code: def forward(
      self, x: paddle.Tensor, short_cuts: List
  ) -> paddle.Tensor:
      for i in range(len(short_cuts)):
          x = self.up_sample_list[i](x, short_cuts[-(i + 1)])
      return x
  
imports: import os
  from typing import Union, List, Tuple
  import paddle
  from paddle import nn
  import paddle.nn.functional
  import numpy
  from paddlehub.module.module import moduleinfo
  import paddlehub.vision.segmentation_transforms
  from paddlehub.module.cv_module import ImageSegmentationModule
  import unet_cityscapes.layers
label_desc: Use image node_id 2 for calling the Decoder obj's underlying member method code with example usage: obj.forward(x, short_cuts) and returns: x