tf.raw_ops.AutoShardDataset
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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 |
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 |
A Tensor of type variant .
|
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Last updated 2021-05-14 UTC.
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