code: def test_dm_control_tf_policy(self):
      task = ALL_TASKS[0]
  
      with TFTrainer(snapshot_config, sess=self.sess) as trainer:
          env = DMControlEnv.from_suite(*task)
  
          policy = GaussianMLPPolicy(
              env_spec=env.spec,
              hidden_sizes=(32, 32),
          )
  
          baseline = LinearFeatureBaseline(env_spec=env.spec)
  
          sampler = LocalSampler(
              agents=policy,
              envs=env,
              max_episode_length=env.spec.max_episode_length,
              is_tf_worker=True,
          )
  
          algo = TRPO(
              env_spec=env.spec,
              policy=policy,
              baseline=baseline,
              sampler=sampler,
              discount=0.99,
              max_kl_step=0.01,
          )
  
          trainer.setup(algo, env)
          trainer.train(n_epochs=1, batch_size=10)
  
          env.close()
  
file_path: garage/tests/garage/envs/dm_control/test_dm_control_tf_policy.py
imports: from dm_control.suite import ALL_TASKS
  import pytest
  from garage.envs.dm_control import DMControlEnv
  from garage.np.baselines import LinearFeatureBaseline
  from garage.sampler import LocalSampler
  from garage.tf.algos import TRPO
  from garage.tf.policies import GaussianMLPPolicy
  from garage.trainer import TFTrainer
  from tests.fixtures import snapshot_config, TfGraphTestCase
label_desc: Use image node_id 1 for calling the TestDmControlTfPolicy obj's underlying member method code with example usage: obj.test_dm_control_tf_policy() without return types