class_docstr: Single-GPU AlexNet without partition toward the channel axis.
code: def __call__(self, x, t):
      h = F.max_pooling_2d(
          F.local_response_normalization(F.relu(self.conv1(x))),
          3,
          stride=2,
      )
      h = F.max_pooling_2d(
          F.local_response_normalization(F.relu(self.conv2(h))),
          3,
          stride=2,
      )
      h = F.relu(self.conv3(h))
      h = F.relu(self.conv4(h))
      h = F.max_pooling_2d(F.relu(self.conv5(h)), 3, stride=2)
      h = F.dropout(F.relu(self.fc6(h)))
      h = F.dropout(F.relu(self.fc7(h)))
      h = self.fc8(h)
  
      loss = F.softmax_cross_entropy(h, t)
      chainer.report({"loss": loss, "accuracy": F.accuracy(h, t)}, self)
      return loss
  
imports: import chainer
  import chainer.functions
  import chainer.links
label_desc: Use image node_id 2 for calling the Alex obj's underlying member method code with example usage: obj.__call__(x, t) and returns: loss