old_contents: # This workload tests running many instances of PPO (many actors)
  # This covers https://github.com/ray-project/ray/pull/12148
  
  import ray
  from ray.tune import run_experiments
  from ray.tune.utils.release_test_util import ProgressCallback
  
  num_redis_shards = 5
  redis_max_memory = 10**8
  object_store_memory = 10**9
  num_nodes = 3
  
  message = ("Make sure there is enough memory on this machine to run this "
             "workload. We divide the system memory by 2 to provide a buffer.")
  assert (num_nodes * object_store_memory + num_redis_shards * redis_max_memory <
          ray._private.utils.get_system_memory() / 2), message
  
  # Simulate a cluster on one machine.
  
  ray.init(address="auto")
  
  # Run the workload.
  
  run_experiments(
      {
          "ppo": {
              "run": "PPO",
              "env": "CartPole-v0",
              "num_samples": 10,
              "config": {
                  "framework": "torch",
                  "num_workers": 7,
                  "num_gpus": 0,
                  "num_sgd_iter": 1,
              },
              "stop": {
                  "timesteps_total": 1,
              },
          }
      },
      callbacks=[ProgressCallback()])
  
new_contents: # This workload tests running many instances of PPO (many actors)
  # This covers https://github.com/ray-project/ray/pull/12148
  
  import ray
  from ray.tune import run_experiments
  from ray.tune.utils.release_test_util import ProgressCallback
  
  num_redis_shards = 5
  redis_max_memory = 10**8
  object_store_memory = 10**9
  num_nodes = 3
  
  message = ("Make sure there is enough memory on this machine to run this "
             "workload. We divide the system memory by 2 to provide a buffer.")
  assert (num_nodes * object_store_memory + num_redis_shards * redis_max_memory <
          ray._private.utils.get_system_memory() / 2), message
  
  # Simulate a cluster on one machine.
  
  ray.init(address="auto")
  
  # Run the workload.
  
  run_experiments(
      {
          "ppo": {
              "run": "PPO",
              "env": "CartPole-v0",
              "num_samples": 10000,
              "config": {
                  "framework": "torch",
                  "num_workers": 7,
                  "num_gpus": 0,
                  "num_sgd_iter": 1,
              },
              "stop": {
                  "timesteps_total": 1,
              },
          }
      },
      callbacks=[ProgressCallback()])
  
subject: Undo faulty change to many_ppo num_samples (#19388)