code: def _train_reg_model(model, use_fp16=False):
      model = copy.deepcopy(model)
      model = model.cuda()
      optimizer = torch.optim.SGD(model.parameters(), lr=0.001)
      return _train(model, optimizer, use_fp16)
  
file_path: fairscale/tests/nn/pipe/test_parity.py
imports: import contextlib
  import copy
  import numpy
  import pytest
  import torch
  from fairscale.fair_dev.testing.testing import skip_if_single_gpu
  from fairscale.nn import Pipe
label_desc: Use image node_id 5 for calling a global function with example usage: _train_reg_model(model, use_fp16) and returns: _train