code: def __init__(self, n_input, n_output, k_size):
      super(UpsampleConv, self).__init__()
  
      self.model = nn.Sequential(
          nn.PixelShuffle(2),
          nn.Conv2d(
              n_input,
              n_output,
              k_size,
              stride=1,
              padding=(k_size - 1) // 2,
              bias=True,
          ),
      )
  
imports: from torch import nn
label_desc: Use image node_id 1 to create a new UpsampleConv object from inherited base classes: nn with example: obj = UpsampleConv(n_input, n_output, k_size)