code: def forward(self, inputs):
      hd1, hd2, hd3, hd4, hd5 = inputs
      d5 = self.convup5(hd5)  # 16->256
      d4 = self.convup4(hd4)  # 32->256
      d3 = self.convup3(hd3)  # 64->256
      d2 = self.convup2(hd2)  # 128->256
      d1 = self.outconv1(hd1)  # 256
      return [d1, d2, d3, d4, d5]
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models.layers.layer_libs import SyncBatchNorm
  from paddleseg.cvlibs.param_init import kaiming_normal_init
label_desc: Use image node_id 2 for calling the DeepSup obj's underlying member method code with example usage: obj.forward(inputs) and returns: list