code: def group_dequantize_tensor_from_qparams(
      w_int32, scales, zeros, n_bit=4, groupsize=128
  ):
      assert groupsize > 1
      # needed for GPTQ single column dequantize
      if groupsize > w_int32.shape[-1] and scales.shape[-1] == 1:
          groupsize = w_int32.shape[-1]
      assert w_int32.shape[-1] % groupsize == 0
      assert w_int32.dim() == 2
  
      w_int32_grouped = w_int32.reshape(-1, groupsize)
      scales = scales.reshape(-1, 1)
      zeros = zeros.reshape(-1, 1)
  
      w_dq = (
          w_int32_grouped.sub(2 ** (n_bit - 1))
          .mul(scales)
          .add(zeros)
          .reshape_as(w_int32)
      )
      return w_dq
  
imports: import time
  from pathlib import Path
  import torch
  import torch.nn
  import torch.nn.functional
  from sentencepiece import SentencePieceProcessor
  from model import Transformer
label_desc: Use image node_id 7 for calling a global function with example usage: group_dequantize_tensor_from_qparams(w_int32, scales, zeros, n_bit, groupsize) and returns: w_dq