code: def test_train(self):
      seed = 0
      num_iterations = 6
      batch_size = 64
  
      # Create a fake environment to test with.
      environment = fakes.ContinuousEnvironment(
          episode_length=10, bounded=True, action_dim=6
      )
      spec = specs.make_environment_spec(environment)
  
      # Construct the agent.
      networks = cql.make_networks(spec, hidden_layer_sizes=(8, 8))
      dataset = fakes.transition_iterator(environment)
      key = jax.random.PRNGKey(seed)
      learner = cql.CQLLearner(
          batch_size,
          networks,
          key,
          demonstrations=dataset(batch_size),
          policy_optimizer=optax.adam(3e-5),
          critic_optimizer=optax.adam(3e-4),
          fixed_cql_coefficient=5.0,
          cql_lagrange_threshold=None,
          target_entropy=0.1,
          num_bc_iters=2,
          num_sgd_steps_per_step=1,
      )
  
      # Train the agent
      for _ in range(num_iterations):
          learner.step()
  
file_path: acme/acme/agents/jax/cql/agent_test.py
imports: from acme import specs
  from acme.agents.jax import cql
  from acme.testing import fakes
  import jax
  import optax
  from absl.testing import absltest
label_desc: Use image node_id 1 for calling the CQLTest obj's underlying member method code with example usage: obj.test_train() without return types