tf.data.experimental.DistributeOptions

Represents options for distributed data processing.

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.data.experimental.DistributeOptions, `tf.compat.v2.data.experimental.DistributeOptions`

tf.data.experimental.DistributeOptions()

You can set the distribution options of a dataset through the experimental_distribute property of tf.data.Options; the property is an instance of tf.data.experimental.DistributeOptions.

options = tf.data.Options()
options.experimental_distribute.auto_shard = False
dataset = dataset.with_options(options)

Attributes
`auto_shard`	Whether the dataset should be automatically sharded when processedin a distributed fashion. This is applicable when using Keras with multi-worker/TPU distribution strategy, and by using strategy.experimental_distribute_dataset(). In other cases, this option does nothing. If None, defaults to True.
`num_devices`	The number of devices attached to this input pipeline. This will be automatically set by MultiDeviceIterator.

Methods

__eq__(
    other
)

Return self==value.

__ne__(
    other
)

Return self!=value.