code: def forward(self, x):
      residual = x
      out = self.relu(self.bn1(self.conv1(x)))
      out = self.relu(self.bn2(self.conv2(out)))
      out = self.bn3(self.conv3(out))
      if self.downsample is not None:
          residual = self.downsample(x)
      out += residual
      return self.relu(out)
  
file_path: avalanche/avalanche/models/resnet32.py
imports: import torch.nn
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: self