hunk.code_window: @pytest.mark.parametrize(
       "ray_start_regular", [
           generate_system_config_map(
               num_heartbeats_timeout=20, ping_gcs_rpc_server_max_retries=60)
       ],
       indirect=True)
   def test_gcs_server_restart(ray_start_regular):
       actor1 = Increase.remote()
  
hunk.labels: keep keep keep replace keep keep keep keep
hunk.after_edit:             num_heartbeats_timeout=2, ping_gcs_rpc_server_max_retries=60)
  
hunk.file_path: python/ray/tests/test_gcs_fault_tolerance.py
hunk.type: replace
file: repeat-after-me-ppo-w-lstm:
      env: ray.rllib.examples.env.repeat_after_me_env.RepeatAfterMeEnv
      run: PPO
      stop:
          episode_reward_mean: 50
          timesteps_total: 100000
      config:
          # Works for both torch and tf.
          framework: tf
          env_config:
            config:
              repeat_delay: 2
          gamma: 0.9
          lr: 0.0003
          num_workers: 0
          num_envs_per_worker: 20
          num_sgd_iter: 5
          entropy_coeff: 0.00001
          model:
              use_lstm: true
              lstm_cell_size: 64
              max_seq_len: 20
              fcnet_hiddens: [64]
              vf_share_layers: true
  