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, 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.  |  
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
 A Tensor of type variant.  |  
    © 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/AutoShardDataset