code: def forward(self, x):
      residual = x
      out = self.conv1(x)
      out = self.bn1(out)
      out = self.relu(out)
      out = self.conv2(out)
      out = self.bn2(out)
      if self.downsample:
          residual = self.downsample(x)
      out += residual
      out = self.relu(out)
      return out
  
file_path: pytorch-tutorial/tutorials/02-intermediate/deep_residual_network/main.py
imports: import torch
  import torch.nn
  import torchvision
  import torchvision.transforms
label_desc: Use image node_id 2 for calling the ResidualBlock obj's underlying member method code with example usage: obj.forward(x) and returns: out