tf.data.experimental.AutotuneOptions | TensorFlow v2.16.1 (original) (raw)
tf.data.experimental.AutotuneOptions
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Represents options for autotuning dataset performance.
View aliases
Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.data.experimental.AutotuneOptions
tf.data.experimental.AutotuneOptions()
options = tf.data.Options()
options.autotune.enabled = False
dataset = dataset.with_options(options)
| Attributes | |
|---|---|
| autotune_algorithm | When autotuning is enabled (through autotune), determines the algorithm to use. |
| 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. |
| enabled | Whether to automatically tune performance knobs. If None, defaults to True. |
| ram_budget | When autotuning is enabled (through autotune), determines the RAM budget to use. Values greater than the available RAM in bytes may result in OOM. If None, defaults to half of the available RAM in bytes. |
Methods
__eq__
__eq__(
other
)
Return self==value.
__ne__
__ne__(
other
)
Return self!=value.
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Last updated 2024-04-26 UTC.