code: def forward(self, x):
      x = self.conv0_1(x)
      x = self.bn0_1(x)
      x = self.relu(x)
      x = self.conv0_2(x)
      x = self.bn0_2(x)
      x = self.relu(x)
  
      x = self.maxpool1(x)
      x = self.layer1(x)
      x = self.conv1(x)
      x = self.bn1(x)
      x = self.relu(x)
  
      x = self.maxpool2(x)
      x = self.layer2(x)
      x = self.conv2(x)
      x = self.bn2(x)
      x = self.relu(x)
  
      x = self.maxpool3(x)
      x = self.layer3(x)
      x = self.conv3(x)
      x = self.bn3(x)
      x = self.relu(x)
  
      x = self.layer4(x)
      x = self.conv4_1(x)
      x = self.bn4_1(x)
      x = self.relu(x)
      x = self.conv4_2(x)
      x = self.bn4_2(x)
      x = self.relu(x)
  
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.init
  import torchvision
  from torchvision import models
  from collections import namedtuple
  from packaging import version
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