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_policy = tf.data.experimental.AutoShardPolicy.OFF dataset = dataset.with_options(options)
Attributes |
auto_shard_policy | The type of sharding to use. See tf.data.experimental.AutoShardPolicy for additional information. |
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 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.data.experimental.DistributeOptions\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/data/ops/options.py#L262-L301) |\n\nRepresents options for distributed data processing.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.data.experimental.DistributeOptions`](https://www.tensorflow.org/api_docs/python/tf/data/experimental/DistributeOptions)\n\n\u003cbr /\u003e\n\n tf.data.experimental.DistributeOptions()\n\nYou can set the distribution options of a dataset through the\n`experimental_distribute` property of [`tf.data.Options`](../../../tf/data/Options); the property is\nan instance of [`tf.data.experimental.DistributeOptions`](../../../tf/data/experimental/DistributeOptions). \n\n options = tf.data.Options()\n options.experimental_distribute.auto_shard_policy = tf.data.experimental.AutoShardPolicy.OFF\n dataset = dataset.with_options(options)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|---------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `auto_shard_policy` | The type of sharding to use. See [`tf.data.experimental.AutoShardPolicy`](../../../tf/data/experimental/AutoShardPolicy) for additional information. |\n| `num_devices` | The number of devices attached to this input pipeline. This will be automatically set by `MultiDeviceIterator`. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `__eq__`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/data/util/options.py#L38-L44) \n\n __eq__(\n other\n )\n\nReturn self==value.\n\n### `__ne__`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/data/util/options.py#L46-L50) \n\n __ne__(\n other\n )\n\nReturn self!=value."]]