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