class_docstr: Clips gradient norm of a module's parameters.
  
  The norm is computed over all gradients together, as if they were
  concatenated into a single vector. Gradients are modified
  in-place.
  
  See :func:`torch.nn.utils.clip_grad_norm_` for more information.
  
  Parameters
  ----------
  gradient_clip_value : float (default=None)
    If not None, clip the norm of all model parameter gradients to this
    value. The type of the norm is determined by the
    ``gradient_clip_norm_type`` parameter and defaults to L2.
  
  gradient_clip_norm_type : float (default=2)
    Norm to use when gradient clipping is active. The default is
    to use L2-norm. Can be 'inf' for infinity norm.
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code: def on_grad_computed(self, _, named_parameters, **kwargs):
      if self.gradient_clip_value is None:
          return
  
      clip_grad_norm_(
          (p for _, p in named_parameters),
          max_norm=self.gradient_clip_value,
          norm_type=self.gradient_clip_norm_type,
      )
  
imports: from torch.nn.utils import clip_grad_norm_
  from skorch.callbacks import Callback
label_desc: Use image node_id 2 for calling the GradientNormClipping obj's underlying member method code with example usage: obj.on_grad_computed(_, named_parameters) without return types