Module: tf.estimator.experimental
Public API for tf.estimator.experimental namespace.
Classes
class InMemoryEvaluatorHook
: Hook to run evaluation in training without a checkpoint.
class KMeans
: An Estimator for K-Means clustering.
class LinearSDCA
: Stochastic Dual Coordinate Ascent helper for linear estimators.
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).
dnn_logit_fn_builder(...)
: Function builder for a dnn logit_fn.
linear_logit_fn_builder(...)
: Function builder for a linear logit_fn.
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/r1.15/api_docs/python/tf/estimator/experimental