tf.estimator.experimental.stop_if_no_increase

TensorFlow 1 version

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Build a serving_input_receiver_fn expecting fed tf.Examples.

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Compat aliases for migration

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tf.compat.v1.estimator.export.build_parsing_serving_input_receiver_fn

tf.estimator.export.build_parsing_serving_input_receiver_fn(
    feature_spec, default_batch_size=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Estimators	TF Lattice Canned Estimators Shape Constraints with Tensorflow Lattice Preprocessing data with TensorFlow Transform

Creates a serving_input_receiver_fn that expects a serialized tf.Example fed into a string placeholder. The function parses the tf.Example according to the provided feature_spec, and returns all parsed Tensors as features.

Args
`feature_spec`	a dict of string to `VarLenFeature`/`FixedLenFeature`.
`default_batch_size`	the number of query examples expected per batch. Leave unset for variable batch size (recommended).

Returns
A serving_input_receiver_fn suitable for use in serving.

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tf.estimator / experimental / experimental.stop_if_no_increase_hook

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Used in the notebooks

Args

Returns