The norm is computed over all gradients together, as if they were
concatenated into a single vector. Gradients are modified in-place.
Usage
nn_utils_clip_grad_norm_(parameters, max_norm, norm_type = 2)
Arguments
- parameters
(IterableTensor 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.
Value
Total norm of the parameters (viewed as a single vector).