tf.data.experimental.DistributeOptions

TensorFlow 1 version View source on GitHub

Represents options for distributed data processing.

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__

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__eq__(
    other
)

Return self==value.

__ne__

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__ne__(
    other
)

Return self!=value.