code: def setUp(self):
      super().setUp()
  
      batch_size = 8
  
      # Mock the replay buffer to avoid loading data over the network
      self.create_replay_buffer = functools.partial(
          mock.create_autospec,
          spec=fixed_replay.JaxFixedReplayBuffer,
          spec_set=True,
      )
      observation_shape = (
          batch_size,
          *dqn_agent.NATURE_DQN_OBSERVATION_SHAPE,
          dqn_agent.NATURE_DQN_STACK_SIZE,
      )
      self.batch = {
          "state": jnp.full(observation_shape, 125, dtype=jnp.uint8),
          "action": jnp.full(batch_size, 0, dtype=jnp.int32),
          "reward": jnp.full(batch_size, 1.0, dtype=jnp.float32),
          "next_state": jnp.full(
              observation_shape, 125, dtype=jnp.uint8
          ),
          "next_action": jnp.full(batch_size, 0, dtype=jnp.int32),
          "next_reward": jnp.full(batch_size, 1.0, dtype=jnp.float32),
          "terminal": jnp.full(batch_size, 0, dtype=jnp.uint8),
          "indices": jnp.arange(batch_size, dtype=jnp.int32),
      }
  
      gin.bind_parameter(
          "fixed_replay.JaxFixedReplayBuffer.replay_capacity", 100
      )
      gin.bind_parameter(
          "fixed_replay.JaxFixedReplayBuffer.batch_size", batch_size
      )
      gin.bind_parameter("JaxDQNAgent.seed", 123)
  
file_path: dopamine/tests/dopamine/labs/offline_rl/jax/offline_agent_test.py
imports: import functools
  from unittest import mock
  from absl.testing import absltest
  from absl.testing import parameterized
  from dopamine.jax.agents.dqn import dqn_agent
  from dopamine.labs.offline_rl import fixed_replay
  from dopamine.labs.offline_rl.jax import networks
  from dopamine.labs.offline_rl.jax import offline_dr3_agent
  import gin
  import jax
  from jax import numpy
label_desc: Use image node_id 1 for calling the OfflineAgentTest obj's underlying member method code with example usage: obj.setUp() without return types