tf.data.Options

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Represents options for tf.data.Dataset.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.data.Options

tf.data.Options()

An Options object can be, for instance, used to control which graph 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.

After constructing an Options object, use dataset.with_options(options) to apply the options to a dataset.

dataset = tf.data.Dataset.range(3)
options = tf.data.Options()
# Set options here.
dataset = dataset.with_options(options)

Attributes
experimental_deterministic	Whether the outputs need to be produced in deterministic order. If None, defaults to True.
experimental_distribute	The distribution strategy options associated with the dataset. See tf.data.experimental.DistributeOptions for more details.
experimental_external_state_policy	This option can be used to override the default policy for how to handle external state when serializing a dataset or checkpointing its iterator. There are three settings available - IGNORE: in which we completely ignore any state; WARN: We warn the user that some state might be thrown away; FAIL: We fail if any state is being captured.
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

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
options	a tf.data.Options to merge with

Raises
ValueError	if the given tf.data.Options cannot be merged

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

__eq__

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__eq__(
    other
)

Return self==value.

__ne__

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__ne__(
    other
)

Return self!=value.