code: def make_non_parallel_copy(model):
      """Make a non-data-parallel copy of the provided model.
  
      torch.nn.DataParallel instances are removed.
      """
  
      def replace_data_parallel(container):
          for name, module in container.named_children():
              if isinstance(module, nn.DataParallel):
                  setattr(container, name, module.module)
              if has_children(module):
                  replace_data_parallel(module)
  
      # Make a copy of the model, because we're going to change it
      new_model = deepcopy(model)
      if isinstance(new_model, nn.DataParallel):
          new_model = new_model.module
      replace_data_parallel(new_model)
  
      return new_model
  
imports: import argparse
  from collections import OrderedDict
  from copy import deepcopy
  import logging
  import operator
  import random
  import numpy
  import torch
  import torch.nn
  import torch.backends.cudnn
  import yaml
  import inspect
label_desc: Use image node_id 43 for calling a global function with example usage: make_non_parallel_copy(model) and returns: new_model