code: def forward(self, x):
      x = self.conv1(x)
      x = self.bn1(x)
      x = self.relu(x)
      x = self.maxpool(x)
  
      x = self.layer1(x)
      x = self.layer2(x)
      x = self.layer3(x)
      x = self.layer4(x)
  
      if self.include_top:
          x = self.avgpool(x)
          x = torch.flatten(x, 1)
          x = self.fc(x)
  
      return x
  
file_path: deep-learning-for-image-processing/pytorch_classification/Test5_resnet/model.py
imports: import torch.nn
  import torch
label_desc: Use image node_id 3 for calling the ResNet obj's underlying member method code with example usage: obj.forward(x) and returns: x