code: def __init__(self, in_chs, norm_layer=BatchNormAct2d):
      super(CatBnAct, self).__init__()
      self.bn = norm_layer(in_chs, eps=0.001)
  
imports: from collections import OrderedDict
  from functools import partial
  from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DPN_MEAN, IMAGENET_DPN_STD, IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import BatchNormAct2d, ConvNormAct, create_conv2d, create_classifier, get_norm_act_layer
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 to create a new CatBnAct object from inherited base classes: nn with example: obj = CatBnAct(in_chs, norm_layer)