code: def __init__(self):
      super().__init__()
      self.input = torch.randn(1, 4, 9, 9)
      self.vision_modules = nn.ModuleList(
          [
              nn.PixelShuffle(2),
              nn.PixelUnshuffle(3),
              nn.Upsample(scale_factor=2, mode="nearest"),
              nn.Upsample(scale_factor=2, mode="bilinear"),
              nn.Upsample(scale_factor=2, mode="bicubic"),
              nn.UpsamplingNearest2d(scale_factor=2),
              nn.UpsamplingBilinear2d(scale_factor=2),
          ]
      )
      self.linear_sample = nn.Upsample(scale_factor=2, mode="linear")
      self.trilinear_sample = nn.Upsample(
          scale_factor=2, mode="trilinear"
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new NNVisionModule object from inherited base classes: torch.nn with example: obj = NNVisionModule()