parameters: (
          parameters: _tensor_or_tensors, max_norm: float, norm_type: float = 2.,
          error_if_nonfinite: bool = False)
return_statement: return clip_grad_norm_(parameters, max_norm, norm_type, error_if_nonfinite)
docstring: r"""Clips gradient norm of an iterable of parameters.
  
      .. warning::
          This method is now deprecated in favor of
          :func:`torch.nn.utils.clip_grad_norm_`.
docstring_summary: r"""Clips gradient norm of an iterable of parameters.
docstring_tokens: r Clips gradient norm of an iterable of parameters .
function: def clip_grad_norm(
          parameters: _tensor_or_tensors, max_norm: float, norm_type: float = 2.,
          error_if_nonfinite: bool = False) -> torch.Tensor:
      r"""Clips gradient norm of an iterable of parameters.
  
      .. warning::
          This method is now deprecated in favor of
          :func:`torch.nn.utils.clip_grad_norm_`.
      """
      warnings.warn("torch.nn.utils.clip_grad_norm is now deprecated in favor "
                    "of torch.nn.utils.clip_grad_norm_.", stacklevel=2)
      return clip_grad_norm_(parameters, max_norm, norm_type, error_if_nonfinite)
function_tokens: def clip_grad_norm ( parameters : _tensor_or_tensors , max_norm : float , norm_type : float = 2. , error_if_nonfinite : bool = False ) -> torch . Tensor : warnings . warn ( "torch.nn.utils.clip_grad_norm is now deprecated in favor " "of torch.nn.utils.clip_grad_norm_." , stacklevel = 2 ) return clip_grad_norm_ ( parameters , max_norm , norm_type , error_if_nonfinite )