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prepare release v0.1.0
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CHANGELOG.md

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# Changelog
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## v0.1.0 (2019-05-22)
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### Bug fixes and other changes
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* skip setup on second remote run
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* add setup file back
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* add branch name to remote gpu test run command
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* remove setup file in release build gpu test
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* ignore coverage in release build tests
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* use tar file name as framework_support_installable in build_all.py
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* Add release build
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* Explicitly set lower-bound for botocore version
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* Pull request to test codebuild trigger on TensorFlow script mode
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* Update integ test for checking Python version
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* Upgrade to TensorFlow 1.13.1
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* Add mpi4py to pip installs
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* Add SageMaker integ test for hyperparameter tuning model_dir logic
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* Add Horovod benchmark
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* Fix model_dir adjustment for hyperparameter tuning jobs
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* change model_dir to training job name if it is for tuning.
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* Tune test_s3_plugin test
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* Skip the s3_plugin test before new binary released
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* Add model saving warning at end of training
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* Specify region when creating S3 resource in integ tests
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* Fix instance_type fixture setup for tests
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* Read framework version from Python SDK for integ test default
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* Fix SageMaker Session handling in Horovod test
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* Configure encoding to be utf-8
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* Use the test argement framework_version in all tests
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* Fix broken test test_distributed_mnist_no_ps
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* Add S3 plugin tests
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* Skip horovod local CPU test in GPU instances
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* Add Horovod tests
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* Skip horovod integration tests
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* TensorFlow 1.12 and Horovod support
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* Deprecate get_marker. Use get_closest_marker instead
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* Force parameter server to run on CPU
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* Add python-dev and build-essential to Dockerfiles
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* Update script_mode_train_any_tf_script_in_sage_maker.ipynb
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* Skip keras local mode test on gpu and use random port for serving in the test
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* Fix Keras test
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* Create parameter server in different thread
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* Add Keras support
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* Fix broken unit tests
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* Unset CUDA_VISIBLE_DEVICES for worker processes
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* Disable GPU for parameter process
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* Set parameter process waiting to False
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* Update sagemaker containers
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* GPU fix
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* Set S3 environment variables
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* Add CI configuration files
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* Add distributed training support
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* Edited the tf script mode notebook
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* Add benchmarking script
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* Add Script Mode example
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* Add integration tests to run training jobs with sagemaker
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* Add tox.ini and configure coverage and flake runs
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* Scriptmode single machine training implementation
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* Update region in s3 boto client in serve
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* Update readme with instructions for 1.9.0 and above
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* Fix deserialization of dicts for json predict requests
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* Add dockerfile and update test for tensorflow 1.10.0
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* Support tensorflow 1.9.0
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* Add integ tests to verify that tensorflow in gpu-image can access gpu-devices.
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* train on 3 epochs for pipe mode test
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* Change error classes used by _default_input_fn() and _default_output_fn()
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* Changing assertion to check only existence
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* Install sagemaker-tensorflow from pypi. Add MKL environment variables for TF 1.8
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* get most recent saved model to export
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* pip install tensorflow 1.8 in 1.8 cpu image
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* install tensorflow extensions
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* upgrade cpu binaries in docker build
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* Force upgrade of the framework binaries to make sure the right binaries are installed.
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* Add Pillow to pip install list
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* Increase train steps for cifar distributed test to mitigate race condition
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* Add TensorFlow 1.8 dockerfiles
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* Add TensorFlow 1.7 dockerfiles
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* Explain how to download tf binaries from PyPI
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* Allow training without S3
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* Fix hyperparameter name for detecting a tuning job
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* Checkout v1.4.1 tag instead of r1.4 branch
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* Move processing of requirements file in.
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* Generate checkpoint path using TRAINING_JOB_NAME environment variable if needed
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* Wrap user-provided model_fn to pass arguments positionally (maintains compatibility with existing behavior)
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* Add more unit tests for trainer, fix __all__ and rename train.py to avoid import conflict
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* Use regional endpoint for S3 client
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* Update README.rst
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* Pass input_channels to eval_input_fn if defined
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* Fix setup.py to refer to renamed README
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* Add test and build instructions
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* Fix year in license headers
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* Add TensorFlow 1.6
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* Add test instructions in README
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* Add container support to install_requires
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* Add Apache license headers
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* Use wget to install tensorflow-model-server
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* Fix file path for integ test
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* Fix s3_prefix path in integ test
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* Fix typo in path for integ test
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* Add input_channels to train_input_fn interface.
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* Update logging and make serving_input_fn optional.
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* remove pip install in tensorflow training
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* Modify integration tests to run nvidia-docker for gpu
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* add h5py for keras models
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* Add local integ tests & resources
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* Restructure repo to use a directory per TF version for dockerfiles
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* Rename "feature_map" variables to "feature_dict" to avoid overloading it with the ML term "feature map"
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* Copying in changes from internal repo:
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* Add functional test
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* Fix FROM image names for final build dockerfiles
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* Add dockerfiles for building our production images (TF 1.4)
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* GPU Dockerfile and setup.py fixes
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* Add base image Dockerfiles for 1.4
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* Merge pull request #1 from aws/mvs-first-commit
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* first commit
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* Updating initial README.md from template
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* Creating initial file from template
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* Creating initial file from template
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* Creating initial file from template
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* Creating initial file from template
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* Creating initial file from template
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* Initial commit
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VERSION

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2.0.1.dev0
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0.1.0

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