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 _create_var_creator(self, next_creator, **kwargs):
      aggregation = kwargs.pop(
          "aggregation", vs.VariableAggregation.NONE
      )
  
      def var_creator(**kwargs):
          """Create an AggregatingVariable."""
          # Create and wrap the variable.
          v = next_creator(**kwargs)
          wrapped_v = ps_values.CachingVariable(v)
          wrapped = ps_values.AggregatingVariable(
              self._container_strategy(), wrapped_v, aggregation
          )
          return wrapped
  
      if self._num_replicas_in_sync > 1:
          if aggregation not in (
              vs.VariableAggregation.NONE,
              vs.VariableAggregation.SUM,
              vs.VariableAggregation.MEAN,
              vs.VariableAggregation.ONLY_FIRST_REPLICA,
          ):
              raise ValueError(
                  "Invalid variable aggregation mode: "
                  + aggregation
                  + " for variable: "
                  + kwargs["name"]
              )
          return var_creator
      else:
  
          def variable_creator_single_replica(**kwargs):
              v = next_creator(**kwargs)
              return ps_values.CachingVariable(v)
  
          return variable_creator_single_replica
  
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 4 for calling the ParameterServerStrategyV2Extended obj's underlying member method code with example usage: obj._create_var_creator(next_creator) and returns: wrapped, var_creator, variable_creator_single_replica, ps_values