code: def _group_norm_flops_compute(
      input: Tensor,
      num_groups: int,
      weight: Optional[Tensor] = None,
      bias: Optional[Tensor] = None,
      eps: float = 1e-5,
  ):
      has_affine = weight is not None
      # estimation
      return input.numel() * (5 if has_affine else 4), 0
  
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 15 for calling a global function with example usage: _group_norm_flops_compute(input, num_groups, weight, bias, eps) and returns: unknown,  int