100%
nvtabular/tools/init.py 0 0 0 0 100%
nvtabular/tools/data_gen.py 236 1 62 1 99% 321
nvtabular/tools/dataset_inspector.py 50 7 18 1 79% 32-39
nvtabular/tools/inspector_script.py 46 46 0 0 0% 17-168
nvtabular/utils.py 102 43 46 8 52% 31-32, 36-37, 50, 61-62, 64-66, 69, 72, 78, 84, 90-126, 145, 149->153
nvtabular/worker.py 82 5 38 7 90% 24-25, 82->99, 91, 92->99, 99->102, 108, 110, 111->113
nvtabular/workflow/init.py 2 0 0 0 100%
nvtabular/workflow/node.py 229 18 110 10 89% 55, 92->97, 145, 247->251, 287, 301, 310, 328-333, 338, 387-388, 399->394, 438-443
nvtabular/workflow/workflow.py 217 16 112 8 92% 28-29, 47, 118, 141, 197, 224-226, 332, 347-348, 366-367, 493, 505

TOTAL 7099 1168 2839 336 81%
Coverage XML written to file coverage.xml

Required test coverage of 70% reached. Total coverage: 81.15%
=========================== short test summary info ============================
SKIPPED [1] ../../../../../usr/local/lib/python3.8/dist-packages/dask_cudf/io/tests/test_s3.py:16: could not import 's3fs': No module named 's3fs'
SKIPPED [8] tests/unit/test_io.py:514: could not import 'uavro': No module named 'uavro'
SKIPPED [1] tests/unit/loader/test_tf_dataloader.py:521: not working correctly in ci environment
===== 3 failed, 1464 passed, 10 skipped, 772 warnings in 912.15s (0:15:12) =====
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/NVTabular/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[nvtabular_tests] $ /bin/bash /tmp/jenkins1951859770167966902.sh

@nvidia-merlin-bot
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GitHub pull request #1115 of commit 201bac7188be718086b32ef5a5d46ba3591f13c9, no merge conflicts.
Running as SYSTEM
Setting status of 201bac7188be718086b32ef5a5d46ba3591f13c9 to PENDING with url http://10.20.13.93:8080/job/nvtabular_tests/3445/ and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/nvtabular_tests
using credential nvidia-merlin-bot
Cloning the remote Git repository
Cloning repository https://github.com/NVIDIA/NVTabular.git
 > git init /var/jenkins_home/workspace/nvtabular_tests/nvtabular # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > 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/NVTabular.git +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/1115/*:refs/remotes/origin/pr/1115/* # timeout=10
 > git rev-parse 201bac7188be718086b32ef5a5d46ba3591f13c9^{commit} # timeout=10
Checking out Revision 201bac7188be718086b32ef5a5d46ba3591f13c9 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 201bac7188be718086b32ef5a5d46ba3591f13c9 # timeout=10
Commit message: "all the way green select by tag"
 > git rev-list --no-walk 3af62e4edb9e645c8b677f1be66766a3ac336ed6 # timeout=10
[nvtabular_tests] $ /bin/bash /tmp/jenkins6794570378129957607.sh
Installing NVTabular
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: pip in /var/jenkins_home/.local/lib/python3.8/site-packages (21.2.4)
Requirement already satisfied: setuptools in /var/jenkins_home/.local/lib/python3.8/site-packages (58.0.4)
Requirement already satisfied: wheel in /var/jenkins_home/.local/lib/python3.8/site-packages (0.37.0)
Requirement already satisfied: pybind11 in /var/jenkins_home/.local/lib/python3.8/site-packages (2.7.1)
running develop
running egg_info
creating nvtabular.egg-info
writing nvtabular.egg-info/PKG-INFO
writing dependency_links to nvtabular.egg-info/dependency_links.txt
writing requirements to nvtabular.egg-info/requires.txt
writing top-level names to nvtabular.egg-info/top_level.txt
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*.h' under directory 'cpp'
warning: no files found matching '*.cu' under directory 'cpp'
warning: no files found matching '*.cuh' under directory 'cpp'
adding license file 'LICENSE'
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
running build_ext
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.8 -c flagcheck.cpp -o flagcheck.o -std=c++17
building 'nvtabular_cpp' extension
creating build
creating build/temp.linux-x86_64-3.8
creating build/temp.linux-x86_64-3.8/cpp
creating build/temp.linux-x86_64-3.8/cpp/nvtabular
creating build/temp.linux-x86_64-3.8/cpp/nvtabular/inference
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+56.g201bac7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+56.g201bac7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+56.g201bac7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/categorify.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+56.g201bac7 -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/fill.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -std=c++17 -fvisibility=hidden -g0
creating build/lib.linux-x86_64-3.8
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -o build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so
copying build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so -> 
Generating nvtabular/inference/triton/model_config_pb2.py from nvtabular/inference/triton/model_config.proto
Creating /var/jenkins_home/.local/lib/python3.8/site-packages/nvtabular.egg-link (link to .)
nvtabular 0.6.0+56.g201bac7 is already the active version in easy-install.pth

Installed /var/jenkins_home/workspace/nvtabular_tests/nvtabular
Processing dependencies for nvtabular==0.6.0+56.g201bac7
Searching for protobuf==3.17.3
Best match: protobuf 3.17.3
Adding protobuf 3.17.3 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for tensorflow-metadata==1.2.0
Best match: tensorflow-metadata 1.2.0
Processing tensorflow_metadata-1.2.0-py3.8.egg
tensorflow-metadata 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow_metadata-1.2.0-py3.8.egg
Searching for pyarrow==4.0.1
Best match: pyarrow 4.0.1
Adding pyarrow 4.0.1 to easy-install.pth file
Installing plasma_store script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for tqdm==4.61.2
Best match: tqdm 4.61.2
Processing tqdm-4.61.2-py3.8.egg
tqdm 4.61.2 is already the active version in easy-install.pth
Installing tqdm script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tqdm-4.61.2-py3.8.egg
Searching for numba==0.54.0
Best match: numba 0.54.0
Processing numba-0.54.0-py3.8-linux-x86_64.egg
numba 0.54.0 is already the active version in easy-install.pth
Installing pycc script to /var/jenkins_home/.local/bin
Installing numba script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg
Searching for pandas==1.2.5
Best match: pandas 1.2.5
Processing pandas-1.2.5-py3.8-linux-x86_64.egg
pandas 1.2.5 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg
Searching for distributed==2021.4.1
Best match: distributed 2021.4.1
Processing distributed-2021.4.1-py3.8.egg
distributed 2021.4.1 is already the active version in easy-install.pth
Installing dask-ssh script to /var/jenkins_home/.local/bin
Installing dask-scheduler script to /var/jenkins_home/.local/bin
Installing dask-worker script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/distributed-2021.4.1-py3.8.egg
Searching for dask==2021.4.1
Best match: dask 2021.4.1
Processing dask-2021.4.1-py3.8.egg
dask 2021.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg
Searching for PyYAML==5.4.1
Best match: PyYAML 5.4.1
Processing PyYAML-5.4.1-py3.8-linux-x86_64.egg
PyYAML 5.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg
Searching for six==1.15.0
Best match: six 1.15.0
Adding six 1.15.0 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for googleapis-common-protos==1.53.0
Best match: googleapis-common-protos 1.53.0
Processing googleapis_common_protos-1.53.0-py3.8.egg
googleapis-common-protos 1.53.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/googleapis_common_protos-1.53.0-py3.8.egg
Searching for absl-py==0.12.0
Best match: absl-py 0.12.0
Processing absl_py-0.12.0-py3.8.egg
absl-py 0.12.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/absl_py-0.12.0-py3.8.egg
Searching for numpy==1.20.2
Best match: numpy 1.20.2
Adding numpy 1.20.2 to easy-install.pth file
Installing f2py script to /var/jenkins_home/.local/bin
Installing f2py3 script to /var/jenkins_home/.local/bin
Installing f2py3.8 script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for setuptools==58.0.4
Best match: setuptools 58.0.4
Adding setuptools 58.0.4 to easy-install.pth file

Using /var/jenkins_home/.local/lib/python3.8/site-packages
Searching for llvmlite==0.37.0
Best match: llvmlite 0.37.0
Processing llvmlite-0.37.0-py3.8-linux-x86_64.egg
llvmlite 0.37.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/llvmlite-0.37.0-py3.8-linux-x86_64.egg
Searching for pytz==2021.1
Best match: pytz 2021.1
Adding pytz 2021.1 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for python-dateutil==2.8.2
Best match: python-dateutil 2.8.2
Adding python-dateutil 2.8.2 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for zict==2.0.0
Best match: zict 2.0.0
Processing zict-2.0.0-py3.8.egg
zict 2.0.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg
Searching for tornado==6.1
Best match: tornado 6.1
Processing tornado-6.1-py3.8-linux-x86_64.egg
tornado 6.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tornado-6.1-py3.8-linux-x86_64.egg
Searching for toolz==0.11.1
Best match: toolz 0.11.1
Processing toolz-0.11.1-py3.8.egg
toolz 0.11.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/toolz-0.11.1-py3.8.egg
Searching for tblib==1.7.0
Best match: tblib 1.7.0
Processing tblib-1.7.0-py3.8.egg
tblib 1.7.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg
Searching for sortedcontainers==2.4.0
Best match: sortedcontainers 2.4.0
Processing sortedcontainers-2.4.0-py3.8.egg
sortedcontainers 2.4.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg
Searching for psutil==5.8.0
Best match: psutil 5.8.0
Processing psutil-5.8.0-py3.8-linux-x86_64.egg
psutil 5.8.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg
Searching for msgpack==1.0.2
Best match: msgpack 1.0.2
Processing msgpack-1.0.2-py3.8-linux-x86_64.egg
msgpack 1.0.2 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/msgpack-1.0.2-py3.8-linux-x86_64.egg
Searching for cloudpickle==1.6.0
Best match: cloudpickle 1.6.0
Processing cloudpickle-1.6.0-py3.8.egg
cloudpickle 1.6.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/cloudpickle-1.6.0-py3.8.egg
Searching for click==8.0.1
Best match: click 8.0.1
Processing click-8.0.1-py3.8.egg
click 8.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/click-8.0.1-py3.8.egg
Searching for partd==1.2.0
Best match: partd 1.2.0
Processing partd-1.2.0-py3.8.egg
partd 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg
Searching for fsspec==2021.8.1
Best match: fsspec 2021.8.1
Processing fsspec-2021.8.1-py3.8.egg
fsspec 2021.8.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/fsspec-2021.8.1-py3.8.egg
Searching for HeapDict==1.0.1
Best match: HeapDict 1.0.1
Processing HeapDict-1.0.1-py3.8.egg
HeapDict 1.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg
Searching for locket==0.2.1
Best match: locket 0.2.1
Processing locket-0.2.1-py3.8.egg
locket 0.2.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg
Finished processing dependencies for nvtabular==0.6.0+56.g201bac7
Running black --check
All done! ✨ 🍰 ✨
125 files would be left unchanged.
Running flake8
Running isort
Skipped 2 files
Running bandit
Running pylint
************* Module nvtabular.ops.categorify
nvtabular/ops/categorify.py:485:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)
************* Module nvtabular.ops.fill
nvtabular/ops/fill.py:67:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)


Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

Running flake8-nb
Building docs
make: Entering directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
make: Leaving directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/nvtabular_tests/nvtabular, configfile: pyproject.toml
plugins: cov-2.12.1, forked-1.3.0, xdist-2.3.0
collected 1503 items / 1 skipped / 1502 selected

tests/unit/test_dask_nvt.py ............................................ [ 2%]
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tests/unit/test_io.py .................................................. [ 10%]
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.........ssssssss................................................. [ 20%]
tests/unit/test_notebooks.py ...... [ 20%]
tests/unit/test_tf4rec.py . [ 20%]
tests/unit/test_tools.py ...................... [ 21%]
tests/unit/test_triton_inference.py .............................. [ 23%]
tests/unit/columns/test_column_schemas.py .............................. [ 25%]
.................................................. [ 29%]
tests/unit/columns/test_column_selector.py .................... [ 30%]
tests/unit/framework_utils/test_tf_feature_columns.py . [ 30%]
tests/unit/framework_utils/test_tf_layers.py ........................... [ 32%]
................................................... [ 35%]
tests/unit/framework_utils/test_torch_layers.py . [ 35%]
tests/unit/loader/test_dataloader_backend.py ..... [ 36%]
tests/unit/loader/test_tf_dataloader.py ................................ [ 38%]
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tests/unit/loader/test_torch_dataloader.py ............................. [ 43%]
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tests/unit/ops/test_column_similarity.py ........................ [ 48%]
tests/unit/ops/test_ops.py ............................................. [ 51%]
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tests/unit/ops/test_ops_schema.py ...................................... [ 80%]
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tests/unit/workflow/test_cpu_workflow.py ...... [ 91%]
tests/unit/workflow/test_workflow.py ................................... [ 93%]
.......................................................... [ 97%]
tests/unit/workflow/test_workflow_node.py ........... [ 98%]
tests/unit/workflow/test_workflow_ops.py .. [ 98%]
tests/unit/workflow/test_workflow_schemas.py ....................... [100%]

=============================== warnings summary ===============================
tests/unit/test_dask_nvt.py: 3 warnings
tests/unit/test_io.py: 24 warnings
tests/unit/test_tf4rec.py: 2 warnings
tests/unit/test_tools.py: 2 warnings
tests/unit/test_triton_inference.py: 5 warnings
tests/unit/loader/test_dataloader_backend.py: 4 warnings
tests/unit/loader/test_tf_dataloader.py: 48 warnings
tests/unit/loader/test_torch_dataloader.py: 14 warnings
tests/unit/ops/test_column_similarity.py: 7 warnings
tests/unit/ops/test_ops.py: 74 warnings
tests/unit/workflow/test_workflow.py: 31 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
tests/unit/workflow/test_workflow_schemas.py: 1 warning
/var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg/numba/cuda/compiler.py:865: NumbaPerformanceWarning: �[1mGrid size (1) < 2 * SM count (112) will likely result in GPU under utilization due to low occupancy.�[0m
warn(NumbaPerformanceWarning(msg))

tests/unit/test_io.py::test_validate_dataset_bad_schema
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:1091: UserWarning: Unable to sample column dtypes to infer nvt.Dataset schema, schema is empty.
warnings.warn(

tests/unit/test_io.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/init.py:38: DeprecationWarning: ColumnGroup is deprecated, use ColumnSelector instead
warnings.warn("ColumnGroup is deprecated, use ColumnSelector instead", DeprecationWarning)

tests/unit/test_io.py: 24 warnings
tests/unit/loader/test_torch_dataloader.py: 54 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/node.py:47: FutureWarning: The ["a", "b", "c"] >> ops.Operator syntax for creating a ColumnGroup has been deprecated in NVTabular 21.09 and will be removed in a future version.
warnings.warn(

tests/unit/test_io.py: 36 warnings
tests/unit/workflow/test_workflow.py: 44 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/workflow.py:89: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for execution. Please use the client argument to initialize a Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 52 warnings
tests/unit/workflow/test_workflow.py: 35 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dask.py:372: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for this write operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 20 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:497: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler is being used for this shuffle operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.1]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:125: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[f"{col}_filled"] = df[col].isna()

tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-parquet-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-0.1]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.01]
tests/unit/ops/test_ops.py::test_fill_median[True-True-op_columns1-csv-no-header-0.1]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:126: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[col] = df[col].fillna(self.medians[col])

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
tests/unit/ops/test_ops.py::test_fill_missing[True-False-parquet]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/indexing.py:1637: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self._setitem_single_block(indexer, value, name)

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:54: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[f"{col}_filled"] = df[col].isna()

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/fill.py:55: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[col] = df[col].fillna(self.fill_val)

tests/unit/ops/test_ops.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:190: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[tmp] = _arange(len(df), like_df=df, dtype="int32")

tests/unit/ops/test_ops.py::test_join_external[True-True-left-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-left-device-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-device-pandas-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:171: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
_ext.drop_duplicates(ignore_index=True, inplace=True)

tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-False]
tests/unit/ops/test_ops.py::test_groupby_op[id-True]
tests/unit/ops/test_ops.py::test_groupby_op[id-False]
/var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/core.py:6610: UserWarning: Insufficient elements for head. 1 elements requested, only 0 elements available. Try passing larger npartitions to head.
warnings.warn(msg.format(n, len(r)))

tests/unit/workflow/test_cpu_workflow.py: 78 warnings
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/frame.py:3191: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self[k1] = value[k2]

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

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Branch BrPart Cover Missing

examples/multi-gpu-movielens/torch_trainer.py 65 0 6 1 99% 32->36
nvtabular/init.py 18 0 0 0 100%
nvtabular/columns/init.py 2 0 0 0 100%
nvtabular/columns/schema.py 213 20 107 23 87% 45->61, 48, 50, 52-55, 57, 67, 82, 98->109, 104, 147, 174, 260->267, 262, 263->265, 275, 291, 292->297, 295->297, 308, 332, 339, 348, 351, 356->355
nvtabular/columns/selector.py 74 1 34 0 99% 121
nvtabular/dispatch.py 258 44 126 22 81% 35-38, 43-45, 51-61, 68-69, 100, 119, 130, 136, 141->143, 154, 177-180, 219, 222, 228, 244, 251, 282->287, 285, 288, 291->295, 328, 339-342, 369-372, 402, 406, 447, 471, 473, 480
nvtabular/framework_utils/init.py 0 0 0 0 100%
nvtabular/framework_utils/tensorflow/init.py 1 0 0 0 100%
nvtabular/framework_utils/tensorflow/feature_column_utils.py 134 78 90 15 39% 30, 99, 103, 114-130, 140, 143-158, 162, 166-167, 173-198, 207-217, 220-227, 229->233, 234, 239-279, 282
nvtabular/framework_utils/tensorflow/layers/init.py 4 0 0 0 100%
nvtabular/framework_utils/tensorflow/layers/embedding.py 153 12 85 6 91% 60, 68->49, 122, 179, 231-239, 335->343, 357->360, 363-364, 367
nvtabular/framework_utils/tensorflow/layers/interaction.py 47 25 20 1 43% 49, 74-103, 106-110, 113
nvtabular/framework_utils/tensorflow/layers/outer_product.py 30 24 10 0 15% 37-38, 41-60, 71-84, 87
nvtabular/framework_utils/torch/init.py 0 0 0 0 100%
nvtabular/framework_utils/torch/layers/init.py 2 0 0 0 100%
nvtabular/framework_utils/torch/layers/embeddings.py 32 2 14 2 91% 50, 91
nvtabular/framework_utils/torch/models.py 45 1 28 4 93% 57->61, 87->89, 93->96, 103
nvtabular/framework_utils/torch/utils.py 75 5 30 5 90% 51->53, 64, 71->76, 75, 118-120
nvtabular/inference/init.py 0 0 0 0 100%
nvtabular/inference/triton/init.py 302 131 130 13 58% 82-86, 140-190, 235-279, 310, 336-344, 352-359, 378, 400-416, 457-461, 499-509, 533-555, 559-626, 633->636, 636->632, 672-682, 691, 701, 722, 729, 735->738, 739
nvtabular/inference/triton/benchmarking_tools.py 52 52 10 0 0% 2-103
nvtabular/inference/triton/data_conversions.py 87 3 58 4 95% 32-33, 84
nvtabular/inference/triton/model.py 176 176 98 0 0% 27-332
nvtabular/inference/triton/model_config_pb2.py 299 0 2 0 100%
nvtabular/io/init.py 4 0 0 0 100%
nvtabular/io/avro.py 88 88 30 0 0% 16-189
nvtabular/io/csv.py 57 6 20 5 86% 22-23, 99, 103->107, 108, 110, 124
nvtabular/io/dask.py 183 8 72 11 93% 111, 114, 150, 398, 408, 425->428, 436, 440->442, 442->438, 447, 449
nvtabular/io/dataframe_engine.py 61 5 28 6 88% 19-20, 50, 69, 88->92, 92->97, 94->97, 97->116, 125
nvtabular/io/dataset.py 349 45 162 29 84% 46-47, 250, 252, 265, 274, 292-306, 426->496, 431-434, 439->449, 444-445, 456->454, 470->474, 485, 496->505, 556-557, 558->562, 605, 727, 729, 731, 737, 741-743, 745, 805-806, 833, 840-841, 847, 853, 949-950, 1067-1072, 1078, 1166
nvtabular/io/dataset_engine.py 23 1 0 0 96% 45
nvtabular/io/hugectr.py 45 2 24 2 91% 34, 74->97, 101
nvtabular/io/parquet.py 492 25 156 15 94% 33-34, 88-89, 92-100, 124->126, 213-215, 338-343, 381-386, 502->509, 570->575, 576-577, 697, 701, 705, 711, 743, 760, 764, 771->773, 881->exit, 891->896, 901->911, 916, 938
nvtabular/io/shuffle.py 31 6 16 5 77% 42, 44-45, 49, 59, 63
nvtabular/io/writer.py 175 13 68 5 92% 24-25, 51, 79, 125, 128, 212, 221, 224, 267, 288-290
nvtabular/io/writer_factory.py 18 2 8 2 85% 35, 60
nvtabular/loader/init.py 0 0 0 0 100%
nvtabular/loader/backend.py 328 13 138 10 95% 128, 143-144, 235->237, 247-251, 297-298, 337->341, 412, 416-417, 447, 552, 560
nvtabular/loader/tensorflow.py 163 22 52 7 86% 58, 66-69, 84, 98, 308, 344, 359-361, 390-392, 402-410, 413-416
nvtabular/loader/tf_utils.py 55 10 20 5 80% 29->32, 32->34, 39->41, 43, 50-51, 58-60, 66-70
nvtabular/loader/torch.py 81 13 16 2 78% 25-27, 30-36, 111, 149-150
nvtabular/ops/init.py 21 0 0 0 100%
nvtabular/ops/bucketize.py 37 10 18 3 69% 53-55, 59->exit, 62-65, 84-87, 94
nvtabular/ops/categorify.py 603 66 332 47 86% 242, 244, 260, 264, 272, 280, 282, 309, 328-329, 347, 358->362, 366-373, 455-456, 481-482, 491, 554->550, 576->578, 676, 694, 730, 808-809, 824-828, 829->793, 847, 855, 862->exit, 886, 889->892, 944, 949, 965->969, 976-979, 990, 994, 996, 1003, 1008-1011, 1089, 1091, 1161->1184, 1167->1184, 1185-1190, 1227, 1246->1251, 1250, 1260->1257, 1265->1257, 1272, 1275, 1283-1293
nvtabular/ops/clip.py 18 2 6 3 79% 44, 52->54, 55
nvtabular/ops/column_similarity.py 118 25 38 5 74% 19-20, 78->exit, 108, 134, 198-199, 208-210, 218-234, 251->254, 255, 265
nvtabular/ops/data_stats.py 56 2 22 3 94% 91->93, 95, 97->87, 102
nvtabular/ops/difference_lag.py 31 1 8 1 95% 69->71, 94
nvtabular/ops/dropna.py 8 0 0 0 100%
nvtabular/ops/fill.py 91 12 36 3 82% 63-67, 93, 121, 147, 151, 162-165
nvtabular/ops/filter.py 20 1 6 1 92% 49
nvtabular/ops/groupby.py 119 3 70 4 96% 73, 84, 94->96, 106->111, 141
nvtabular/ops/hash_bucket.py 35 3 18 2 87% 72, 102, 108
nvtabular/ops/hashed_cross.py 36 4 15 3 86% 53, 66, 81, 91
nvtabular/ops/internal/init.py 3 0 0 0 100%
nvtabular/ops/internal/concat_columns.py 11 0 0 0 100%
nvtabular/ops/internal/identity.py 6 1 0 0 83% 42
nvtabular/ops/internal/subset_columns.py 13 1 0 0 92% 53
nvtabular/ops/join_external.py 89 7 36 6 90% 20-21, 113, 115, 117, 159, 176->178, 215
nvtabular/ops/join_groupby.py 101 7 36 4 92% 108, 115, 124, 131->130, 215-216, 219-220
nvtabular/ops/lambdaop.py 39 6 18 6 79% 59, 63, 77, 89, 94, 103
nvtabular/ops/list_slice.py 66 24 26 1 58% 21-22, 53-54, 104-118, 126-137
nvtabular/ops/logop.py 13 0 0 0 100%
nvtabular/ops/moments.py 65 0 20 0 100%
nvtabular/ops/normalize.py 81 10 14 1 86% 70, 78-79, 85, 118-119, 141-142, 146, 157
nvtabular/ops/operator.py 64 1 12 1 97% 111
nvtabular/ops/rename.py 41 3 22 3 90% 47, 88-90
nvtabular/ops/stat_operator.py 8 0 0 0 100%
nvtabular/ops/target_encoding.py 153 11 66 4 91% 167->171, 175->184, 232-233, 236-237, 249-255, 346->349, 362
nvtabular/tags.py 16 0 0 0 100%
nvtabular/tools/init.py 0 0 0 0 100%
nvtabular/tools/data_gen.py 236 1 62 1 99% 321
nvtabular/tools/dataset_inspector.py 50 7 18 1 79% 32-39
nvtabular/tools/inspector_script.py 46 46 0 0 0% 17-168
nvtabular/utils.py 102 43 46 8 52% 31-32, 36-37, 50, 61-62, 64-66, 69, 72, 78, 84, 90-126, 145, 149->153
nvtabular/worker.py 82 5 38 7 90% 24-25, 82->99, 91, 92->99, 99->102, 108, 110, 111->113
nvtabular/workflow/init.py 2 0 0 0 100%
nvtabular/workflow/node.py 229 18 110 10 89% 55, 93->98, 146, 248->252, 288, 302, 311, 329-334, 339, 388-389, 400->395, 439-444
nvtabular/workflow/workflow.py 221 15 112 7 93% 28-29, 47, 139, 195, 222-224, 332, 347-348, 366-367, 502, 514

TOTAL 7152 1168 2863 335 81%
Coverage XML written to file coverage.xml

Required test coverage of 70% reached. Total coverage: 81.31%
=========================== short test summary info ============================
SKIPPED [1] ../../../../../usr/local/lib/python3.8/dist-packages/dask_cudf/io/tests/test_s3.py:16: could not import 's3fs': No module named 's3fs'
SKIPPED [8] tests/unit/test_io.py:544: could not import 'uavro': No module named 'uavro'
SKIPPED [1] tests/unit/loader/test_tf_dataloader.py:521: not working correctly in ci environment
========= 1494 passed, 10 skipped, 778 warnings in 2247.06s (0:37:27) ==========
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/NVTabular/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[nvtabular_tests] $ /bin/bash /tmp/jenkins2070829114145527690.sh

@nvidia-merlin-bot
Copy link
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Click to view CI Results
GitHub pull request #1115 of commit ff40aebc2bf66a3cded664480ec196e65a58cc86, no merge conflicts.
Running as SYSTEM
Setting status of ff40aebc2bf66a3cded664480ec196e65a58cc86 to PENDING with url http://10.20.13.93:8080/job/nvtabular_tests/3446/ and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/nvtabular_tests
using credential nvidia-merlin-bot
Cloning the remote Git repository
Cloning repository https://github.com/NVIDIA/NVTabular.git
 > git init /var/jenkins_home/workspace/nvtabular_tests/nvtabular # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > 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/NVTabular.git +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/1115/*:refs/remotes/origin/pr/1115/* # timeout=10
 > git rev-parse ff40aebc2bf66a3cded664480ec196e65a58cc86^{commit} # timeout=10
Checking out Revision ff40aebc2bf66a3cded664480ec196e65a58cc86 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f ff40aebc2bf66a3cded664480ec196e65a58cc86 # timeout=10
Commit message: "removing unnecessary comment line"
 > git rev-list --no-walk 201bac7188be718086b32ef5a5d46ba3591f13c9 # timeout=10
[nvtabular_tests] $ /bin/bash /tmp/jenkins8166375316604754120.sh
Installing NVTabular
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: pip in /var/jenkins_home/.local/lib/python3.8/site-packages (21.2.4)
Requirement already satisfied: setuptools in /var/jenkins_home/.local/lib/python3.8/site-packages (58.0.4)
Requirement already satisfied: wheel in /var/jenkins_home/.local/lib/python3.8/site-packages (0.37.0)
Requirement already satisfied: pybind11 in /var/jenkins_home/.local/lib/python3.8/site-packages (2.7.1)
running develop
running egg_info
creating nvtabular.egg-info
writing nvtabular.egg-info/PKG-INFO
writing dependency_links to nvtabular.egg-info/dependency_links.txt
writing requirements to nvtabular.egg-info/requires.txt
writing top-level names to nvtabular.egg-info/top_level.txt
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*.h' under directory 'cpp'
warning: no files found matching '*.cu' under directory 'cpp'
warning: no files found matching '*.cuh' under directory 'cpp'
adding license file 'LICENSE'
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
running build_ext
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.8 -c flagcheck.cpp -o flagcheck.o -std=c++17
building 'nvtabular_cpp' extension
creating build
creating build/temp.linux-x86_64-3.8
creating build/temp.linux-x86_64-3.8/cpp
creating build/temp.linux-x86_64-3.8/cpp/nvtabular
creating build/temp.linux-x86_64-3.8/cpp/nvtabular/inference
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+57.gff40aeb -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+57.gff40aeb -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+57.gff40aeb -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/categorify.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+57.gff40aeb -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/fill.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -std=c++17 -fvisibility=hidden -g0
creating build/lib.linux-x86_64-3.8
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -o build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so
copying build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so -> 
Generating nvtabular/inference/triton/model_config_pb2.py from nvtabular/inference/triton/model_config.proto
Creating /var/jenkins_home/.local/lib/python3.8/site-packages/nvtabular.egg-link (link to .)
nvtabular 0.6.0+57.gff40aeb is already the active version in easy-install.pth

Installed /var/jenkins_home/workspace/nvtabular_tests/nvtabular
Processing dependencies for nvtabular==0.6.0+57.gff40aeb
Searching for protobuf==3.17.3
Best match: protobuf 3.17.3
Adding protobuf 3.17.3 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for tensorflow-metadata==1.2.0
Best match: tensorflow-metadata 1.2.0
Processing tensorflow_metadata-1.2.0-py3.8.egg
tensorflow-metadata 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow_metadata-1.2.0-py3.8.egg
Searching for pyarrow==4.0.1
Best match: pyarrow 4.0.1
Adding pyarrow 4.0.1 to easy-install.pth file
Installing plasma_store script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for tqdm==4.61.2
Best match: tqdm 4.61.2
Processing tqdm-4.61.2-py3.8.egg
tqdm 4.61.2 is already the active version in easy-install.pth
Installing tqdm script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tqdm-4.61.2-py3.8.egg
Searching for numba==0.54.0
Best match: numba 0.54.0
Processing numba-0.54.0-py3.8-linux-x86_64.egg
numba 0.54.0 is already the active version in easy-install.pth
Installing pycc script to /var/jenkins_home/.local/bin
Installing numba script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg
Searching for pandas==1.2.5
Best match: pandas 1.2.5
Processing pandas-1.2.5-py3.8-linux-x86_64.egg
pandas 1.2.5 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg
Searching for distributed==2021.4.1
Best match: distributed 2021.4.1
Processing distributed-2021.4.1-py3.8.egg
distributed 2021.4.1 is already the active version in easy-install.pth
Installing dask-ssh script to /var/jenkins_home/.local/bin
Installing dask-scheduler script to /var/jenkins_home/.local/bin
Installing dask-worker script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/distributed-2021.4.1-py3.8.egg
Searching for dask==2021.4.1
Best match: dask 2021.4.1
Processing dask-2021.4.1-py3.8.egg
dask 2021.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg
Searching for PyYAML==5.4.1
Best match: PyYAML 5.4.1
Processing PyYAML-5.4.1-py3.8-linux-x86_64.egg
PyYAML 5.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg
Searching for six==1.15.0
Best match: six 1.15.0
Adding six 1.15.0 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for googleapis-common-protos==1.53.0
Best match: googleapis-common-protos 1.53.0
Processing googleapis_common_protos-1.53.0-py3.8.egg
googleapis-common-protos 1.53.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/googleapis_common_protos-1.53.0-py3.8.egg
Searching for absl-py==0.12.0
Best match: absl-py 0.12.0
Processing absl_py-0.12.0-py3.8.egg
absl-py 0.12.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/absl_py-0.12.0-py3.8.egg
Searching for numpy==1.20.2
Best match: numpy 1.20.2
Adding numpy 1.20.2 to easy-install.pth file
Installing f2py script to /var/jenkins_home/.local/bin
Installing f2py3 script to /var/jenkins_home/.local/bin
Installing f2py3.8 script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for setuptools==58.0.4
Best match: setuptools 58.0.4
Adding setuptools 58.0.4 to easy-install.pth file

Using /var/jenkins_home/.local/lib/python3.8/site-packages
Searching for llvmlite==0.37.0
Best match: llvmlite 0.37.0
Processing llvmlite-0.37.0-py3.8-linux-x86_64.egg
llvmlite 0.37.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/llvmlite-0.37.0-py3.8-linux-x86_64.egg
Searching for pytz==2021.1
Best match: pytz 2021.1
Adding pytz 2021.1 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for python-dateutil==2.8.2
Best match: python-dateutil 2.8.2
Adding python-dateutil 2.8.2 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for zict==2.0.0
Best match: zict 2.0.0
Processing zict-2.0.0-py3.8.egg
zict 2.0.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg
Searching for tornado==6.1
Best match: tornado 6.1
Processing tornado-6.1-py3.8-linux-x86_64.egg
tornado 6.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tornado-6.1-py3.8-linux-x86_64.egg
Searching for toolz==0.11.1
Best match: toolz 0.11.1
Processing toolz-0.11.1-py3.8.egg
toolz 0.11.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/toolz-0.11.1-py3.8.egg
Searching for tblib==1.7.0
Best match: tblib 1.7.0
Processing tblib-1.7.0-py3.8.egg
tblib 1.7.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg
Searching for sortedcontainers==2.4.0
Best match: sortedcontainers 2.4.0
Processing sortedcontainers-2.4.0-py3.8.egg
sortedcontainers 2.4.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg
Searching for psutil==5.8.0
Best match: psutil 5.8.0
Processing psutil-5.8.0-py3.8-linux-x86_64.egg
psutil 5.8.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg
Searching for msgpack==1.0.2
Best match: msgpack 1.0.2
Processing msgpack-1.0.2-py3.8-linux-x86_64.egg
msgpack 1.0.2 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/msgpack-1.0.2-py3.8-linux-x86_64.egg
Searching for cloudpickle==1.6.0
Best match: cloudpickle 1.6.0
Processing cloudpickle-1.6.0-py3.8.egg
cloudpickle 1.6.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/cloudpickle-1.6.0-py3.8.egg
Searching for click==8.0.1
Best match: click 8.0.1
Processing click-8.0.1-py3.8.egg
click 8.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/click-8.0.1-py3.8.egg
Searching for partd==1.2.0
Best match: partd 1.2.0
Processing partd-1.2.0-py3.8.egg
partd 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg
Searching for fsspec==2021.8.1
Best match: fsspec 2021.8.1
Processing fsspec-2021.8.1-py3.8.egg
fsspec 2021.8.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/fsspec-2021.8.1-py3.8.egg
Searching for HeapDict==1.0.1
Best match: HeapDict 1.0.1
Processing HeapDict-1.0.1-py3.8.egg
HeapDict 1.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg
Searching for locket==0.2.1
Best match: locket 0.2.1
Processing locket-0.2.1-py3.8.egg
locket 0.2.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg
Finished processing dependencies for nvtabular==0.6.0+57.gff40aeb
Running black --check
All done! ✨ 🍰 ✨
125 files would be left unchanged.
Running flake8
Running isort
Skipped 2 files
Running bandit
Running pylint
************* Module nvtabular.ops.categorify
nvtabular/ops/categorify.py:485:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)
************* Module nvtabular.ops.fill
nvtabular/ops/fill.py:67:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)


Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

Running flake8-nb
Building docs
make: Entering directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
make: Leaving directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/nvtabular_tests/nvtabular, configfile: pyproject.toml
plugins: cov-2.12.1, forked-1.3.0, xdist-2.3.0
collected 1503 items / 1 skipped / 1502 selected

tests/unit/test_dask_nvt.py ............................................ [ 2%]
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tests/unit/test_io.py .................................................. [ 10%]
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.........ssssssss................................................. [ 20%]
tests/unit/test_notebooks.py ...... [ 20%]
tests/unit/test_tf4rec.py . [ 20%]
tests/unit/test_tools.py ...................... [ 21%]
tests/unit/test_triton_inference.py .............................. [ 23%]
tests/unit/columns/test_column_schemas.py .............................. [ 25%]
.................................................. [ 29%]
tests/unit/columns/test_column_selector.py .................... [ 30%]
tests/unit/framework_utils/test_tf_feature_columns.py . [ 30%]
tests/unit/framework_utils/test_tf_layers.py ........................... [ 32%]
................................................... [ 35%]
tests/unit/framework_utils/test_torch_layers.py . [ 35%]
tests/unit/loader/test_dataloader_backend.py ..... [ 36%]
tests/unit/loader/test_tf_dataloader.py ................................ [ 38%]
........................................s [ 41%]
tests/unit/loader/test_torch_dataloader.py ............................. [ 43%]
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tests/unit/ops/test_column_similarity.py ........................ [ 48%]
tests/unit/ops/test_ops.py ............................................. [ 51%]
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tests/unit/ops/test_ops_schema.py ...................................... [ 80%]
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tests/unit/workflow/test_cpu_workflow.py ...... [ 91%]
tests/unit/workflow/test_workflow.py ................................... [ 93%]
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tests/unit/workflow/test_workflow_node.py ........... [ 98%]
tests/unit/workflow/test_workflow_ops.py .. [ 98%]
tests/unit/workflow/test_workflow_schemas.py ....................... [100%]

=============================== warnings summary ===============================
tests/unit/test_dask_nvt.py: 3 warnings
tests/unit/test_io.py: 24 warnings
tests/unit/test_tf4rec.py: 2 warnings
tests/unit/test_tools.py: 2 warnings
tests/unit/test_triton_inference.py: 5 warnings
tests/unit/loader/test_dataloader_backend.py: 4 warnings
tests/unit/loader/test_tf_dataloader.py: 48 warnings
tests/unit/loader/test_torch_dataloader.py: 14 warnings
tests/unit/ops/test_column_similarity.py: 7 warnings
tests/unit/ops/test_ops.py: 74 warnings
tests/unit/workflow/test_workflow.py: 31 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
tests/unit/workflow/test_workflow_schemas.py: 1 warning
/var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg/numba/cuda/compiler.py:865: NumbaPerformanceWarning: �[1mGrid size (1) < 2 * SM count (112) will likely result in GPU under utilization due to low occupancy.�[0m
warn(NumbaPerformanceWarning(msg))

tests/unit/test_io.py::test_validate_dataset_bad_schema
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:1091: UserWarning: Unable to sample column dtypes to infer nvt.Dataset schema, schema is empty.
warnings.warn(

tests/unit/test_io.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/init.py:38: DeprecationWarning: ColumnGroup is deprecated, use ColumnSelector instead
warnings.warn("ColumnGroup is deprecated, use ColumnSelector instead", DeprecationWarning)

tests/unit/test_io.py: 24 warnings
tests/unit/loader/test_torch_dataloader.py: 54 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/node.py:47: FutureWarning: The ["a", "b", "c"] >> ops.Operator syntax for creating a ColumnGroup has been deprecated in NVTabular 21.09 and will be removed in a future version.
warnings.warn(

tests/unit/test_io.py: 36 warnings
tests/unit/workflow/test_workflow.py: 44 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/workflow.py:89: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for execution. Please use the client argument to initialize a Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 52 warnings
tests/unit/workflow/test_workflow.py: 35 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dask.py:372: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for this write operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 20 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:497: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler is being used for this shuffle operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/ops/test_column_similarity.py: 12 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/column_similarity.py:109: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[name] = similarities

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
tests/unit/ops/test_ops.py::test_fill_missing[True-False-parquet]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/indexing.py:1637: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self._setitem_single_block(indexer, value, name)

tests/unit/ops/test_ops.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:190: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[tmp] = _arange(len(df), like_df=df, dtype="int32")

tests/unit/ops/test_ops.py::test_join_external[True-True-left-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-left-device-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-device-pandas-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:171: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
_ext.drop_duplicates(ignore_index=True, inplace=True)

tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-False]
tests/unit/ops/test_ops.py::test_groupby_op[id-True]
tests/unit/ops/test_ops.py::test_groupby_op[id-False]
/var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/core.py:6610: UserWarning: Insufficient elements for head. 1 elements requested, only 0 elements available. Try passing larger npartitions to head.
warnings.warn(msg.format(n, len(r)))

tests/unit/workflow/test_cpu_workflow.py: 78 warnings
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/frame.py:3191: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self[k1] = value[k2]

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

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Branch BrPart Cover Missing

examples/multi-gpu-movielens/torch_trainer.py 65 0 6 1 99% 32->36
nvtabular/init.py 18 0 0 0 100%
nvtabular/columns/init.py 2 0 0 0 100%
nvtabular/columns/schema.py 213 20 107 23 87% 45->61, 48, 50, 52-55, 57, 67, 82, 98->109, 104, 147, 174, 260->267, 262, 263->265, 275, 291, 292->297, 295->297, 308, 332, 339, 348, 351, 356->355
nvtabular/columns/selector.py 74 1 34 0 99% 121
nvtabular/dispatch.py 258 44 126 22 81% 35-38, 43-45, 51-61, 68-69, 100, 119, 130, 136, 141->143, 154, 177-180, 219, 222, 228, 244, 251, 282->287, 285, 288, 291->295, 328, 339-342, 369-372, 402, 406, 447, 471, 473, 480
nvtabular/framework_utils/init.py 0 0 0 0 100%
nvtabular/framework_utils/tensorflow/init.py 1 0 0 0 100%
nvtabular/framework_utils/tensorflow/feature_column_utils.py 134 78 90 15 39% 30, 99, 103, 114-130, 140, 143-158, 162, 166-167, 173-198, 207-217, 220-227, 229->233, 234, 239-279, 282
nvtabular/framework_utils/tensorflow/layers/init.py 4 0 0 0 100%
nvtabular/framework_utils/tensorflow/layers/embedding.py 153 12 85 6 91% 60, 68->49, 122, 179, 231-239, 335->343, 357->360, 363-364, 367
nvtabular/framework_utils/tensorflow/layers/interaction.py 47 25 20 1 43% 49, 74-103, 106-110, 113
nvtabular/framework_utils/tensorflow/layers/outer_product.py 30 24 10 0 15% 37-38, 41-60, 71-84, 87
nvtabular/framework_utils/torch/init.py 0 0 0 0 100%
nvtabular/framework_utils/torch/layers/init.py 2 0 0 0 100%
nvtabular/framework_utils/torch/layers/embeddings.py 32 2 14 2 91% 50, 91
nvtabular/framework_utils/torch/models.py 45 1 28 4 93% 57->61, 87->89, 93->96, 103
nvtabular/framework_utils/torch/utils.py 75 5 30 5 90% 51->53, 64, 71->76, 75, 118-120
nvtabular/inference/init.py 0 0 0 0 100%
nvtabular/inference/triton/init.py 302 131 130 13 58% 82-86, 140-190, 235-279, 310, 336-344, 352-359, 378, 400-416, 457-461, 499-509, 533-555, 559-626, 633->636, 636->632, 672-682, 691, 701, 722, 729, 735->738, 739
nvtabular/inference/triton/benchmarking_tools.py 52 52 10 0 0% 2-103
nvtabular/inference/triton/data_conversions.py 87 3 58 4 95% 32-33, 84
nvtabular/inference/triton/model.py 176 176 98 0 0% 27-332
nvtabular/inference/triton/model_config_pb2.py 299 0 2 0 100%
nvtabular/io/init.py 4 0 0 0 100%
nvtabular/io/avro.py 88 88 30 0 0% 16-189
nvtabular/io/csv.py 57 6 20 5 86% 22-23, 99, 103->107, 108, 110, 124
nvtabular/io/dask.py 183 8 72 11 93% 111, 114, 150, 398, 408, 425->428, 436, 440->442, 442->438, 447, 449
nvtabular/io/dataframe_engine.py 61 5 28 6 88% 19-20, 50, 69, 88->92, 92->97, 94->97, 97->116, 125
nvtabular/io/dataset.py 349 45 162 29 84% 46-47, 250, 252, 265, 274, 292-306, 426->496, 431-434, 439->449, 444-445, 456->454, 470->474, 485, 496->505, 556-557, 558->562, 605, 727, 729, 731, 737, 741-743, 745, 805-806, 833, 840-841, 847, 853, 949-950, 1067-1072, 1078, 1166
nvtabular/io/dataset_engine.py 23 1 0 0 96% 45
nvtabular/io/hugectr.py 45 2 24 2 91% 34, 74->97, 101
nvtabular/io/parquet.py 492 25 156 15 94% 33-34, 88-89, 92-100, 124->126, 213-215, 338-343, 381-386, 502->509, 570->575, 576-577, 697, 701, 705, 711, 743, 760, 764, 771->773, 881->exit, 891->896, 901->911, 916, 938
nvtabular/io/shuffle.py 31 6 16 5 77% 42, 44-45, 49, 59, 63
nvtabular/io/writer.py 175 13 68 5 92% 24-25, 51, 79, 125, 128, 212, 221, 224, 267, 288-290
nvtabular/io/writer_factory.py 18 2 8 2 85% 35, 60
nvtabular/loader/init.py 0 0 0 0 100%
nvtabular/loader/backend.py 328 13 138 10 95% 128, 143-144, 235->237, 247-251, 297-298, 337->341, 412, 416-417, 447, 552, 560
nvtabular/loader/tensorflow.py 163 22 52 7 86% 58, 66-69, 84, 98, 308, 344, 359-361, 390-392, 402-410, 413-416
nvtabular/loader/tf_utils.py 55 10 20 5 80% 29->32, 32->34, 39->41, 43, 50-51, 58-60, 66-70
nvtabular/loader/torch.py 81 13 16 2 78% 25-27, 30-36, 111, 149-150
nvtabular/ops/init.py 21 0 0 0 100%
nvtabular/ops/bucketize.py 37 10 18 3 69% 53-55, 59->exit, 62-65, 84-87, 94
nvtabular/ops/categorify.py 603 66 332 47 86% 242, 244, 260, 264, 272, 280, 282, 309, 328-329, 347, 358->362, 366-373, 455-456, 481-482, 491, 554->550, 576->578, 676, 694, 730, 808-809, 824-828, 829->793, 847, 855, 862->exit, 886, 889->892, 944, 949, 965->969, 976-979, 990, 994, 996, 1003, 1008-1011, 1089, 1091, 1161->1184, 1167->1184, 1185-1190, 1227, 1246->1251, 1250, 1260->1257, 1265->1257, 1272, 1275, 1283-1293
nvtabular/ops/clip.py 18 2 6 3 79% 44, 52->54, 55
nvtabular/ops/column_similarity.py 118 25 38 5 74% 19-20, 78->exit, 108, 134, 198-199, 208-210, 218-234, 251->254, 255, 265
nvtabular/ops/data_stats.py 56 2 22 3 94% 91->93, 95, 97->87, 102
nvtabular/ops/difference_lag.py 31 1 8 1 95% 69->71, 94
nvtabular/ops/dropna.py 8 0 0 0 100%
nvtabular/ops/fill.py 91 12 36 3 82% 63-67, 93, 121, 147, 151, 162-165
nvtabular/ops/filter.py 20 1 6 1 92% 49
nvtabular/ops/groupby.py 119 3 70 4 96% 73, 84, 94->96, 106->111, 141
nvtabular/ops/hash_bucket.py 35 3 18 2 87% 72, 102, 108
nvtabular/ops/hashed_cross.py 36 4 15 3 86% 53, 66, 81, 91
nvtabular/ops/internal/init.py 3 0 0 0 100%
nvtabular/ops/internal/concat_columns.py 11 0 0 0 100%
nvtabular/ops/internal/identity.py 6 1 0 0 83% 42
nvtabular/ops/internal/subset_columns.py 13 1 0 0 92% 53
nvtabular/ops/join_external.py 89 7 36 6 90% 20-21, 113, 115, 117, 159, 176->178, 215
nvtabular/ops/join_groupby.py 101 7 36 4 92% 108, 115, 124, 131->130, 215-216, 219-220
nvtabular/ops/lambdaop.py 39 6 18 6 79% 59, 63, 77, 89, 94, 103
nvtabular/ops/list_slice.py 66 24 26 1 58% 21-22, 53-54, 104-118, 126-137
nvtabular/ops/logop.py 13 0 0 0 100%
nvtabular/ops/moments.py 65 0 20 0 100%
nvtabular/ops/normalize.py 81 10 14 1 86% 70, 78-79, 85, 118-119, 141-142, 146, 157
nvtabular/ops/operator.py 64 1 12 1 97% 111
nvtabular/ops/rename.py 41 3 22 3 90% 47, 88-90
nvtabular/ops/stat_operator.py 8 0 0 0 100%
nvtabular/ops/target_encoding.py 153 11 66 4 91% 167->171, 175->184, 232-233, 236-237, 249-255, 346->349, 362
nvtabular/tags.py 16 0 0 0 100%
nvtabular/tools/init.py 0 0 0 0 100%
nvtabular/tools/data_gen.py 236 1 62 1 99% 321
nvtabular/tools/dataset_inspector.py 50 7 18 1 79% 32-39
nvtabular/tools/inspector_script.py 46 46 0 0 0% 17-168
nvtabular/utils.py 102 43 46 8 52% 31-32, 36-37, 50, 61-62, 64-66, 69, 72, 78, 84, 90-126, 145, 149->153
nvtabular/worker.py 82 5 38 7 90% 24-25, 82->99, 91, 92->99, 99->102, 108, 110, 111->113
nvtabular/workflow/init.py 2 0 0 0 100%
nvtabular/workflow/node.py 229 18 110 10 89% 55, 93->98, 146, 248->252, 288, 302, 311, 329-334, 339, 388-389, 400->395, 439-444
nvtabular/workflow/workflow.py 221 15 112 7 93% 28-29, 47, 139, 195, 222-224, 332, 347-348, 366-367, 502, 514

TOTAL 7152 1168 2863 335 81%
Coverage XML written to file coverage.xml

Required test coverage of 70% reached. Total coverage: 81.31%
=========================== short test summary info ============================
SKIPPED [1] ../../../../../usr/local/lib/python3.8/dist-packages/dask_cudf/io/tests/test_s3.py:16: could not import 's3fs': No module named 's3fs'
SKIPPED [8] tests/unit/test_io.py:544: could not import 'uavro': No module named 'uavro'
SKIPPED [1] tests/unit/loader/test_tf_dataloader.py:521: not working correctly in ci environment
========= 1494 passed, 10 skipped, 776 warnings in 2872.70s (0:47:52) ==========
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/NVTabular/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[nvtabular_tests] $ /bin/bash /tmp/jenkins4473635180736111959.sh

@benfred benfred merged commit 8e8a6f6 into NVIDIA-Merlin:main Sep 14, 2021
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GitHub pull request #1115 of commit 54bde8b1d60c9025b0f05a3e357155ff428be48e, no merge conflicts.
Running as SYSTEM
Building in workspace /var/jenkins_home/workspace/nvtabular_tests
using credential nvidia-merlin-bot
Cloning the remote Git repository
Cloning repository https://github.com/NVIDIA/NVTabular.git
 > git init /var/jenkins_home/workspace/nvtabular_tests/nvtabular # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > 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/NVTabular.git +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/1115/*:refs/remotes/origin/pr/1115/* # timeout=10
 > git rev-parse 54bde8b1d60c9025b0f05a3e357155ff428be48e^{commit} # timeout=10
Checking out Revision 54bde8b1d60c9025b0f05a3e357155ff428be48e (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 54bde8b1d60c9025b0f05a3e357155ff428be48e # timeout=10
Commit message: "Merge branch 'main' into select-by-tag"
 > git rev-list --no-walk f260df8f9ad927408e81ec1cd94f398d9f4e7321 # timeout=10
First time build. Skipping changelog.
[nvtabular_tests] $ /bin/bash /tmp/jenkins8602481822023104191.sh
Installing NVTabular
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: pip in /var/jenkins_home/.local/lib/python3.8/site-packages (21.2.4)
Requirement already satisfied: setuptools in /var/jenkins_home/.local/lib/python3.8/site-packages (58.0.4)
Requirement already satisfied: wheel in /var/jenkins_home/.local/lib/python3.8/site-packages (0.37.0)
Requirement already satisfied: pybind11 in /var/jenkins_home/.local/lib/python3.8/site-packages (2.7.1)
running develop
running egg_info
creating nvtabular.egg-info
writing nvtabular.egg-info/PKG-INFO
writing dependency_links to nvtabular.egg-info/dependency_links.txt
writing requirements to nvtabular.egg-info/requires.txt
writing top-level names to nvtabular.egg-info/top_level.txt
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*.h' under directory 'cpp'
warning: no files found matching '*.cu' under directory 'cpp'
warning: no files found matching '*.cuh' under directory 'cpp'
adding license file 'LICENSE'
writing manifest file 'nvtabular.egg-info/SOURCES.txt'
running build_ext
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.8 -c flagcheck.cpp -o flagcheck.o -std=c++17
building 'nvtabular_cpp' extension
creating build
creating build/temp.linux-x86_64-3.8
creating build/temp.linux-x86_64-3.8/cpp
creating build/temp.linux-x86_64-3.8/cpp/nvtabular
creating build/temp.linux-x86_64-3.8/cpp/nvtabular/inference
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+59.g54bde8b -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+59.g54bde8b -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/__init__.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+59.g54bde8b -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/categorify.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o -std=c++17 -fvisibility=hidden -g0
x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DVERSION_INFO=0.6.0+59.g54bde8b -I./cpp/ -I/var/jenkins_home/.local/lib/python3.8/site-packages/pybind11/include -I/usr/include/python3.8 -c cpp/nvtabular/inference/fill.cc -o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -std=c++17 -fvisibility=hidden -g0
creating build/lib.linux-x86_64-3.8
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.8/cpp/nvtabular/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/__init__.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/categorify.o build/temp.linux-x86_64-3.8/cpp/nvtabular/inference/fill.o -o build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so
copying build/lib.linux-x86_64-3.8/nvtabular_cpp.cpython-38-x86_64-linux-gnu.so -> 
Generating nvtabular/inference/triton/model_config_pb2.py from nvtabular/inference/triton/model_config.proto
Creating /var/jenkins_home/.local/lib/python3.8/site-packages/nvtabular.egg-link (link to .)
nvtabular 0.6.0+59.g54bde8b is already the active version in easy-install.pth

Installed /var/jenkins_home/workspace/nvtabular_tests/nvtabular
Processing dependencies for nvtabular==0.6.0+59.g54bde8b
Searching for protobuf==3.17.3
Best match: protobuf 3.17.3
Adding protobuf 3.17.3 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for tensorflow-metadata==1.2.0
Best match: tensorflow-metadata 1.2.0
Processing tensorflow_metadata-1.2.0-py3.8.egg
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Using /var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow_metadata-1.2.0-py3.8.egg
Searching for pyarrow==4.0.1
Best match: pyarrow 4.0.1
Adding pyarrow 4.0.1 to easy-install.pth file
Installing plasma_store script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for tqdm==4.61.2
Best match: tqdm 4.61.2
Processing tqdm-4.61.2-py3.8.egg
tqdm 4.61.2 is already the active version in easy-install.pth
Installing tqdm script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tqdm-4.61.2-py3.8.egg
Searching for numba==0.54.0
Best match: numba 0.54.0
Processing numba-0.54.0-py3.8-linux-x86_64.egg
numba 0.54.0 is already the active version in easy-install.pth
Installing pycc script to /var/jenkins_home/.local/bin
Installing numba script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg
Searching for pandas==1.2.5
Best match: pandas 1.2.5
Processing pandas-1.2.5-py3.8-linux-x86_64.egg
pandas 1.2.5 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg
Searching for distributed==2021.4.1
Best match: distributed 2021.4.1
Processing distributed-2021.4.1-py3.8.egg
distributed 2021.4.1 is already the active version in easy-install.pth
Installing dask-ssh script to /var/jenkins_home/.local/bin
Installing dask-scheduler script to /var/jenkins_home/.local/bin
Installing dask-worker script to /var/jenkins_home/.local/bin

Using /var/jenkins_home/.local/lib/python3.8/site-packages/distributed-2021.4.1-py3.8.egg
Searching for dask==2021.4.1
Best match: dask 2021.4.1
Processing dask-2021.4.1-py3.8.egg
dask 2021.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg
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Best match: PyYAML 5.4.1
Processing PyYAML-5.4.1-py3.8-linux-x86_64.egg
PyYAML 5.4.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg
Searching for six==1.15.0
Best match: six 1.15.0
Adding six 1.15.0 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for googleapis-common-protos==1.53.0
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Processing googleapis_common_protos-1.53.0-py3.8.egg
googleapis-common-protos 1.53.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/googleapis_common_protos-1.53.0-py3.8.egg
Searching for absl-py==0.12.0
Best match: absl-py 0.12.0
Processing absl_py-0.12.0-py3.8.egg
absl-py 0.12.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/absl_py-0.12.0-py3.8.egg
Searching for numpy==1.20.2
Best match: numpy 1.20.2
Adding numpy 1.20.2 to easy-install.pth file
Installing f2py script to /var/jenkins_home/.local/bin
Installing f2py3 script to /var/jenkins_home/.local/bin
Installing f2py3.8 script to /var/jenkins_home/.local/bin

Using /usr/local/lib/python3.8/dist-packages
Searching for setuptools==58.0.4
Best match: setuptools 58.0.4
Adding setuptools 58.0.4 to easy-install.pth file

Using /var/jenkins_home/.local/lib/python3.8/site-packages
Searching for llvmlite==0.37.0
Best match: llvmlite 0.37.0
Processing llvmlite-0.37.0-py3.8-linux-x86_64.egg
llvmlite 0.37.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/llvmlite-0.37.0-py3.8-linux-x86_64.egg
Searching for pytz==2021.1
Best match: pytz 2021.1
Adding pytz 2021.1 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for python-dateutil==2.8.2
Best match: python-dateutil 2.8.2
Adding python-dateutil 2.8.2 to easy-install.pth file

Using /usr/local/lib/python3.8/dist-packages
Searching for zict==2.0.0
Best match: zict 2.0.0
Processing zict-2.0.0-py3.8.egg
zict 2.0.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg
Searching for tornado==6.1
Best match: tornado 6.1
Processing tornado-6.1-py3.8-linux-x86_64.egg
tornado 6.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tornado-6.1-py3.8-linux-x86_64.egg
Searching for toolz==0.11.1
Best match: toolz 0.11.1
Processing toolz-0.11.1-py3.8.egg
toolz 0.11.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/toolz-0.11.1-py3.8.egg
Searching for tblib==1.7.0
Best match: tblib 1.7.0
Processing tblib-1.7.0-py3.8.egg
tblib 1.7.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg
Searching for sortedcontainers==2.4.0
Best match: sortedcontainers 2.4.0
Processing sortedcontainers-2.4.0-py3.8.egg
sortedcontainers 2.4.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg
Searching for psutil==5.8.0
Best match: psutil 5.8.0
Processing psutil-5.8.0-py3.8-linux-x86_64.egg
psutil 5.8.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg
Searching for msgpack==1.0.2
Best match: msgpack 1.0.2
Processing msgpack-1.0.2-py3.8-linux-x86_64.egg
msgpack 1.0.2 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/msgpack-1.0.2-py3.8-linux-x86_64.egg
Searching for cloudpickle==1.6.0
Best match: cloudpickle 1.6.0
Processing cloudpickle-1.6.0-py3.8.egg
cloudpickle 1.6.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/cloudpickle-1.6.0-py3.8.egg
Searching for click==8.0.1
Best match: click 8.0.1
Processing click-8.0.1-py3.8.egg
click 8.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/click-8.0.1-py3.8.egg
Searching for partd==1.2.0
Best match: partd 1.2.0
Processing partd-1.2.0-py3.8.egg
partd 1.2.0 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg
Searching for fsspec==2021.8.1
Best match: fsspec 2021.8.1
Processing fsspec-2021.8.1-py3.8.egg
fsspec 2021.8.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/fsspec-2021.8.1-py3.8.egg
Searching for HeapDict==1.0.1
Best match: HeapDict 1.0.1
Processing HeapDict-1.0.1-py3.8.egg
HeapDict 1.0.1 is already the active version in easy-install.pth

Using /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg
Searching for locket==0.2.1
Best match: locket 0.2.1
Processing locket-0.2.1-py3.8.egg
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Using /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg
Finished processing dependencies for nvtabular==0.6.0+59.g54bde8b
Running black --check
All done! ✨ 🍰 ✨
125 files would be left unchanged.
Running flake8
Running isort
Skipped 2 files
Running bandit
Running pylint
************* Module nvtabular.ops.categorify
nvtabular/ops/categorify.py:485:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)
************* Module nvtabular.ops.fill
nvtabular/ops/fill.py:67:15: I1101: Module 'nvtabular_cpp' has no 'inference' member, but source is unavailable. Consider adding this module to extension-pkg-allow-list if you want to perform analysis based on run-time introspection of living objects. (c-extension-no-member)


Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

Running flake8-nb
Building docs
make: Entering directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
/usr/local/lib/python3.8/dist-packages/recommonmark/parser.py:75: UserWarning: Container node skipped: type=document
warn("Container node skipped: type={0}".format(mdnode.t))
make: Leaving directory '/var/jenkins_home/workspace/nvtabular_tests/nvtabular/docs'
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/nvtabular_tests/nvtabular, configfile: pyproject.toml
plugins: cov-2.12.1, forked-1.3.0, xdist-2.3.0
collected 1503 items / 1 skipped / 1502 selected

tests/unit/test_dask_nvt.py ............................................ [ 2%]
..................................................................... [ 7%]
tests/unit/test_io.py .................................................. [ 10%]
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.........ssssssss................................................. [ 20%]
tests/unit/test_notebooks.py ...... [ 20%]
tests/unit/test_tf4rec.py . [ 20%]
tests/unit/test_tools.py ...................... [ 21%]
tests/unit/test_triton_inference.py .............................. [ 23%]
tests/unit/columns/test_column_schemas.py .............................. [ 25%]
.................................................. [ 29%]
tests/unit/columns/test_column_selector.py .................... [ 30%]
tests/unit/framework_utils/test_tf_feature_columns.py . [ 30%]
tests/unit/framework_utils/test_tf_layers.py F.......................... [ 32%]
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tests/unit/framework_utils/test_torch_layers.py . [ 35%]
tests/unit/loader/test_dataloader_backend.py ..... [ 36%]
tests/unit/loader/test_tf_dataloader.py ................................ [ 38%]
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tests/unit/loader/test_torch_dataloader.py ............................. [ 43%]
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tests/unit/ops/test_column_similarity.py ........................ [ 48%]
tests/unit/ops/test_ops.py ............................................. [ 51%]
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tests/unit/ops/test_ops_schema.py ...................................... [ 80%]
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tests/unit/workflow/test_cpu_workflow.py ...... [ 91%]
tests/unit/workflow/test_workflow.py ................................... [ 93%]
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tests/unit/workflow/test_workflow_node.py ........... [ 98%]
tests/unit/workflow/test_workflow_ops.py .. [ 98%]
tests/unit/workflow/test_workflow_schemas.py ....................... [100%]

=================================== FAILURES ===================================
____________________ test_dense_embedding_layer[sum-stack] _____________________

aggregation = 'stack', combiner = 'sum'

@pytest.mark.parametrize("aggregation", ["stack", "concat"])
@pytest.mark.parametrize("combiner", ["sum", "mean"])  # TODO: add sqrtn
def test_dense_embedding_layer(aggregation, combiner):
    raw_good_columns = get_good_feature_columns()
    scalar_numeric, vector_numeric, one_hot, multi_hot = raw_good_columns
    one_hot_embedding = tf.feature_column.indicator_column(one_hot)
    multi_hot_embedding = tf.feature_column.embedding_column(multi_hot, 8, combiner=combiner)

    # should raise ValueError if passed categorical columns
    with pytest.raises(ValueError):
        embedding_layer = layers.DenseFeatures(raw_good_columns, aggregation=aggregation)

    if aggregation == "stack":
        # can't pass numeric to stack aggregation unless dims are 1
        with pytest.raises(ValueError):
            embedding_layer = layers.DenseFeatures(
                [
                    scalar_numeric,
                    vector_numeric,
                    one_hot_embedding,
                    multi_hot_embedding,
                ],
                aggregation=aggregation,
            )
        # can't have mismatched dims with stack aggregation
        with pytest.raises(ValueError):
            embedding_layer = layers.DenseFeatures(
                [one_hot_embedding, multi_hot_embedding], aggregation=aggregation
            )

        # reset b embedding to have matching dims
        multi_hot_embedding = tf.feature_column.embedding_column(multi_hot, 100, combiner=combiner)
        cols = [one_hot_embedding, multi_hot_embedding]
    else:
        cols = [scalar_numeric, vector_numeric, one_hot_embedding, multi_hot_embedding]

    embedding_layer = layers.DenseFeatures(cols, aggregation=aggregation)
    inputs = {
        "scalar_continuous": tf.keras.Input(name="scalar_continuous", shape=(1,), dtype=tf.float32),
        "vector_continuous": tf.keras.Input(
            name="vector_continuous__values", shape=(1,), dtype=tf.float32
        ),
        "one_hot": tf.keras.Input(name="one_hot", shape=(1,), dtype=tf.int64),
        "multi_hot": (
            tf.keras.Input(name="multi_hot__values", shape=(1,), dtype=tf.int64),
            tf.keras.Input(name="multi_hot__nnzs", shape=(1,), dtype=tf.int64),
        ),
    }
    if aggregation == "stack":
        inputs.pop("scalar_continuous")
        inputs.pop("vector_continuous")

    output = embedding_layer(inputs)
    model = tf.keras.Model(inputs=inputs, outputs=output)
    model.compile("sgd", "mse")

    # TODO: check for out-of-range categorical behavior
    scalar = np.array([0.1, -0.2, 0.3], dtype=np.float32)
    vector = np.random.randn(3, 128).astype("float32")
    one_hot = np.array([44, 21, 32])
    multi_hot_values = np.array([0, 2, 1, 4, 1, 3, 1])
    multi_hot_nnzs = np.array([1, 2, 4])
    x = {
        "scalar_continuous": scalar[:, None],
        "vector_continuous": vector.flatten()[:, None],
        "one_hot": one_hot[:, None],
        "multi_hot": (multi_hot_values[:, None], multi_hot_nnzs[:, None]),
    }
    if aggregation == "stack":
        x.pop("scalar_continuous")
        x.pop("vector_continuous")

    multi_hot_embedding_table = embedding_layer.embedding_tables["multi_hot"].numpy()
    multi_hot_embedding_rows = _compute_expected_multi_hot(
        multi_hot_embedding_table, multi_hot_values, multi_hot_nnzs, combiner
    )

    # check that shape and values match up
    y_hat = model(x).numpy()
    assert y_hat.shape[0] == 3
    if aggregation == "stack":
        assert len(y_hat.shape) == 3
        # len of columns is 2 because of mh (vals, nnzs) struct
        assert y_hat.shape[1] == (len(x))
        assert y_hat.shape[2] == 100
      np.testing.assert_allclose(y_hat[:, 0], multi_hot_embedding_rows, rtol=1e-05)

E AssertionError:
E Not equal to tolerance rtol=1e-05, atol=0
E
E Mismatched elements: 1 / 300 (0.333%)
E Max absolute difference: 1.1920929e-07
E Max relative difference: 1.197275e-05
E x: array([[ 5.459625e-02, 1.931962e-01, 7.864931e-02, -7.575755e-02,
E 1.695274e-01, 8.539402e-03, -4.046920e-02, -1.502117e-01,
E 7.889244e-02, -1.869609e-02, 2.263088e-01, 1.033977e-01,...
E y: array([[ 5.459625e-02, 1.931962e-01, 7.864931e-02, -7.575755e-02,
E 1.695274e-01, 8.539402e-03, -4.046920e-02, -1.502117e-01,
E 7.889244e-02, -1.869609e-02, 2.263088e-01, 1.033977e-01,...

tests/unit/framework_utils/test_tf_layers.py:139: AssertionError
----------------------------- Captured stderr call -----------------------------
2021-09-14 23:40:39.829626: I tensorflow/core/platform/cpu_feature_guard.cc:142] 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.
2021-09-14 23:40:40.875220: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 1627 MB memory: -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0
2021-09-14 23:40:40.876538: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 15173 MB memory: -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0
=============================== warnings summary ===============================
tests/unit/test_dask_nvt.py: 3 warnings
tests/unit/test_io.py: 24 warnings
tests/unit/test_tf4rec.py: 2 warnings
tests/unit/test_tools.py: 2 warnings
tests/unit/test_triton_inference.py: 5 warnings
tests/unit/loader/test_dataloader_backend.py: 4 warnings
tests/unit/loader/test_tf_dataloader.py: 48 warnings
tests/unit/loader/test_torch_dataloader.py: 14 warnings
tests/unit/ops/test_column_similarity.py: 7 warnings
tests/unit/ops/test_ops.py: 74 warnings
tests/unit/workflow/test_workflow.py: 31 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
tests/unit/workflow/test_workflow_schemas.py: 1 warning
/var/jenkins_home/.local/lib/python3.8/site-packages/numba-0.54.0-py3.8-linux-x86_64.egg/numba/cuda/compiler.py:865: NumbaPerformanceWarning: �[1mGrid size (1) < 2 * SM count (112) will likely result in GPU under utilization due to low occupancy.�[0m
warn(NumbaPerformanceWarning(msg))

tests/unit/test_io.py::test_validate_dataset_bad_schema
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:1091: UserWarning: Unable to sample column dtypes to infer nvt.Dataset schema, schema is empty.
warnings.warn(

tests/unit/test_io.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/init.py:38: DeprecationWarning: ColumnGroup is deprecated, use ColumnSelector instead
warnings.warn("ColumnGroup is deprecated, use ColumnSelector instead", DeprecationWarning)

tests/unit/test_io.py: 24 warnings
tests/unit/loader/test_torch_dataloader.py: 54 warnings
tests/unit/workflow/test_workflow_node.py: 1 warning
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/node.py:47: FutureWarning: The ["a", "b", "c"] >> ops.Operator syntax for creating a ColumnGroup has been deprecated in NVTabular 21.09 and will be removed in a future version.
warnings.warn(

tests/unit/test_io.py: 36 warnings
tests/unit/workflow/test_workflow.py: 44 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/workflow/workflow.py:89: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for execution. Please use the client argument to initialize a Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 52 warnings
tests/unit/workflow/test_workflow.py: 35 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dask.py:372: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler will be used for this write operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/test_io.py: 20 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/io/dataset.py:497: UserWarning: A global dask.distributed client has been detected, but the single-threaded scheduler is being used for this shuffle operation. Please use the client argument to initialize a Dataset and/or Workflow object with distributed-execution enabled.
warnings.warn(

tests/unit/ops/test_ops.py::test_fill_missing[True-True-parquet]
tests/unit/ops/test_ops.py::test_fill_missing[True-False-parquet]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/indexing.py:1637: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self._setitem_single_block(indexer, value, name)

tests/unit/ops/test_ops.py: 96 warnings
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:190: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df[tmp] = _arange(len(df), like_df=df, dtype="int32")

tests/unit/ops/test_ops.py::test_join_external[True-True-left-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-left-device-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-host-pandas-parquet]
tests/unit/ops/test_ops.py::test_join_external[True-True-inner-device-pandas-parquet]
/var/jenkins_home/workspace/nvtabular_tests/nvtabular/nvtabular/ops/join_external.py:171: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
_ext.drop_duplicates(ignore_index=True, inplace=True)

tests/unit/ops/test_ops.py::test_filter[parquet-0.1-True]
tests/unit/ops/test_ops.py::test_filter[parquet-0.1-False]
tests/unit/ops/test_ops.py::test_groupby_op[id-True]
tests/unit/ops/test_ops.py::test_groupby_op[id-False]
/var/jenkins_home/.local/lib/python3.8/site-packages/dask-2021.4.1-py3.8.egg/dask/dataframe/core.py:6610: UserWarning: Insufficient elements for head. 1 elements requested, only 0 elements available. Try passing larger npartitions to head.
warnings.warn(msg.format(n, len(r)))

tests/unit/workflow/test_cpu_workflow.py: 78 warnings
/var/jenkins_home/.local/lib/python3.8/site-packages/pandas-1.2.5-py3.8-linux-x86_64.egg/pandas/core/frame.py:3191: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self[k1] = value[k2]

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

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Branch BrPart Cover Missing

examples/multi-gpu-movielens/torch_trainer.py 65 0 6 1 99% 32->36
nvtabular/init.py 18 0 0 0 100%
nvtabular/columns/init.py 2 0 0 0 100%
nvtabular/columns/schema.py 213 20 107 23 87% 45->61, 48, 50, 52-55, 57, 67, 82, 98->109, 104, 147, 174, 260->267, 262, 263->265, 275, 291, 292->297, 295->297, 308, 332, 339, 348, 351, 356->355
nvtabular/columns/selector.py 74 1 34 0 99% 121
nvtabular/dispatch.py 258 44 126 22 81% 35-38, 43-45, 51-61, 68-69, 100, 119, 130, 136, 141->143, 154, 177-180, 219, 222, 228, 244, 251, 282->287, 285, 288, 291->295, 328, 339-342, 369-372, 402, 406, 447, 471, 473, 480
nvtabular/framework_utils/init.py 0 0 0 0 100%
nvtabular/framework_utils/tensorflow/init.py 1 0 0 0 100%
nvtabular/framework_utils/tensorflow/feature_column_utils.py 134 78 90 15 39% 30, 99, 103, 114-130, 140, 143-158, 162, 166-167, 173-198, 207-217, 220-227, 229->233, 234, 239-279, 282
nvtabular/framework_utils/tensorflow/layers/init.py 4 0 0 0 100%
nvtabular/framework_utils/tensorflow/layers/embedding.py 153 12 85 6 91% 60, 68->49, 122, 179, 231-239, 335->343, 357->360, 363-364, 367
nvtabular/framework_utils/tensorflow/layers/interaction.py 47 25 20 1 43% 49, 74-103, 106-110, 113
nvtabular/framework_utils/tensorflow/layers/outer_product.py 30 24 10 0 15% 37-38, 41-60, 71-84, 87
nvtabular/framework_utils/torch/init.py 0 0 0 0 100%
nvtabular/framework_utils/torch/layers/init.py 2 0 0 0 100%
nvtabular/framework_utils/torch/layers/embeddings.py 32 2 14 2 91% 50, 91
nvtabular/framework_utils/torch/models.py 45 1 28 4 93% 57->61, 87->89, 93->96, 103
nvtabular/framework_utils/torch/utils.py 75 5 30 5 90% 51->53, 64, 71->76, 75, 118-120
nvtabular/inference/init.py 0 0 0 0 100%
nvtabular/inference/triton/init.py 302 131 130 13 58% 82-86, 140-190, 235-279, 310, 336-344, 352-359, 378, 400-416, 457-461, 499-509, 533-555, 559-626, 633->636, 636->632, 672-682, 691, 701, 722, 729, 735->738, 739
nvtabular/inference/triton/benchmarking_tools.py 52 52 10 0 0% 2-103
nvtabular/inference/triton/data_conversions.py 87 3 58 4 95% 32-33, 84
nvtabular/inference/triton/model.py 176 176 98 0 0% 27-332
nvtabular/inference/triton/model_config_pb2.py 299 0 2 0 100%
nvtabular/io/init.py 4 0 0 0 100%
nvtabular/io/avro.py 88 88 30 0 0% 16-189
nvtabular/io/csv.py 57 6 20 5 86% 22-23, 99, 103->107, 108, 110, 124
nvtabular/io/dask.py 183 8 72 11 93% 111, 114, 150, 398, 408, 425->428, 436, 440->442, 442->438, 447, 449
nvtabular/io/dataframe_engine.py 61 5 28 6 88% 19-20, 50, 69, 88->92, 92->97, 94->97, 97->116, 125
nvtabular/io/dataset.py 349 45 162 29 84% 46-47, 250, 252, 265, 274, 292-306, 426->496, 431-434, 439->449, 444-445, 456->454, 470->474, 485, 496->505, 556-557, 558->562, 605, 727, 729, 731, 737, 741-743, 745, 805-806, 833, 840-841, 847, 853, 949-950, 1067-1072, 1078, 1166
nvtabular/io/dataset_engine.py 23 1 0 0 96% 45
nvtabular/io/hugectr.py 45 2 24 2 91% 34, 74->97, 101
nvtabular/io/parquet.py 492 25 156 15 94% 33-34, 88-89, 92-100, 124->126, 213-215, 338-343, 381-386, 502->509, 570->575, 576-577, 697, 701, 705, 711, 743, 760, 764, 771->773, 881->exit, 891->896, 901->911, 916, 938
nvtabular/io/shuffle.py 31 6 16 5 77% 42, 44-45, 49, 59, 63
nvtabular/io/writer.py 175 13 68 5 92% 24-25, 51, 79, 125, 128, 212, 221, 224, 267, 288-290
nvtabular/io/writer_factory.py 18 2 8 2 85% 35, 60
nvtabular/loader/init.py 0 0 0 0 100%
nvtabular/loader/backend.py 328 13 138 10 95% 128, 143-144, 235->237, 247-251, 297-298, 337->341, 412, 416-417, 447, 552, 560
nvtabular/loader/tensorflow.py 163 22 52 7 86% 58, 66-69, 84, 98, 308, 344, 359-361, 390-392, 402-410, 413-416
nvtabular/loader/tf_utils.py 55 10 20 5 80% 29->32, 32->34, 39->41, 43, 50-51, 58-60, 66-70
nvtabular/loader/torch.py 81 13 16 2 78% 25-27, 30-36, 111, 149-150
nvtabular/ops/init.py 21 0 0 0 100%
nvtabular/ops/bucketize.py 37 10 18 3 69% 53-55, 59->exit, 62-65, 84-87, 94
nvtabular/ops/categorify.py 603 66 332 47 86% 242, 244, 260, 264, 272, 280, 282, 309, 328-329, 347, 358->362, 366-373, 455-456, 481-482, 491, 554->550, 576->578, 676, 694, 730, 808-809, 824-828, 829->793, 847, 855, 862->exit, 886, 889->892, 944, 949, 965->969, 976-979, 990, 994, 996, 1003, 1008-1011, 1089, 1091, 1161->1184, 1167->1184, 1185-1190, 1227, 1246->1251, 1250, 1260->1257, 1265->1257, 1272, 1275, 1283-1293
nvtabular/ops/clip.py 18 2 6 3 79% 44, 52->54, 55
nvtabular/ops/column_similarity.py 118 25 38 5 74% 19-20, 78->exit, 108, 134, 198-199, 208-210, 218-234, 251->254, 255, 265
nvtabular/ops/data_stats.py 56 2 22 3 94% 91->93, 95, 97->87, 102
nvtabular/ops/difference_lag.py 31 1 8 1 95% 69->71, 94
nvtabular/ops/dropna.py 8 0 0 0 100%
nvtabular/ops/fill.py 91 12 36 3 82% 63-67, 93, 121, 147, 151, 162-165
nvtabular/ops/filter.py 20 1 6 1 92% 49
nvtabular/ops/groupby.py 119 3 70 4 96% 73, 84, 94->96, 106->111, 141
nvtabular/ops/hash_bucket.py 35 3 18 2 87% 72, 102, 108
nvtabular/ops/hashed_cross.py 36 4 15 3 86% 53, 66, 81, 91
nvtabular/ops/internal/init.py 3 0 0 0 100%
nvtabular/ops/internal/concat_columns.py 11 0 0 0 100%
nvtabular/ops/internal/identity.py 6 1 0 0 83% 42
nvtabular/ops/internal/subset_columns.py 13 1 0 0 92% 53
nvtabular/ops/join_external.py 89 7 36 6 90% 20-21, 113, 115, 117, 159, 176->178, 215
nvtabular/ops/join_groupby.py 101 7 36 4 92% 108, 115, 124, 131->130, 215-216, 219-220
nvtabular/ops/lambdaop.py 39 6 18 6 79% 59, 63, 77, 89, 94, 103
nvtabular/ops/list_slice.py 66 24 26 1 58% 21-22, 53-54, 104-118, 126-137
nvtabular/ops/logop.py 13 0 0 0 100%
nvtabular/ops/moments.py 65 0 20 0 100%
nvtabular/ops/normalize.py 81 10 14 1 86% 70, 78-79, 85, 118-119, 141-142, 146, 157
nvtabular/ops/operator.py 64 1 12 1 97% 111
nvtabular/ops/rename.py 41 3 22 3 90% 47, 88-90
nvtabular/ops/stat_operator.py 8 0 0 0 100%
nvtabular/ops/target_encoding.py 153 11 66 4 91% 167->171, 175->184, 232-233, 236-237, 249-255, 346->349, 362
nvtabular/tags.py 16 0 0 0 100%
nvtabular/tools/init.py 0 0 0 0 100%
nvtabular/tools/data_gen.py 236 1 62 1 99% 321
nvtabular/tools/dataset_inspector.py 50 7 18 1 79% 32-39
nvtabular/tools/inspector_script.py 46 46 0 0 0% 17-168
nvtabular/utils.py 102 43 46 8 52% 31-32, 36-37, 50, 61-62, 64-66, 69, 72, 78, 84, 90-126, 145, 149->153
nvtabular/worker.py 82 5 38 7 90% 24-25, 82->99, 91, 92->99, 99->102, 108, 110, 111->113
nvtabular/workflow/init.py 2 0 0 0 100%
nvtabular/workflow/node.py 229 18 110 10 89% 55, 93->98, 146, 248->252, 288, 302, 311, 329-334, 339, 388-389, 400->395, 439-444
nvtabular/workflow/workflow.py 221 15 112 7 93% 28-29, 47, 139, 195, 222-224, 332, 347-348, 366-367, 502, 514

TOTAL 7152 1168 2863 335 81%
Coverage XML written to file coverage.xml

Required test coverage of 70% reached. Total coverage: 81.31%
=========================== short test summary info ============================
SKIPPED [1] ../../../../../usr/local/lib/python3.8/dist-packages/dask_cudf/io/tests/test_s3.py:16: could not import 's3fs': No module named 's3fs'
SKIPPED [8] tests/unit/test_io.py:544: could not import 'uavro': No module named 'uavro'
SKIPPED [1] tests/unit/loader/test_tf_dataloader.py:521: not working correctly in ci environment
==== 1 failed, 1493 passed, 10 skipped, 764 warnings in 2597.96s (0:43:17) =====
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/NVTabular/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[nvtabular_tests] $ /bin/bash /tmp/jenkins9209267422391190166.sh

@benfred benfred linked an issue Sep 15, 2021 that may be closed by this pull request
mikemckiernan pushed a commit that referenced this pull request Nov 24, 2022
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Add column tagging API to NVTabular
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