hunk.code_window:         config_path = self.write_config(SMALL_CLUSTER)
           self.provider = MockProvider()
           runner = MockProcessRunner()
           get_or_create_head_node(
               SMALL_CLUSTER,
               config_path,
  
hunk.labels: keep keep add keep keep keep
hunk.after_edit:         runner.respond_to_call("json .Mounts", ["[]"])
           # Two initial calls to docker cp, one before run, two final calls to cp
           runner.respond_to_call(".State.Running",
                                  ["false", "false", "false", "true", "true"])
  
hunk.file_path: python/ray/tests/test_autoscaler.py
hunk.type: add
file: cartpole-appo:
      env: CartPole-v0
      run: APPO
      stop:
          episode_reward_mean: 150
          timesteps_total: 200000
      config:
          # Works for both torch and tf.
          framework: tf
          rollout_fragment_length: 10
          train_batch_size: 10
          num_envs_per_worker: 5
          num_workers: 1
          num_gpus: 0
          vtrace: false
  