code: def forward(self, x):
      identity = x
      if self.downsample is not None:
          identity = self.downsample(x)
  
      out = self.conv1(x)
      out = self.bn1(out)
      out = self.relu(out)
  
      out = self.conv2(out)
      out = self.bn2(out)
      out = self.relu(out)
  
      out = self.conv3(out)
      out = self.bn3(out)
  
      out += identity
      out = self.relu(out)
  
      return out
  
file_path: deep-learning-for-image-processing/pytorch_classification/tensorboard_test/model.py
imports: import torch.nn
  import torch
label_desc: Use image node_id 2 for calling the Bottleneck obj's underlying member method code with example usage: obj.forward(x) and returns: out