code: def update_parameters(optimizer: torch.optim.Optimizer) -> None:
      optimizer.step()
      optimizer.zero_grad()
  
imports: import copy
  import os
  import tempfile
  from typing import Any, Dict, List, Tuple, Type
  import unittest
  import pytest
  import torch
  from torch import nn
  import torch.distributed
  import torch.nn.functional
  import fairscale.experimental.nn.data_parallel.gossip
  from fairscale.fair_dev.testing.testing import skip_if_single_gpu, spawn_for_all_world_sizes
label_desc: Use image node_id 3 for calling a global function with example usage: update_parameters(optimizer) without return types