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Officially support AdaNet on TPU using adanet.TPUEstimator with adanet.Estimator feature parity.
Support dictionary candidate pools in adanet.AutoEnsembleEstimator constructor to specify human-readable candidate names.
Improve AutoEnsembleEstimator ability to handling custom tf.estimator.Estimator subclasses.
Introduce adanet.ensemble which contains interfaces and examples of ways to learn ensembles using AdaNet. Users can now extend AdaNet to use custom ensemble-learning methods.
Record TensorBoard scalar, image, histogram, and audio summaries on TPU during training.
Add debug mode to help detect NaNs and Infs during training.
Improve subnetwork tf.train.SessionRunHook support to handle more edge cases.
Maintain compatibility with TensorFlow versions 1.9 thru 1.13 Only works for TensorFlow version >=1.13. Fixed in AdaNet v0.6.1.
Improve documentation including adding 'Getting Started' documentation to adanet.readthedocs.io.
BREAKING CHANGE: Importing the adanet.subnetwork package using from adanet.core import subnetwork will no longer work, because the package was moved to the adanet/subnetwork directory. Most users should already be using adanet.subnetwork or from adanet import subnetwork, and should not be affected.