code: def _create_server(
      table: Text = reverb_variable_container.DEFAULT_TABLE,
      max_size: int = 1,
      signature: Optional[types.NestedTensorSpec] = (
          tf.TensorSpec((), tf.int64),
          {
              "var1": (tf.TensorSpec((2), tf.float64),),
              "var2": tf.TensorSpec((2, 1), tf.int32),
          },
      ),
  ) -> Tuple[reverb.Server, Text]:
      server = reverb.Server(
          tables=[
              reverb.Table(
                  name=table,
                  sampler=reverb.selectors.Uniform(),
                  remover=reverb.selectors.Fifo(),
                  rate_limiter=reverb.rate_limiters.MinSize(1),
                  max_size=max_size,
                  max_times_sampled=0,
                  signature=signature,
              )
          ],
          port=portpicker.pick_unused_port(),
      )
      return server, "localhost:{}".format(server.port)
  
imports: from typing import Optional, Text, Tuple
  from absl import logging
  from absl.testing import parameterized
  import numpy
  import portpicker
  import reverb
  import tensorflow.compat.v2
  from tf_agents.experimental.distributed import reverb_variable_container
  from tf_agents.system import system_multiprocessing
  from tf_agents.typing import types
  from tf_agents.utils import nest_utils
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling a global function with example usage: _create_server(table, max_size, signature) and returns: server,  str