code: def forward(self, input):
      conv1 = self.conv_layer1_1(input)
      conv2 = self.conv_layer1_2(conv1)
  
      la1 = self.la1(conv2)
  
      tr1 = self.tr1([la1])
      st2 = self.st2(tr1)
  
      tr2 = self.tr2(st2)
      st3 = self.st3(tr2)
  
      tr3 = self.tr3(st3)
      st4 = self.st4(tr3)
  
      last_cls = self.last_cls(st4)
  
      y = last_cls[0]
      for idx in range(3):
          y = paddle.add(
              last_cls[idx + 1], self.cls_head_conv_list[idx](y)
          )
  
      y = self.conv_last(y)
      feature = self.pool2d_avg(y)
      y = paddle.reshape(feature, shape=[-1, feature.shape[1]])
      y = self.out(y)
      return y, feature
  
imports: import os
  import math
  from typing import Union
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import paddlehub.vision.transforms
  import numpy
  from paddle.nn.initializer import Uniform
  from paddle import ParamAttr
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.cv_module import ImageClassifierModule
label_desc: Use image node_id 3 for calling the HRNet40 obj's underlying member method code with example usage: obj.forward(input) and returns: y,  feature