code: def forward(self, x0):
      h, w = x0.size()[-2:]
      paddingBottom = int(np.ceil(h / 64) * 64 - h)
      paddingRight = int(np.ceil(w / 64) * 64 - w)
      x0 = nn.ReplicationPad2d((0, paddingRight, 0, paddingBottom))(x0)
  
      x1 = self.m_head(x0)
      x2 = self.m_down1(x1)
      x3 = self.m_down2(x2)
      x4 = self.m_down3(x3)
      x = self.m_body(x4)
      x = self.m_up3(x + x4)
      x = self.m_up2(x + x3)
      x = self.m_up1(x + x2)
      x = self.m_tail(x + x1)
  
      x = x[..., :h, :w]
  
      return x
  
imports: import numpy
  import torch
  import torch.nn
  from einops import rearrange
  from einops.layers.torch import Rearrange
  from timm.models.layers import trunc_normal_, DropPath
label_desc: Use image node_id 2 for calling the SCUNet obj's underlying member method code with example usage: obj.forward(x0) and returns: x