class_docstr: Extended class for ParameterServerStrategyV2.
  
  Please see `tf.distribute.StrategyExtended` doc for more information.
class_docstr_tok: ["Extended","class","for","ParameterServerStrategyV2",".","Please","see","`","tf.distribute.StrategyExtended","`","doc","for","more","information","."]
code: def _distribute_datasets_from_function(self, dataset_fn, options):
      # There is no synchronization beyond a worker and thus, the number of
      # input pipelines in sync is only 1 per worker.
      input_pipeline_id_in_sync = 0
      num_input_pipelines_in_sync = 1
  
      input_context = distribute_lib.InputContext(
          num_input_pipelines=num_input_pipelines_in_sync,
          input_pipeline_id=input_pipeline_id_in_sync,
          num_replicas_in_sync=self._num_replicas_in_sync,
      )
  
      # If this DistributedDatasetFromFunction is created outside
      # ClusterCoordinator, i,e, outside a tf.function, we don't build its
      # underlying datasets immediately until it is passed to
      # ClusterCoordinator.create_per_worker_dataset.
      return input_util.get_distributed_datasets_from_function(
          dataset_fn,
          self._input_workers_with_options(options),
          [input_context],
          self._container_strategy(),
          options=options,
          build=ops.inside_function(),
      )
  
imports: import functools
  import os
  import threading
  from tensorflow.python.distribute import cross_device_ops
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import input_lib
  from tensorflow.python.distribute import input_util
  from tensorflow.python.distribute import load_context
  from tensorflow.python.distribute import mirrored_run
  from tensorflow.python.distribute import multi_worker_util
  from tensorflow.python.distribute import parameter_server_strategy
  from tensorflow.python.distribute import ps_values
  from tensorflow.python.distribute import sharded_variable
  from tensorflow.python.distribute import values
  from tensorflow.python.distribute.cluster_resolver import cluster_resolver
  from tensorflow.python.distribute.coordinator import cluster_coordinator
  from tensorflow.python.eager import context
  from tensorflow.python.eager import remote
  from tensorflow.python.framework import config
  from tensorflow.python.framework import device
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.trackable import base
  from tensorflow.python.training import server_lib
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_inspect
  from tensorflow.python.util.tf_export import tf_export
  from tsl.protobuf import coordination_config_pb2
label_desc: Use image node_id 13 for calling the ParameterServerStrategyV2Extended obj's underlying member method code with example usage: obj._distribute_datasets_from_function(dataset_fn, options) and returns: input_util