code: def copy_cmax_grad_from_paras(para_list):
      res = []
      for para in para_list:
          if para.input_quant.clip.clip_value_max.grad is not None:
              grad = (
                  para.input_quant.clip.clip_value_max.grad.data.clone()
                  .detach()
                  .contiguous()
              )
          else:
              grad = torch.zeros_like(para)
          res.append(grad)
  
      return [torch.Tensor(res)]
  
imports: import random
  import time
  from collections import OrderedDict
  import numpy
  import torch
label_desc: Use image node_id 7 for calling a global function with example usage: copy_cmax_grad_from_paras(para_list) and returns: list