code: def __init__(
      self, in_channels, out_channels, kernel_size=2, stride=2
  ):
      super(DeconvX2_Res, self).__init__()
  
      self.convx2_res = Conv2dX2_Res(
          in_channels, in_channels, kernel_size=3, padding=1
      )
      self.upsample = nn.Sequential(
          nn.ConvTranspose2d(
              in_channels,
              out_channels,
              kernel_size=kernel_size,
              stride=stride,
          ),
          nn.ReLU(inplace=True),
      )
  
imports: import torch
  import torch.nn
  import torch.nn.init
  import torch.nn.functional
  import numpy
label_desc: Use image node_id 1 to create a new DeconvX2_Res object from inherited base classes: nn with example: obj = DeconvX2_Res(in_channels, out_channels, kernel_size, stride)