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change: move script mode branch to master (#234)
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mvsusp authored Sep 19, 2019
1 parent c8963f3 commit 12fd7ef
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20 changes: 20 additions & 0 deletions .coveragerc_py27
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[run]
branch = True
timid = True

[report]
exclude_lines =
pragma: no cover
pragma: py2 no cover
if six.PY3
elif six.PY3

partial_branches =
pragma: no cover
pragma: py2 no cover
if six.PY3
elif six.PY3

show_missing = True

fail_under = 75
20 changes: 20 additions & 0 deletions .coveragerc_py36
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[run]
branch = True
timid = True

[report]
exclude_lines =
pragma: no cover
pragma: py3 no cover
if six.PY2
elif six.PY2

partial_branches =
pragma: no cover
pragma: py3 no cover
if six.PY3
elif six.PY3

show_missing = True

fail_under = 90
3 changes: 3 additions & 0 deletions .flake8
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[flake8]
application_import_names = sagemaker_tensorflow_container, test, timeout, utils
import-order-style = google
6 changes: 5 additions & 1 deletion .gitignore
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Expand Up @@ -3,4 +3,8 @@ dist
**/*.egg-info
.DS_Store
.idea/
*.iml
*.iml
**/.ipynb_checkpoints
**/.python-version
.tox
*~
295 changes: 295 additions & 0 deletions CHANGELOG.md
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# Changelog

## v2.0.7 (2019-08-15)

### Bug fixes and other changes

* update no-p2 and no-p3 regions.

## v2.0.6 (2019-08-01)

### Bug fixes and other changes

* fix horovod mnist script

## v2.0.5 (2019-06-17)

### Bug fixes and other changes

* bump sagemaker-containers version to 2.4.10
* add hyperparameter tuning test

## v2.0.4 (2019-06-06)

### Bug fixes and other changes

* fix integ test errors when running with py2

## v2.0.3 (2019-06-06)

### Bug fixes and other changes

* only run one test during deployment

## v2.0.2 (2019-06-04)

### Bug fixes and other changes

* resolve pluggy version conflict

## v2.0.1 (2019-06-03)

### Bug fixes and other changes

* remove non-ascii character in CHANGELOG
* remove extra comma in buildspec-release.yml

## v2.0.0 (2019-06-03)

### Bug fixes and other changes

* Parameterize processor and py_version for test runs
* use unique name for integration job hyperparameter tuning job
* fix flake8 errors and add flake8 run in buildspec.yml
* skip gpu SageMaker test in regions with limited amount of p2/3 instances
* skip setup on second remote run
* add setup file back
* add branch name to remote gpu test run command
* remove setup file in release build gpu test
* ignore coverage in release build tests
* use tar file name as framework_support_installable in build_all.py
* Add release build
* Explicitly set lower-bound for botocore version
* Pull request to test codebuild trigger on TensorFlow script mode
* Update integ test for checking Python version
* Upgrade to TensorFlow 1.13.1
* Add mpi4py to pip installs
* Add SageMaker integ test for hyperparameter tuning model_dir logic
* Add Horovod benchmark
* Fix model_dir adjustment for hyperparameter tuning jobs
* change model_dir to training job name if it is for tuning.
* Tune test_s3_plugin test
* Skip the s3_plugin test before new binary released
* Add model saving warning at end of training
* Specify region when creating S3 resource in integ tests
* Fix instance_type fixture setup for tests
* Read framework version from Python SDK for integ test default
* Fix SageMaker Session handling in Horovod test
* Configure encoding to be utf-8
* Use the test argement framework_version in all tests
* Fix broken test test_distributed_mnist_no_ps
* Add S3 plugin tests
* Skip horovod local CPU test in GPU instances
* Add Horovod tests
* Skip horovod integration tests
* TensorFlow 1.12 and Horovod support
* Deprecate get_marker. Use get_closest_marker instead
* Force parameter server to run on CPU
* Add python-dev and build-essential to Dockerfiles
* Update script_mode_train_any_tf_script_in_sage_maker.ipynb
* Skip keras local mode test on gpu and use random port for serving in the test
* Fix Keras test
* Create parameter server in different thread
* Add Keras support
* Fix broken unit tests
* Unset CUDA_VISIBLE_DEVICES for worker processes
* Disable GPU for parameter process
* Set parameter process waiting to False
* Update sagemaker containers
* GPU fix
* Set S3 environment variables
* Add CI configuration files
* Add distributed training support
* Edited the tf script mode notebook
* Add benchmarking script
* Add Script Mode example
* Add integration tests to run training jobs with sagemaker
* Add tox.ini and configure coverage and flake runs
* Scriptmode single machine training implementation
* Update region in s3 boto client in serve
* Update readme with instructions for 1.9.0 and above
* Fix deserialization of dicts for json predict requests
* Add dockerfile and update test for tensorflow 1.10.0
* Support tensorflow 1.9.0
* Add integ tests to verify that tensorflow in gpu-image can access gpu-devices.
* train on 3 epochs for pipe mode test
* Change error classes used by _default_input_fn() and _default_output_fn()
* Changing assertion to check only existence
* Install sagemaker-tensorflow from pypi. Add MKL environment variables for TF 1.8
* get most recent saved model to export
* pip install tensorflow 1.8 in 1.8 cpu image
* install tensorflow extensions
* upgrade cpu binaries in docker build
* Force upgrade of the framework binaries to make sure the right binaries are installed.
* Add Pillow to pip install list
* Increase train steps for cifar distributed test to mitigate race condition
* Add TensorFlow 1.8 dockerfiles
* Add TensorFlow 1.7 dockerfiles
* Explain how to download tf binaries from PyPI
* Allow training without S3
* Fix hyperparameter name for detecting a tuning job
* Checkout v1.4.1 tag instead of r1.4 branch
* Move processing of requirements file in.
* Generate checkpoint path using TRAINING_JOB_NAME environment variable if needed
* Wrap user-provided model_fn to pass arguments positionally (maintains compatibility with existing behavior)
* Add more unit tests for trainer, fix __all__ and rename train.py to avoid import conflict
* Use regional endpoint for S3 client
* Update README.rst
* Pass input_channels to eval_input_fn if defined
* Fix setup.py to refer to renamed README
* Add test and build instructions
* Fix year in license headers
* Add TensorFlow 1.6
* Add test instructions in README
* Add container support to install_requires
* Add Apache license headers
* Use wget to install tensorflow-model-server
* Fix file path for integ test
* Fix s3_prefix path in integ test
* Fix typo in path for integ test
* Add input_channels to train_input_fn interface.
* Update logging and make serving_input_fn optional.
* remove pip install in tensorflow training
* Modify integration tests to run nvidia-docker for gpu
* add h5py for keras models
* Add local integ tests & resources
* Restructure repo to use a directory per TF version for dockerfiles
* Rename "feature_map" variables to "feature_dict" to avoid overloading it with the ML term "feature map"
* Copying in changes from internal repo:
* Add functional test
* Fix FROM image names for final build dockerfiles
* Add dockerfiles for building our production images (TF 1.4)
* GPU Dockerfile and setup.py fixes
* Add base image Dockerfiles for 1.4
* Merge pull request #1 from aws/mvs-first-commit
* first commit
* Updating initial README.md from template
* Creating initial file from template
* Creating initial file from template
* Creating initial file from template
* Creating initial file from template
* Creating initial file from template
* Initial commit

## v0.1.0 (2019-05-22)

### Bug fixes and other changes

* skip setup on second remote run
* add setup file back
* add branch name to remote gpu test run command
* remove setup file in release build gpu test
* ignore coverage in release build tests
* use tar file name as framework_support_installable in build_all.py
* Add release build
* Explicitly set lower-bound for botocore version
* Pull request to test codebuild trigger on TensorFlow script mode
* Update integ test for checking Python version
* Upgrade to TensorFlow 1.13.1
* Add mpi4py to pip installs
* Add SageMaker integ test for hyperparameter tuning model_dir logic
* Add Horovod benchmark
* Fix model_dir adjustment for hyperparameter tuning jobs
* change model_dir to training job name if it is for tuning.
* Tune test_s3_plugin test
* Skip the s3_plugin test before new binary released
* Add model saving warning at end of training
* Specify region when creating S3 resource in integ tests
* Fix instance_type fixture setup for tests
* Read framework version from Python SDK for integ test default
* Fix SageMaker Session handling in Horovod test
* Configure encoding to be utf-8
* Use the test argement framework_version in all tests
* Fix broken test test_distributed_mnist_no_ps
* Add S3 plugin tests
* Skip horovod local CPU test in GPU instances
* Add Horovod tests
* Skip horovod integration tests
* TensorFlow 1.12 and Horovod support
* Deprecate get_marker. Use get_closest_marker instead
* Force parameter server to run on CPU
* Add python-dev and build-essential to Dockerfiles
* Update script_mode_train_any_tf_script_in_sage_maker.ipynb
* Skip keras local mode test on gpu and use random port for serving in the test
* Fix Keras test
* Create parameter server in different thread
* Add Keras support
* Fix broken unit tests
* Unset CUDA_VISIBLE_DEVICES for worker processes
* Disable GPU for parameter process
* Set parameter process waiting to False
* Update sagemaker containers
* GPU fix
* Set S3 environment variables
* Add CI configuration files
* Add distributed training support
* Edited the tf script mode notebook
* Add benchmarking script
* Add Script Mode example
* Add integration tests to run training jobs with sagemaker
* Add tox.ini and configure coverage and flake runs
* Scriptmode single machine training implementation
* Update region in s3 boto client in serve
* Update readme with instructions for 1.9.0 and above
* Fix deserialization of dicts for json predict requests
* Add dockerfile and update test for tensorflow 1.10.0
* Support tensorflow 1.9.0
* Add integ tests to verify that tensorflow in gpu-image can access gpu-devices.
* train on 3 epochs for pipe mode test
* Change error classes used by _default_input_fn() and _default_output_fn()
* Changing assertion to check only existence
* Install sagemaker-tensorflow from pypi. Add MKL environment variables for TF 1.8
* get most recent saved model to export
* pip install tensorflow 1.8 in 1.8 cpu image
* install tensorflow extensions
* upgrade cpu binaries in docker build
* Force upgrade of the framework binaries to make sure the right binaries are installed.
* Add Pillow to pip install list
* Increase train steps for cifar distributed test to mitigate race condition
* Add TensorFlow 1.8 dockerfiles
* Add TensorFlow 1.7 dockerfiles
* Explain how to download tf binaries from PyPI
* Allow training without S3
* Fix hyperparameter name for detecting a tuning job
* Checkout v1.4.1 tag instead of r1.4 branch
* Move processing of requirements file in.
* Generate checkpoint path using TRAINING_JOB_NAME environment variable if needed
* Wrap user-provided model_fn to pass arguments positionally (maintains compatibility with existing behavior)
* Add more unit tests for trainer, fix __all__ and rename train.py to avoid import conflict
* Use regional endpoint for S3 client
* Update README.rst
* Pass input_channels to eval_input_fn if defined
* Fix setup.py to refer to renamed README
* Add test and build instructions
* Fix year in license headers
* Add TensorFlow 1.6
* Add test instructions in README
* Add container support to install_requires
* Add Apache license headers
* Use wget to install tensorflow-model-server
* Fix file path for integ test
* Fix s3_prefix path in integ test
* Fix typo in path for integ test
* Add input_channels to train_input_fn interface.
* Update logging and make serving_input_fn optional.
* remove pip install in tensorflow training
* Modify integration tests to run nvidia-docker for gpu
* add h5py for keras models
* Add local integ tests & resources
* Restructure repo to use a directory per TF version for dockerfiles
* Rename "feature_map" variables to "feature_dict" to avoid overloading it with the ML term "feature map"
* Copying in changes from internal repo:
* Add functional test
* Fix FROM image names for final build dockerfiles
* Add dockerfiles for building our production images (TF 1.4)
* GPU Dockerfile and setup.py fixes
* Add base image Dockerfiles for 1.4
* Merge pull request #1 from aws/mvs-first-commit
* first commit
* Updating initial README.md from template
* Creating initial file from template
* Creating initial file from template
* Creating initial file from template
* Creating initial file from template
* Creating initial file from template
* Initial commit
4 changes: 0 additions & 4 deletions CODE_OF_CONDUCT.md

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