class_docstr: PWIL Agent builder.
class_docstr_tok: ["PWIL","Agent","builder","."]
code: def make_dataset_iterator(  # pytype: disable=signature-mismatch  # overriding-return-type-checks
      self, replay_client: reverb.Client
  ) -> Optional[Iterator[reverb.ReplaySample]]:
      # make_dataset_iterator is only called once (per learner), to pass the
      # iterator to make_learner. By using adders we ensure the transition types
      # (e.g. n-step transitions) that the direct RL agent expects.
      if self._config.num_transitions_rb > 0:
  
          def prefill_thread():
              # Populating the replay buffer with the direct RL agent guarantees that
              # a constant reward will be used, not the imitation reward.
              prefill_reward = (
                  self._config.alpha
                  if self._config.prefill_constant_reward
                  else None
              )
              _prefill_with_demonstrations(
                  adder=self._rl_agent.make_adder(
                      replay_client, None, None
                  ),
                  demonstrations=list(
                      self._demonstrations_fn().demonstrations
                  ),
                  min_num_transitions=self._config.num_transitions_rb,
                  reward=prefill_reward,
              )
  
          # Populate the replay buffer in a separate thread, so that the learner
          # can sample from the buffer, to avoid blocking on the buffer being full.
          threading.Thread(target=prefill_thread, daemon=True).start()
  
      return self._rl_agent.make_dataset_iterator(replay_client)
  
imports: import threading
  from typing import Callable, Generic, Iterator, List, Optional, Sequence
  from acme import adders
  from acme import core
  from acme import specs
  from acme import types
  from acme.agents.jax import builders
  from acme.agents.jax.pwil import adder
  from acme.agents.jax.pwil import config
  from acme.agents.jax.pwil import rewarder
  from acme.jax import networks
  from acme.jax.imitation_learning_types import DirectPolicyNetwork, DirectRLNetworks
  from acme.jax.types import PRNGKey
  from acme.utils import counting
  from acme.utils import loggers
  import dm_env
  import numpy
  import reverb
label_desc: Use image node_id 4 for calling the PWILBuilder obj's underlying member method code with example usage: obj.make_dataset_iterator(replay_client) and returns: self