/TensorFlow 1.15


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Represents options for tf.data.Dataset.

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

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_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_stateful_whitelist By default, tf.data will refuse to serialize a dataset or checkpoint its iterator if the dataset contains a stateful op as the serialization / checkpointing won't be able to capture its state. Users can -- at their own risk -- override this restriction by explicitly whitelisting stateful ops by specifying them in this list.
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.



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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.

options a tf.data.Options to merge with
ValueError if the given tf.data.Options cannot be merged
New tf.data.Options() object which is the result of merging self with the input tf.data.Options.


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Return self==value.


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Return self!=value.

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