code: def forward(self, x):
      # Left branch
      y1 = self.sep_conv1(x)
      y2 = self.sep_conv2(x)
      # Right branch
      y3 = F.max_pool2d(x, kernel_size=3, stride=self.stride, padding=1)
      if self.stride == 2:
          y3 = self.bn1(self.conv1(y3))
      y4 = self.sep_conv3(x)
      # Concat & reduce channels
      b1 = F.relu(y1 + y2)
      b2 = F.relu(y3 + y4)
      y = torch.cat([b1, b2], 1)
      return F.relu(self.bn2(self.conv2(y)))
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the CellB obj's underlying member method code with example usage: obj.forward(x) and returns: F