tf.raw_ops.AutoShardDataset
Creates a dataset that shards the input dataset.
tf.raw_ops.AutoShardDataset( input_dataset, num_workers, index, output_types, output_shapes, auto_shard_policy=0, num_replicas=0, name=None )
Creates a dataset that shards the input dataset by num_workers, returning a sharded dataset for the index-th worker. This attempts to automatically shard a dataset by examining the Dataset graph and inserting a shard op before the inputs to a reader Dataset (e.g. CSVDataset, TFRecordDataset).
This dataset will throw a NotFound error if we cannot shard the dataset automatically.
Args | |
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input_dataset | A Tensor of type variant . A variant tensor representing the input dataset. |
num_workers | A Tensor of type int64 . A scalar representing the number of workers to distribute this dataset across. |
index | A Tensor of type int64 . A scalar representing the index of the current worker out of num_workers. |
output_types | A list of tf.DTypes that has length >= 1 . |
output_shapes | A list of shapes (each a tf.TensorShape or list of ints ) that has length >= 1 . |
auto_shard_policy | An optional int . Defaults to 0 . |
num_replicas | An optional int . Defaults to 0 . |
name | A name for the operation (optional). |
Returns | |
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A Tensor of type variant . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/AutoShardDataset