tf.data.experimental.OptimizationOptions

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Represents options for dataset optimizations.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.data.experimental.OptimizationOptions

tf.data.experimental.OptimizationOptions()

You can set the optimization options of a dataset through the experimental_optimization property of tf.data.Options; the property is an instance of tf.data.experimental.OptimizationOptions.

options = tf.data.Options()
options.experimental_optimization.noop_elimination = True
options.experimental_optimization.map_vectorization.enabled = True
options.experimental_optimization.apply_default_optimizations = False
dataset = dataset.with_options(options)

Attributes
apply_default_optimizations	Whether to apply default graph optimizations. If False, only graph optimizations that have been explicitly enabled will be applied.
autotune	Whether to automatically tune performance knobs. If None, defaults to True.
autotune_buffers	When autotuning is enabled (through autotune), determines whether to also autotune buffer sizes for datasets with parallelism. If None, defaults to False.
autotune_cpu_budget	When autotuning is enabled (through autotune), determines the CPU budget to use. Values greater than the number of schedulable CPU cores are allowed but may result in CPU contention. If None, defaults to the number of schedulable CPU cores.
filter_fusion	Whether to fuse filter transformations. If None, defaults to False.
filter_with_random_uniform_fusion	Whether to fuse filter dataset that predicts random_uniform < rate into a sampling dataset. If None, defaults to False.
hoist_random_uniform	Whether to hoist tf.random_uniform() ops out of map transformations. If None, defaults to False.
map_and_batch_fusion	Whether to fuse map and batch transformations. If None, defaults to True.
map_and_filter_fusion	Whether to fuse map and filter transformations. If None, defaults to False.
map_fusion	Whether to fuse map transformations. If None, defaults to False.
map_parallelization	Whether to parallelize stateless map transformations. If None, defaults to False.
map_vectorization	The map vectorization options associated with the dataset. See tf.data.experimental.MapVectorizationOptions for more details.
noop_elimination	Whether to eliminate no-op transformations. If None, defaults to True.
parallel_batch	Whether to parallelize copying of batch elements. If None, defaults to False.
shuffle_and_repeat_fusion	Whether to fuse shuffle and repeat transformations. If None, defaults to True.

Methods

__eq__

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__eq__(
    other
)

Return self==value.

__ne__

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__ne__(
    other
)

Return self!=value.