code: def _stress_optimizer(
      self, model, optimizer, num_processes=1, iterations=100
  ):
      logger.info("_stress_optimizer begin")
      processes = []
      for rank in range(num_processes):
          p = mp.get_context("spawn").Process(
              name=f"Process-{rank}",
              target=do_optim,
              args=(model, optimizer, iterations, rank),
          )
          p.start()
          self.addCleanup(p.terminate)
          processes.append(p)
  
      for p in processes:
          p.join()
  
      logger.info("_stress_optimizer complete")
  
imports: import logging
  import os
  import unittest
  from unittest import main, TestCase
  import torch
  import torch.multiprocessing
  import torch.nn
  from torch.optim import Adagrad
  from torchbiggraph.async_adagrad import AsyncAdagrad
  from torchbiggraph.row_adagrad import RowAdagrad
label_desc: Use image node_id 1 for calling the TestOptimizers obj's underlying member method code with example usage: obj._stress_optimizer(model, optimizer, num_processes, iterations) without return types