code: def forward(self, inputs_):
      x1 = self.stack1(inputs_)
      x3 = self.stack3(inputs_)
      x5 = self.stack5(inputs_)
      x_pool = self.stack_pool(inputs_)
  
      x = torch.cat([x1, x3, x5, x_pool], dim=1)
      x = self.reducer(x)
  
      if self.pool:
          return x, self.pool(x)
  
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the UNetDownStack obj's underlying member method code with example usage: obj.forward(inputs_) and returns: x, x,  self