code: def quant_conv_flop(inputs: List[Any], outputs: List[Any]):
      """
      Count flops for quantized convolution.
      """
      x, w = inputs[:2]
      x_shape, w_shape, out_shape = (
          get_shape(x),
          get_shape(w),
          get_shape(outputs[0]),
      )
  
      return conv_flop_count(
          x_shape, w_shape, out_shape, transposed=False
      )
  
imports: import os
  from collections import defaultdict
  from numbers import Number
  from typing import Any, List
  import torch
  from torch.utils._python_dispatch import TorchDispatchMode
  from torch.utils._pytree import tree_map
  from torchvision.models._api import Weights
label_desc: Use image node_id 8 for calling a global function with example usage: quant_conv_flop(inputs, outputs) and returns: conv_flop_count