tensors will be split into shards when the saver writes the checkpoint
      shards to disk. `tf.train.experimental.ShardByTaskPolicy` is the default
      sharding behavior, but `tf.train.experimental.MaxShardSizePolicy` can be
      used to shard the checkpoint with a maximum shard file size. Users with
      advanced use cases can also write their own custom

  let summary = "Gets next element for the provided shard number.";

  let arguments = (ins
    Arg<TF_ResourceTensor, [{A MultiDeviceIterator resource.}], [TF_DatasetIteratorRead, TF_DatasetIteratorWrite]>:$multi_device_iterator,
    Arg<TF_Int32Tensor, [{Integer representing which shard to fetch data for.}]>:$shard_num,

                            required:
                            - name
                            type: object
                          literal:
                            description: Literal adds the same, hard-coded value to
                              each span.
                            properties:
                              value:
                                description: The tag value to use.

                            required:
                            - name
                            type: object
                          literal:
                            description: Literal adds the same, hard-coded value to
                              each span.
                            properties:
                              value:
                                description: The tag value to use.