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.
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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