code: def forward(self, inputs_):
      down1, down1_pool = self.down1(inputs_)
  
      downs = [down1]
  
      # execute down nodes
      prev_down_pool = down1_pool
      for i in range(2, self.n_stacks + 1):
          layer_name = "down" + str(i)
          layer = getattr(self, layer_name)
          down, prev_down_pool = layer(prev_down_pool)
          downs.append(down)
  
      center = self.center(prev_down_pool)
  
      # excute up nodes
      prev = center
      for i in range(self.n_stacks):
          n = self.n_stacks - i
          matching_down = downs.pop()
          layer_name = "up" + str(n)
          layer = getattr(self, layer_name)
          prev = layer(prev, matching_down)
  
      x = self.classify(prev)
  
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the UNet_stack obj's underlying member method code with example usage: obj.forward(inputs_) and returns: x