class_docstr: Function for fast gradient normalization.
  Typical use case is normalization for mle loss.
class_docstr_tok: ["Function","for","fast","gradient","normalization",".","Typical","use","case","is","normalization","for","mle","loss","."]
code: def backward(ctx, grad_output: torch.Tensor):
      return (
          grad_output
          - grad_output.sum(-1).unsqueeze(-1) * ctx.saved_tensors[0],
          None,
          None,
      )
  
file_path: NeMo/nemo/collections/asr/parts/k2/grad_utils.py
imports: import torch
  from nemo.collections.asr.parts.k2.utils import make_non_pad_mask
label_desc: Use image node_id 2 for calling the GradExpNormalize obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: unknown,  None,  None