code: def conv_flop_jit(inputs: List[Any], outputs: List[Any]):
      """
      Count flops for convolution.
      """
      x, w = inputs[:2]
      x_shape, w_shape, out_shape = (x.shape, w.shape, outputs[0].shape)
      transposed = inputs[6]
  
      return conv_flop_count(
          x_shape, w_shape, out_shape, transposed=transposed
      )
  
imports: import operator
  from collections import defaultdict
  from contextlib import contextmanager
  from enum import Enum, auto
  from functools import partial, reduce
  from typing import Any, Callable, List, Union
  import torch
  from torch.utils._pytree import tree_map
label_desc: Use image node_id 8 for calling a global function with example usage: conv_flop_jit(inputs, outputs) and returns: conv_flop_count