def METHOD_NAME(model: nn.Module,
                                     input_signature: torch.Tensor,
                                     channel_divisible: int) -> None:
  logging.info("before padding:")
  profiler.model_complexity(
      model, input_signature, readable=True, print_model_analysis=True)
  expanding_runner = ExpandingRunner(model.cpu(), input_signature)
  expanded_model, _ = expanding_runner.expand(channel_divisible)
  logging.info("after padding:")
  profiler.model_complexity(
      expanded_model, input_signature, readable=True, print_model_analysis=True)