code: def get_reverb_buffer(
      data_spec,
      sequence_length=None,
      table_name="uniform_table",
      table=None,
      reverb_server_address=None,
      port=None,
      replay_capacity=1000,
      min_size_limiter_size=1,
  ):
      """Returns an instance of Reverb replay buffer and observer to add items.
  
      Either creates a local reverb server or uses a remote reverb server at
      reverb_sever_address (if set).
  
      If reverb_server_address is None, creates a local server with a uniform
      table underneath.
  
      Args:
        data_spec: spec of the data elements to be stored in the replay buffer
        sequence_length: integer specifying sequence_lenghts used to write to the
          given table.
        table_name: Name of the table to create.
        table: Optional table for the backing local server. If None, automatically
          creates a uniform sampling table.
        reverb_server_address: Address of the remote reverb server, if None a local
          server is created.
        port: Port to launch the server in.
        replay_capacity: Optinal (for default uniform sampling table only, i.e if
          table=None) capacity of the uniform sampling table for the local replay
          server.
        min_size_limiter_size: Optional (for default uniform sampling table only,
          i.e if table=None) minimum number of items required in the RB before
          sampling can begin, used for local server only.
  
      Returns:
        Reverb replay buffer instance
  
        Note: the if local server is created, it is not returned. It can be
          retrieved by calling local_server() on the returned replay buffer.
      """
      table_signature = tensor_spec.add_outer_dim(
          data_spec, sequence_length
      )
  
      if reverb_server_address is None:
          if table is None:
              table = _create_uniform_table(
                  table_name,
                  table_signature,
                  table_capacity=replay_capacity,
                  min_size_limiter_size=min_size_limiter_size,
              )
  
          reverb_server = reverb.Server([table], port=port)
          reverb_replay = reverb_replay_buffer.ReverbReplayBuffer(
              data_spec,
              sequence_length=sequence_length,
              table_name=table_name,
              local_server=reverb_server,
          )
      else:
          reverb_replay = reverb_replay_buffer.ReverbReplayBuffer(
              data_spec,
              sequence_length=sequence_length,
              table_name=table_name,
              server_address=reverb_server_address,
          )
  
      return reverb_replay
  
imports: from tf_agents.replay_buffers import reverb_replay_buffer
  from tf_agents.replay_buffers import reverb_utils
  from tf_agents.specs import tensor_spec
  from tf_agents.utils import lazy_loader
label_desc: Use image node_id 2 for calling a global function with example usage: get_reverb_buffer(data_spec, sequence_length, table_name, table, reverb_server_address, port, replay_capacity, min_size_limiter_size) and returns: reverb_replay