this module.
  This method sets the parameters' "requires_grad" attributes in-
  place.

  This method is helpful for freezing part of the module for
  finetuning or training parts of a model individually (e.g., GAN
  training).

  See Locally disabling gradient computation for a comparison
  between *.requires_grad_()* and several similar mechanisms that
  may be confused with it.

  Parameters:
     **requires_grad** (*bool*) -- whether autograd should record
     operations on parameters in this module. Default: "True".

  Returns:
     self

  Return type:
     Module

save(f, _extra_files={})
  See "torch.jit.save" for details.

set_extra_state(state)
  This function is called from "load_state_dict()" to handle any
  extra state found within the *state_dict*. Implement this
  function and a corresponding "get_extra_state()" for your module
  if you need to store extra state within its *state_dict*.
