code: def forward(ctx, x, scale):
      ctx.scale = scale
      res = x.new(x)
      return res
  
imports: import logging
  from typing import List, Optional, Tuple
  import torch
  from torch import nn, Tensor
  from torch.nn import Module, Parameter
  from .wavlm_attention import WavLMSelfAttention
label_desc: Use image node_id 1 for calling the GradMultiply obj's underlying member method code with example usage: obj.forward(ctx, x, scale) and returns: res