code: def run(self):
      self.opt["no_cuda"] = True
      if (
          "ordered" not in self.opt["datatype"]
          and "train" in self.opt["datatype"]
      ):
          self.opt["datatype"] = self.opt["datatype"] + ":ordered"
      agent = create_agent(self.opt)
      agent.opt.log()
      num_examples = self.opt["num_examples"]
      field = self.opt["field"] + "_vec"
      if num_examples < 0:
          num_examples = float("inf")
      assert self.opt["batchsize"] == 1
      assert isinstance(agent, TorchAgent)
  
      world = create_task(self.opt, agent)
      teacher = world.get_task_agent()
  
      # set up logging
      log_every_n_secs = self.opt.get("log_every_n_secs", -1)
      if log_every_n_secs <= 0:
          log_every_n_secs = float("inf")
      log_time = TimeLogger()
  
      lengths = []
  
      cnt = 0
      total = min(teacher.num_examples(), num_examples)
      while not teacher.epoch_done() and cnt < num_examples:
          act = teacher.act()
          processed = agent.observe(act)
          try:
              text_vec = processed[field]
          except KeyError:
              raise KeyError(f"Pick one of {list(processed.keys())}")
          if text_vec is not None and (
              not self.opt["final_only"] or act.get("episode_done")
          ):
              cnt += 1
              lengths.append(float(len(text_vec)))
          agent.self_observe({})
  
          if log_time.time() > log_every_n_secs:
              report = self._compute_stats(lengths)
              text, report = log_time.log(report["exs"], total, report)
              logging.info(text)
  
      report = self._compute_stats(lengths)
      print(nice_report(report))
      return report
  
file_path: ParlAI/parlai/scripts/token_stats.py
imports: import numpy
  from parlai.core.script import ParlaiScript, register_script
  from parlai.core.agents import create_agent
  from parlai.core.torch_agent import TorchAgent
  from parlai.core.worlds import create_task
  from parlai.core.params import ParlaiParser
  from parlai.utils.misc import TimeLogger, nice_report
  import parlai.utils.logging
label_desc: Use image node_id 3 for calling the TokenStats obj's underlying member method code with example usage: obj.run() and returns: report