code: def forward(self, x):
      x, conv2 = self.resnet_features(x)
      x1 = self.aspp1(x)
      x2 = self.aspp2(x)
      x3 = self.aspp3(x)
      x4 = self.aspp4(x)
      x5 = self.image_pool(x)
      x5 = F.interpolate(x5, size=x4.size()[2:], mode="nearest")
  
      x = torch.cat((x1, x2, x3, x4, x5), dim=1)
      x = self.fc1(x)
      x = F.interpolate(x, scale_factor=(4, 4), mode="bilinear")
  
      low_lebel_features = self.reduce_conv2(conv2)
  
      x = torch.cat((x, low_lebel_features), dim=1)
      x = self.last_conv(x)
      x = F.interpolate(x, scale_factor=(4, 4), mode="bilinear")
  
      return x
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision.models
label_desc: Use image node_id 2 for calling the DeepLabv3_plus obj's underlying member method code with example usage: obj.forward(x) and returns: x