code: def push_rlds_to_reverb(
      rlds_data: tf.data.Dataset,
      reverb_observer: Union[
          reverb_utils.ReverbAddEpisodeObserver,
          reverb_utils.ReverbAddTrajectoryObserver,
      ],
      policy_info_fn: _PolicyFnType = None,
  ) -> int:
      """Pushes the RLDS data to Reverb server as TF Agents trajectories.
  
      Pushes the rlds_data provided to Reverb server using reverb_observer after
      converting it to TF Agents trajectories.
  
      Please note that the data spec used to initialize replay buffer and reverb
      server  for creating the reverb_observer must match the data
      spec for rlds_data.
  
      Args:
        rlds_data: An RLDS dataset is tf.data.Dataset of RLDS episodes, where each
          episode contains a tf.data.Dataset of RLDS steps. An RLDS step is a
          dictionary of tensors containing is_first, is_last, observation, action,
          reward, is_terminal, and discount.
        reverb_observer: A Reverb observer for writing trajectories data to Reverb.
        policy_info_fn: An optional function to create some policy.info to be used
          while generating TF-Agents trajectories.
  
      Returns:
        An int representing the number of trajectories successfully pushed to RLDS.
  
      Raises:
        ValueError: If no RLDS steps exist in rlds_data.
        ValueError: If step spec for rlds_data is not valid.
        ValueError: If data spec used to initialize replay buffer and reverb server
        for creating the reverb_observer does not match the data spec for trajectory
        dataset that can be created using rlds_data.
        InvalidArgumentError: If the RLDS dataset provided has episodes that:
          - Incorrectly end i.e. does not end in last step.
          - Incorrectly terminate i.e. a terminal step is not the last step.
          - Incorrectly begin i.e. a last step is not followed by the first step.
            Please note that the last step of the last episode is taken care of
            in the function and the user does not need to make sure that the last
            step of the last episode is followed by a first step.
      """
  
      table_signature_spec = reverb_observer.get_table_signature()
      if table_signature_spec != tensor_spec.add_outer_dim(
          create_trajectory_data_spec(rlds_data)
      ):
          raise ValueError(
              "Replay buffer table signature spec should match RLDS data spec."
          )
  
      steps = 0
      for entry in convert_rlds_to_trajectories(
          rlds_data, policy_info_fn
      ):
          reverb_observer(entry)
          steps += 1
      logging.info("Successfully wrote %d steps to Reverb.", steps)
      return steps
  
file_path: agents/tf_agents/replay_buffers/rlds_to_reverb.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Callable, Dict, List, Optional, Tuple, Union
  from absl import logging
  import numpy
  import rlds
  import tensorflow
  from tf_agents.replay_buffers import reverb_utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
label_desc: Use image node_id 6 for calling a global function with example usage: push_rlds_to_reverb(rlds_data, reverb_observer, policy_info_fn) and returns: steps