code: def __init__(
      self, in_channels, out_channels, kernel_size=3, padding=1
  ):
      super(Conv2dX2_Res, self).__init__()
  
      self.layer = nn.Sequential(
          nn.Conv2d(
              in_channels,
              out_channels,
              kernel_size=kernel_size,
              padding=padding,
          ),
          nn.BatchNorm2d(out_channels),
          nn.ReLU(inplace=True),
          nn.Conv2d(
              out_channels,
              out_channels,
              kernel_size=kernel_size,
              padding=padding,
          ),
      )
  
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 Conv2dX2_Res object from inherited base classes: nn with example: obj = Conv2dX2_Res(in_channels, out_channels, kernel_size, padding)