class_docstr: Simulate training updates.
class_docstr_tok: ["Simulate","training","updates","."]
code: def train_step(self, batch):
      ret = super().train_step(batch)
      update_freq = self.opt.get("update_freq", 1)
      if update_freq == 1:
          self._number_training_updates += 1
      else:
          self._number_grad_accum = (
              self._number_grad_accum + 1
          ) % update_freq
          self._number_training_updates += int(
              self._number_grad_accum == 0
          )
      return ret
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.torch_agent import TorchAgent, Output
  import torch
  from parlai.core.agents import Agent
label_desc: Use image node_id 1 for calling the MockTrainUpdatesAgent obj's underlying member method code with example usage: obj.train_step(batch) and returns: ret