torch.nn.utils.clip_grad_norm_(parameters, max_norm, norm_type=2.0, error_if_nonfinite=False)[source]

Clips gradient norm of an iterable of parameters.

The norm is computed over all gradients together, as if they were concatenated into a single vector. Gradients are modified in-place.

  • parameters (Iterable[Tensor] or Tensor) – an iterable of Tensors or a single Tensor that will have gradients normalized

  • max_norm (float or int) – max norm of the gradients

  • norm_type (float or int) – type of the used p-norm. Can be 'inf' for infinity norm.

  • error_if_nonfinite (bool) – if True, an error is thrown if the total norm of the gradients from :attr:parameters is nan, inf, or -inf. Default: False (will switch to True in the future)


Total norm of the parameters (viewed as a single vector).


Access comprehensive developer documentation for PyTorch

View Docs


Get in-depth tutorials for beginners and advanced developers

View Tutorials


Find development resources and get your questions answered

View Resources