code: def bmm_flop_jit(inputs: List[Any], outputs: List[Any]) -> int:
      """
      Count flops for the bmm operation.
      """
      # Inputs should be a list of length 2.
      # Inputs contains the shapes of two tensor.
      assert len(inputs) == 2, len(inputs)
      input_shapes = [v.shape for v in inputs]
      n, c, t = input_shapes[0]
      d = input_shapes[-1][-1]
      flops = n * c * t * d
      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 6 for calling a global function with example usage: bmm_flop_jit(inputs, outputs) and returns: flops