code: def _einsum_flops_compute(equation, *operands):
      """
      Count flops for the einsum operation.
      """
      equation = equation.replace(" ", "")
      input_shapes = [o.shape for o in operands]
  
      # Re-map equation so that same equation with different alphabet
      # representations will look the same.
      letter_order = OrderedDict(
          (k, 0) for k in equation if k.isalpha()
      ).keys()
      mapping = {ord(x): 97 + i for i, x in enumerate(letter_order)}
      equation = equation.translate(mapping)
  
      np_arrs = [np.zeros(s) for s in input_shapes]
      optim = np.einsum_path(equation, *np_arrs, optimize="optimal")[1]
      for line in optim.split("\n"):
          if "optimized flop" in line.lower():
              flop = int(float(line.split(":")[-1]))
              return flop, 0
      raise NotImplementedError("Unsupported einsum operation.")
  
imports: import time
  import torch
  import torch.nn
  import torch.nn.functional
  from functools import partial
  from typing import List, Optional
  from collections import OrderedDict
  import numpy
label_desc: Use image node_id 23 for calling a global function with example usage: _einsum_flops_compute(equation) and returns: flop,  int