tf.data.Options

Represents options for tf.data.Dataset.

tf.data.Options()

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

The options are set for the entire dataset and are carried over to datasets created through tf.data transformations.

The options can be set by constructing an Options object and using the tf.data.Dataset.with_options(options) transformation, which returns a dataset with the options set.

dataset = tf.data.Dataset.range(42)
options = tf.data.Options()
options.experimental_deterministic = False
dataset = dataset.with_options(options)
print(dataset.options().experimental_deterministic)
False

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: External state is ignored without a warning; WARN: External state is ignored and a warning is logged; FAIL: External state results in an error.
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

View source

merge(
    options
)

Merges itself with the given tf.data.Options.

If this object and the options to merge set an option differently, a warning is generated and this object's value is updated with the options object's value.

Args
options a tf.data.Options to merge with

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

__eq__

View source

__eq__(
    other
)

Return self==value.

__ne__

View source

__ne__(
    other
)

Return self!=value.