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.
 |