code: def forward(self, input):
      output1 = self.level1(input)  # x2
  
      output2_0 = self.level2_0(output1)  # x4
      for i, layer in enumerate(self.level2):
          if i == 0:
              output2 = layer(output2_0)
          else:
              output2 = layer(output2)
  
      output3_0 = self.level3_0(
          self.BR2(paddle.concat([output2_0, output2], 1))
      )  # x8
      for i, layer in enumerate(self.level3):
          if i == 0:
              output3 = layer(output3_0)
          else:
              output3 = layer(output3)
  
      output3_cat = self.BR3(paddle.concat([output3_0, output3], 1))
      classifier = self.classifier(output3_cat)
      return classifier
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the SINetEncoder obj's underlying member method code with example usage: obj.forward(input) and returns: classifier