tf.data.experimental.DistributeOptions
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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__
View source
__eq__(
other
)
Return self==value.
__ne__
View source
__ne__(
other
)
Return self!=value.
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Last updated 2020-10-01 UTC.
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