code: def forward(self, inputs: paddle.Tensor) -> paddle.Tensor:
      y = self.conv1_1(inputs)
      y = self.conv1_2(y)
      y = self.conv1_3(y)
      y = self.pool2d_max(y)
      feat_list = []
      for stage in self.stage_list:
          for block in stage:
              y = block(y)
          feat_list.append(y)
      return feat_list
  
file_path: PaddleHub/modules/image/semantic_segmentation/ginet_resnet101vd_voc/resnet.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import ginet_resnet101vd_voc.layers
label_desc: Use image node_id 2 for calling the ResNet101_vd obj's underlying member method code with example usage: obj.forward(inputs) and returns: feat_list