code: def normalization(channels):
      """
      Make a standard normalization layer.
  
      :param channels: number of input channels.
      :return: an nn.Module for normalization.
      """
      return GroupNorm32(32, channels)
  
file_path: PaddleHub/modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/nn.py
imports: import math
  import paddle
  import paddle.nn
label_desc: Use image node_id 8 for calling a global function with example usage: normalization(channels) and returns: GroupNorm32