Tensorflow-estimator

Changes

* Use `tf.compat.v1.estimator.inputs` instead of `tf.estimator.inputs`
* Replace `contrib` references with `tf.estimator.experimental.*` for APIs in `early_stopping.py`
* Determining the “correct” value of the `--iterations_per_loop` for TPUEstimator or DistributionStrategy continues to be a challenge for our users. We propose dynamically tuning the `--iterations_per_loop` variable, specifically for using TPUEstimator in training mode, based on a user target TPU execution time. Users might specify a value such as: `--iterations_per_loop=300s`, which will result in roughly 300 seconds being spent on the TPU between host side operations.

Thanks to our Contributors

This release contains contributions from many people at Google.

Changes

* Use `tf.compat.v1.estimator.inputs` instead of `tf.estimator.inputs`
* Replace `contrib` references with `tf.estimator.experimental.*` for APIs in `early_stopping.py`
* Determining the “correct” value of the `--iterations_per_loop` for TPUEstimator or DistributionStrategy continues to be a challenge for our users. We propose dynamically tuning the `--iterations_per_loop` variable, specifically for using TPUEstimator in training mode, based on a user target TPU execution time. Users might specify a value such as: `--iterations_per_loop=300s`, which will result in roughly 300 seconds being spent on the TPU between host side operations.

Thanks to our Contributors

This release contains contributions from many people at Google.

Changes

* Replace all occurences of `tf.contrib.estimator.BaselineEstimator` with `tf.estimator.BaselineEstimator`
* Replace all occurences of `tf.contrib.estimator.DNNLinearCombinedEstimator` with `tf.estimator.DNNLinearCombinedEstimator`
* Replace all occurrences of `tf.contrib.estimator.DNNEstimator` with `tf.estimator.DNNEstimator`
* Replace all occurrences of `tf.contrib.estimator.LinearEstimator` with `tf.estimator.LinearEstimator`
* Users of `tf.contrib.estimator.export_all_saved_models` and related should switch to `tf.estimator.Estimator.experimental_export_all_saved_models`.
* Update `regression_head` to head API for Canned Estimator V2.
* Update `multi_class_head` to head API for Canned Estimator V2.
* Replace all occurences of `tf.contrib.estimator.InMemoryEvaluatorHook` and `tf.contrib.estimator.make_stop_at_checkpoint_step_hook` with `tf.estimator.experimental.InMemoryEvaluatorHook` and `tf.estimator.experimental.make_stop_at_checkpoint_step_hook`
* Migrate linear optimizer from contrib to core.

Thanks to our Contributors

This release contains contributions from many people at Google.

Changes

* Replace all occurences of `tf.contrib.estimator.BaselineEstimator` with `tf.estimator.BaselineEstimator`
* Replace all occurences of `tf.contrib.estimator.DNNLinearCombinedEstimator` with `tf.estimator.DNNLinearCombinedEstimator`
* Replace all occurrences of `tf.contrib.estimator.DNNEstimator` with `tf.estimator.DNNEstimator`
* Replace all occurrences of `tf.contrib.estimator.LinearEstimator` with `tf.estimator.LinearEstimator`
* Users of `tf.contrib.estimator.export_all_saved_models` and related should switch to `tf.estimator.Estimator.experimental_export_all_saved_models`.
* Update `regression_head` to head API for Canned Estimator V2.
* Update `multi_class_head` to head API for Canned Estimator V2.
* Replace all occurences of `tf.contrib.estimator.InMemoryEvaluatorHook` and `tf.contrib.estimator.make_stop_at_checkpoint_step_hook` with `tf.estimator.experimental.InMemoryEvaluatorHook` and `tf.estimator.experimental.make_stop_at_checkpoint_step_hook`
* Migrate linear optimizer from contrib to core.

Thanks to our Contributors

This release contains contributions from many people at Google.