code: def __init__(
      self,
      in_c,
      out_c,
      kernel_size=4,
      stride=2,
      padding=1,
      norm=nn.InstanceNorm2d,
      act=nn.ReLU,
  ):
      super(UpCNA, self).__init__()
      self.layer = nn.Sequential(
          nn.ConvTranspose2d(in_c, out_c, kernel_size, stride, padding),
          norm(out_c),
          act(True),
      )
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new UpCNA object from inherited base classes: nn with example: obj = UpCNA(in_c, out_c, kernel_size, stride, padding, norm, act)