torch.nn.utils.clip_grad_norm_
torch.nn.utils.clip_grad_norm_(parameters, max_norm, norm_type=2.0, error_if_nonfinite=False, foreach=None)
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:
      * parameters (Iterable[Tensor] or Tensor) -- an
        iterable of Tensors or a single Tensor that will have
        gradients normalized
  * **max_norm** (*float*) -- max norm of the gradients

  * **norm_type** (*float*) -- 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 "parameters" is "nan",
    "inf", or "-inf". Default: False (will switch to True in the
    future)

  * **foreach** (*bool*) -- use the faster foreach-based
