code: def test_hasgrad(model, strict=False, verbose=False):
      """Tests if a pytorch module has got parameters with gradient equal to 0. Returns the
      ratio of parameters with 0 gradient against the total number of parameters
  
      Parameters
      ----------
      strict:
          If True then raises an error
      verbose:
          If True then displays all the parameter's names that have 0 gradient
      """
      count = 0
      total_params = 0
      for name, p in model.named_parameters():
          if p.requires_grad:
              total_params += 1
              assert p.grad is not None
              if torch.nonzero(p.grad, as_tuple=False).sum() == 0:
                  if verbose:
                      print("Param with name %s has 0 grad" % name)
                  count += 1
      if count > 0:
          msg = "Model has %.2f%% of parameters with 0 gradient" % (
              count / (1.0 * total_params)
          )
          if strict:
              raise ValueError(msg)
          else:
              return count / (1.0 * total_params)
      return 1
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_hasgrad(model, strict, verbose) and returns: int, unknown