class_docstr:     Callback for valuate the performance of the model.
  Args:
      actor_num_params: The number of parameters of the actor model.
      critic_num_params: The number of parameters of the critic model.
      initial_model_num_params: The number of parameters of the initial model.
      reward_model_num_params: The number of parameters of the reward model.
      enable_grad_checkpoint: Whether to enable gradient checkpointing.
      ignore_episodes: The number of episodes to ignore when calculating the performance.
code: def on_episode_start(self, episode: int) -> None:
      self.disable = (
          self.ignore_episodes > 0 and episode < self.ignore_episodes
      )
      if self.disable:
          return
      self.overall_timer.start()
  
imports: from time import time
  from typing import Optional
  import torch
  import torch.distributed
  from coati.experience_maker import Experience
  from .base import Callback
label_desc: Use image node_id 2 for calling the PerformanceEvaluator obj's underlying member method code with example usage: obj.on_episode_start(episode) without return types