|TensorFlow 2 version||View source on GitHub|
Represents options for tf.data.Dataset.
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
Initialize self. See help(type(self)) for accurate signature.
Whether the outputs need to be produced in deterministic order. If None, defaults to True.
The distribution strategy options associated with the dataset. See
tf.data.experimental.DistributeOptions for more details.
The optimization options associated with the dataset. See
tf.data.experimental.OptimizationOptions for more details.
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.
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.
The statistics options associated with the dataset. See
tf.data.experimental.StatsOptions for more details.
The threading options associated with the dataset. See
tf.data.experimental.ThreadingOptions for more details.
Merges itself with the given
tf.data.Options can be merged as long as there does not exist an
attribute that is set to different values in
tf.data.Optionsto merge with
ValueError: if the given
tf.data.Optionscannot be merged