code: def forward(self, net: Tensor) -> Tensor:
      hx = net
  
      hxin = self.rebnconvin(hx)
  
      hx1 = self.rebnconv1(hxin)
      hx2 = self.rebnconv2(hx1)
      hx3 = self.rebnconv3(hx2)
  
      hx4 = self.rebnconv4(hx3)
  
      hx3d = self.rebnconv3d(torch.cat((hx4, hx3), 1))
      hx2d = self.rebnconv2d(torch.cat((hx3d, hx2), 1))
      hx1d = self.rebnconv1d(torch.cat((hx2d, hx1), 1))
  
      return hx1d + hxin
  
imports: import torch
  import numpy
  import torch.nn
  import torch.nn.functional
  from PIL import Image
  from torch import Tensor
  from cftool.cv import to_rgb
  from torchvision.transforms.functional import normalize
  from ....misc.toolkit import download_model
label_desc: Use image node_id 2 for calling the RSU4F obj's underlying member method code with example usage: obj.forward(net) and returns: unknown