code: def __init__(
      self,
      in_chan,
      out_chan,
      ks=3,
      stride=1,
      padding=1,
      *args,
      **kwargs,
  ):
      super(ConvBNReLU, self).__init__()
      self.conv = nn.Conv2d(
          in_chan,
          out_chan,
          kernel_size=ks,
          stride=stride,
          padding=padding,
          bias=False,
      )
      self.bn = nn.BatchNorm2d(out_chan)
      self.init_weight()
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from ParsingResnet import Resnet18
label_desc: Use image node_id 1 to create a new ConvBNReLU object from inherited base classes: nn with example: obj = ConvBNReLU(in_chan, out_chan, ks, stride, padding)