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) [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

• 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 implementation. If None, use the foreach implementation for CUDA and CPU native tensors and silently fall back to the slow implementation for other device types. Default: None

Returns

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

Return type

Tensor