class_docstr: Upscaling then double conv
code: def __init__(self, in_channels, out_channels, bilinear=True):
      super().__init__()
      if bilinear:
          self.up = nn.Upsample(
              scale_factor=2, mode="bilinear", align_corners=True
          )
          self.conv = DoubleConv(
              in_channels, out_channels, in_channels // 2
          )
      else:
          self.up = nn.ConvTranspose2d(
              in_channels, in_channels // 2, kernel_size=2, stride=2
          )
          self.conv = DoubleConv(in_channels, out_channels)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new Up object from inherited base classes: nn with example: obj = Up(in_channels, out_channels, bilinear)