class_docstr: Offline Rainbow agent with BC regularization (akin to CQL).
docstr: Creates the fixed replay buffer used by the agent.
docstr_tok: ["Creates","the","fixed","replay","buffer","used","by","the","agent","."]
code: def _build_replay_buffer(self):
      """Creates the fixed replay buffer used by the agent."""
  
      if not self._use_tfds:
          return fixed_replay.JaxFixedReplayBuffer(
              data_dir=self.replay_data_dir,
              observation_shape=self.observation_shape,
              stack_size=self.stack_size,
              update_horizon=self.update_horizon,
              gamma=self.gamma,
              observation_dtype=self.observation_dtype,
          )
  
      dataset_name = tfds_replay.get_atari_ds_name_from_replay(
          self.replay_data_dir
      )
      return tfds_replay.JaxFixedReplayBufferTFDS(
          replay_capacity=gin.query_parameter(
              "JaxFixedReplayBuffer.replay_capacity"
          ),
          batch_size=gin.query_parameter(
              "JaxFixedReplayBuffer.batch_size"
          ),
          dataset_name=dataset_name,
          stack_size=self.stack_size,
          update_horizon=self.update_horizon,
          gamma=self.gamma,
          return_to_go=self._add_return_to_go,
      )
  
imports: import functools
  from absl import logging
  from dopamine.jax import losses
  from dopamine.jax.agents.full_rainbow import full_rainbow_agent
  from dopamine.jax.agents.rainbow import rainbow_agent
  from dopamine.labs.offline_rl import fixed_replay
  from dopamine.labs.offline_rl.rlu_tfds import tfds_replay
  import gin
  import jax
  import jax.numpy
  import numpy
  import optax
  import tensorflow
label_desc: Use image node_id 3 for calling the OfflineJaxRainbowAgent obj's underlying member method code with example usage: obj._build_replay_buffer() and returns: tfds_replay, fixed_replay