code: def _num_groups(num_channels, num_groups, group_size):
      if group_size:
          assert num_channels % group_size == 0
          return num_channels // group_size
      return num_groups
  
imports: from typing import Union, List, Optional, Any
  import torch
  from torch import nn
  from torch.nn import functional
  from torchvision.ops.misc import FrozenBatchNorm2d
  from .create_act import get_act_layer
  from .fast_norm import is_fast_norm, fast_group_norm, fast_layer_norm
  from .trace_utils import _assert
label_desc: Use image node_id 5 for calling a global function with example usage: _num_groups(num_channels, num_groups, group_size) and returns: num_groups, unknown