fix: flip master to script mode

.coveragerc_py27

@@ -0,0 +1,20 @@
+[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

.coveragerc_py36

@@ -0,0 +1,20 @@
+[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

.flake8

@@ -0,0 +1,3 @@
+[flake8]
+application_import_names = sagemaker_tensorflow_container, test, timeout, utils
+import-order-style = google

.gitignore

@@ -3,4 +3,8 @@ dist
 **/*.egg-info
 .DS_Store
 .idea/
-*.iml
+*.iml
+**/.ipynb_checkpoints
+**/.python-version
+.tox
+*~

CHANGELOG.md

@@ -0,0 +1,283 @@
+# Changelog
+
+## 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

MANIFEST.in

@@ -1,2 +1,3 @@
+include VERSION
 include LICENSE
 include README.md