Current Version (Still in Development)

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Release 0.1.7

cloud_fit uses pickle instead of cloudpickle.
Better integration tests checking for job status.
Small bug fixes.

Release 0.1.6

New module CloudTuner - Implementation of a library for hyperparameter tuning that is built into the KerasTuner and creates a seamless integration with Cloud AI Platform Optimizer as a backend to get suggestions of hyperparameters and run trials.
New application Monitoring - TensorFlow extension that exports its metrics to Stackdriver backend, allowing users to monitor the training and inference jobs in real time.
New experimental project cloud_fit - an experimental module that enables training keras models on Cloud AI Platform Training by serializing the model, and datasets for remote execution.
Small bug fixes.

Release 0.1.5

Restructuring of source code for new projects
Multi-file code example
Integration test example
Small bug fixes

Release 0.1.4

New API remote() to detect if currently in a remote cloud env.
CI using Github Action.
Updated README.
Some minor bug fixes.

Release 0.1.3

New features * Support for single node Keras tuner workflow. * Support for TPU training.

Fixes * Fixed docker build decode errors. * Default to Py3 for TF docker images.

Others * New colab notebook example. * New Auto Keras example. * Improved ReadMe docs. * Improved error messages.

Release 0.1.2

Support for passing colab notebook as entry_point.
Support for cloud docker build and colab workflow.
Support for log streaming in colab

Release 0.1.1

Detailed README with setup instructions and examples
Support for running run API from within a python script which contains a Keras model

Release 0.1.0

First release * Initial release with support for running a python script on GCP

Examples for basic workflows in Keras