code: def __init__(self, in_chs, activation_fn=nn.ReLU(inplace=True)):
      super(CatBnAct, self).__init__()
      self.bn = nn.BatchNorm2d(in_chs, eps=0.001)
      self.act = activation_fn
  
imports: import os
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.model_zoo
  from collections import OrderedDict
  from .adaptive_avgmax_pool import adaptive_avgmax_pool2d
  from .convert_from_mxnet import convert_from_mxnet, has_mxnet
label_desc: Use image node_id 1 to create a new CatBnAct object from inherited base classes: nn with example: obj = CatBnAct(in_chs, activation_fn)