code: def forward(self, x):
      out = x  # ;print('x    ',x.size())
      #
      down1, out = self.down1(out)  ##;print('down1',down1.size())  #256
      down2, out = self.down2(out)  # ;print('down2',down2.size())  #128
      down3, out = self.down3(out)  # ;print('down3',down3.size())  #64
      down4, out = self.down4(out)  # ;print('down4',down4.size())  #32
      down5, out = self.down5(out)  # ;print('down5',down5.size())  #16
      down6, out = self.down6(out)  # ;print('down6',down6.size())  #8
      pass  # ;print('out  ',out.size())
  
      out = self.center(out)
      out = self.up6(down6, out)
      out = self.up5(down5, out)
      out = self.up4(down4, out)
      out = self.up3(down3, out)
      out = self.up2(down2, out)
      out = self.up1(down1, out)
      # 1024
  
      out = self.classify(out)
      # out = torch.squeeze(out, dim=1)
      return out
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the UNet1024 obj's underlying member method code with example usage: obj.forward(x) and returns: out