code: def register_dataset(
      service, dataset, compression="AUTO", dataset_id=None
  ) -> tensor.Tensor:
      """Registers a dataset with the tf.data service.
  
      `register_dataset` registers a dataset with the tf.data service so that
      datasets can be created later with
      `tf.data.experimental.service.from_dataset_id`. This is useful when the
      dataset
      is registered by one process, then used in another process. When the same
      process is both registering and reading from the dataset, it is simpler to use
      `tf.data.experimental.service.distribute` instead.
  
      If the dataset is already registered with the tf.data service,
      `register_dataset` returns the already-registered dataset's id.
  
      >>> dispatcher = tf.data.experimental.service.DispatchServer()
      >>> dispatcher_address = dispatcher.target.split("://")[1]
      >>> worker = tf.data.experimental.service.WorkerServer(
      ...     tf.data.experimental.service.WorkerConfig(
      ...         dispatcher_address=dispatcher_address))
      >>> dataset = tf.data.Dataset.range(10)
      >>> dataset_id = tf.data.experimental.service.register_dataset(
      ...     dispatcher.target, dataset)
      >>> dataset = tf.data.experimental.service.from_dataset_id(
      ...     processing_mode="parallel_epochs",
      ...     service=dispatcher.target,
      ...     dataset_id=dataset_id,
      ...     element_spec=dataset.element_spec)
      >>> print(list(dataset.as_numpy_iterator()))
      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
  
      Args:
        service: A string or a tuple indicating how to connect to the tf.data
          service. If it's a string, it should be in the format
          `[<protocol>://]<address>`, where `<address>` identifies the dispatcher
            address and `<protocol>` can optionally be used to override the default
            protocol to use. If it's a tuple, it should be (protocol, address).
        dataset: A `tf.data.Dataset` to register with the tf.data service.
        compression: (Optional.) How to compress the dataset's elements before
          transferring them over the network. "AUTO" leaves the decision of how to
          compress up to the tf.data service runtime. `None` indicates not to
          compress.
        dataset_id: (Optional.) By default, tf.data service generates a unique
          (string) ID for each registered dataset. If a `dataset_id` is provided, it
          will use the specified ID. If a dataset with a matching ID already exists,
          no new dataset is registered. This is useful if multiple training jobs
          want to (re)use the same dataset for training. In this case, they can
          register the dataset with the same dataset ID.
  
      Returns:
        A scalar string tensor representing the dataset ID.
      """
      return _register_dataset(
          service, dataset, compression, dataset_id
      )
  
imports: import enum
  import functools
  from typing import Callable
  from tensorflow.core.protobuf import data_service_pb2
  from tensorflow.python import tf2
  from tensorflow.python.data.experimental.ops import compression_ops
  from tensorflow.python.data.experimental.service import _pywrap_server_lib
  from tensorflow.python.data.experimental.service import _pywrap_utils
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.data.ops import structured_function
  from tensorflow.python.data.ops.options import AutoShardPolicy
  from tensorflow.python.data.ops.options import ExternalStatePolicy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 11 for calling a global function with example usage: register_dataset(service, dataset, compression, dataset_id) and returns: _register_dataset