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tf.data.Options

TensorFlow 2.0 version View source on GitHub

Class Options

Represents options for tf.data.Dataset.

Aliases:

  • Class tf.compat.v1.data.Options
  • Class tf.compat.v2.data.Options

An Options object can be, for instance, used to control which static optimizations to apply or whether to use performance modeling to dynamically tune the parallelism of operations such as tf.data.Dataset.map or tf.data.Dataset.interleave.

__init__

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__init__()

Properties

experimental_deterministic

Whether the outputs need to be produced in deterministic order. If None, defaults to True.

experimental_distribute

The distribution options associated with the dataset. See tf.data.experimental.DistributeOptions for more details.

experimental_optimization

The optimization options associated with the dataset. See tf.data.experimental.OptimizationOptions for more details.

experimental_slack

Whether to introduce 'slack' in the last prefetch of the input pipeline, if it exists. This may reduce CPU contention with accelerator host-side activity at the start of a step. The slack frequency is determined by the number of devices attached to this input pipeline. If None, defaults to False.

experimental_stats

The statistics options associated with the dataset. See tf.data.experimental.StatsOptions for more details.

experimental_threading

The threading options associated with the dataset. See tf.data.experimental.ThreadingOptions for more details.

Methods

__eq__

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__eq__(other)

__ne__

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__ne__(other)

merge

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merge(options)

Merges itself with the given tf.data.Options.

The given tf.data.Options can be merged as long as there does not exist an attribute that is set to different values in self and options.

Args:

Raises:

Returns:

New tf.data.Options() object which is the result of merging self with the input tf.data.Options.