docstr: Run one episode. The agent will tell each observer to run n_steps.
docstr_tok: ["Run","one","episode",".","The","agent","will","tell","each","observer","to","run","n_steps","."]
code: def run_episode(self, n_steps=0):
      r"""
      Run one episode. The agent will tell each observer to run n_steps.
      """
      futs = []
      for ob_rref in self.ob_rrefs:
          # make async RPC to kick off an episode on all observers
          futs.append(
              rpc_async(
                  ob_rref.owner(),
                  _call_method,
                  args=(
                      Observer.run_episode,
                      ob_rref,
                      self.agent_rref,
                      n_steps,
                  ),
              )
          )
  
      # wait until all observers have finished this episode
      for fut in futs:
          fut.wait()
  
imports: import numpy
  from itertools import count
  import torch
  import torch.distributed.rpc
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torch.distributed.rpc import RRef, rpc_sync, rpc_async, remote
  from torch.distributions import Categorical
  from torch.testing._internal.dist_utils import dist_init, worker_name
  from torch.testing._internal.distributed.rpc.rpc_agent_test_fixture import RpcAgentTestFixture
label_desc: Use image node_id 4 for calling the Agent obj's underlying member method code with example usage: obj.run_episode(n_steps) without return types