code: def forward(self, inputs):
      h1 = self.conv1(inputs)  # h1->320*320*64
      h2 = self.poolconv2(h1)  # h2->160*160*128
      h3 = self.poolconv3(h2)  # h3->80*80*256
      h4 = self.poolconv4(h3)  # h4->40*40*512
      hd5 = self.poolconv5(h4)  # h5->20*20*1024
      return [h1, h2, h3, h4, hd5]
  
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 Encoder obj's underlying member method code with example usage: obj.forward(inputs) and returns: list