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Module: tf.estimator.experimental

Public API for tf.estimator.experimental namespace.

Classes

class InMemoryEvaluatorHook: Hook to run evaluation in training without a checkpoint.

class LinearSDCA: Stochastic Dual Coordinate Ascent helper for linear estimators.

class RNNClassifier: A classifier for TensorFlow RNN models.

class RNNEstimator: An Estimator for TensorFlow RNN models with user-specified head.

Functions

build_raw_supervised_input_receiver_fn(...): Build a supervised_input_receiver_fn for raw features and labels.

call_logit_fn(...): Calls logit_fn (experimental).

make_early_stopping_hook(...): Creates early-stopping hook.

make_stop_at_checkpoint_step_hook(...): Creates a proper StopAtCheckpointStepHook based on chief status.

stop_if_higher_hook(...): Creates hook to stop if the given metric is higher than the threshold.

stop_if_lower_hook(...): Creates hook to stop if the given metric is lower than the threshold.

stop_if_no_decrease_hook(...): Creates hook to stop if metric does not decrease within given max steps.

stop_if_no_increase_hook(...): Creates hook to stop if metric does not increase within given max steps.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/estimator/experimental