class_docstr: Represents options for distributed data processing.
  
  You can set the distribution options of a dataset through the
  `experimental_distribute` property of `tf.data.Options`; the property is
  an instance of `tf.data.experimental.DistributeOptions`.
  
  ```python
  options = tf.data.Options()
  options.experimental_distribute.auto_shard_policy = tf.data.experimental.AutoShardPolicy.OFF
  dataset = dataset.with_options(options)
  ```
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code: def _from_proto(self, pb):
      self.auto_shard_policy = AutoShardPolicy._from_proto(
          pb.auto_shard_policy
      )  # pylint: disable=protected-access
      if pb.WhichOneof("optional_num_devices") is not None:
          self.num_devices = pb.num_devices
  
imports: import enum
  import platform
  from absl import logging
  from tensorflow.core.framework import dataset_options_pb2
  from tensorflow.core.framework import model_pb2
  from tensorflow.python.data.ops import test_mode
  from tensorflow.python.data.util import options
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the DistributeOptions obj's underlying member method code with example usage: obj._from_proto(pb) without return types