code: def __init__(
      self,
      in_chs,
      out_chs,
      kernel_size,
      stride=1,
      pad_type="",
      act_layer=nn.ReLU,
      norm_layer=nn.BatchNorm2d,
      norm_kwargs=None,
  ):
      super(ConvBnAct, self).__init__()
      assert stride in [1, 2]
      norm_kwargs = norm_kwargs or {}
      self.conv = select_conv2d(
          in_chs, out_chs, kernel_size, stride=stride, padding=pad_type
      )
      self.bn1 = norm_layer(out_chs, **norm_kwargs)
      self.act1 = act_layer(inplace=True)
  
imports: import re
  from copy import deepcopy
  from .conv2d_layers import *
  from geffnet.activations import *
label_desc: Use image node_id 1 to create a new ConvBnAct object from inherited base classes: nn with example: obj = ConvBnAct(in_chs, out_chs, kernel_size, stride, pad_type, act_layer, norm_layer, norm_kwargs)