code: def build_tfds_replay(
      stack_size,
      update_horizon,
      gamma,
      return_to_go=False,
      dataset=None,
      game="Pong",
      run_number=1,
      batch_size=32,
      repeat_ds=True,
  ):
      """Builds the tfds replay buffer."""
      transition_fn = get_transition_dataset_fn(
          stack_size, update_horizon, gamma, return_to_go=return_to_go
      )
      if dataset is None:
          dataset_name = (
              f"rlu_atari_checkpoints_ordered/{game}_run_{run_number}"
          )
          # Create a dataset of episodes sampling `data_percent`% episodes
          # from each of the data split
          dataset = uniformly_subsampled_atari_data(
              dataset_name, data_percent=10
          )
      atari_ds = create_atari_ds_loader(
          dataset, transition_fn=transition_fn
      )
      return create_ds_iterator(atari_ds, batch_size, repeat=repeat_ds)
  
file_path: dopamine/dopamine/labs/offline_rl/rlu_tfds/tfds_atari_utils.py
imports: import rlds
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 6 for calling a global function with example usage: build_tfds_replay(stack_size, update_horizon, gamma, return_to_go, dataset, game, run_number, batch_size, repeat_ds) and returns: create_ds_iterator