code: def linear_flop_jit(inputs: List[Any], outputs: List[Any]) -> int:
      """
      Count flops for the aten::linear operator.
      """
      # Inputs is a list of length 3; unlike aten::addmm, it is the first
      # two elements that are relevant.
      input_shapes = [v.shape for v in inputs[0:2]]
      # input_shapes[0]: [dim0, dim1, ..., input_feature_dim]
      # input_shapes[1]: [output_feature_dim, input_feature_dim]
      assert input_shapes[0][-1] == input_shapes[1][-1]
      flops = reduce(operator.mul, input_shapes[0]) * input_shapes[1][0]
      return flops
  
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 5 for calling a global function with example usage: linear_flop_jit(inputs, outputs) and returns: flops