text: from network import Network
  
  
  class VGG16Adverserial100(Network):
      def setup_with_dropout(self,factor):
          (self.feed('data')
               .conv(3, 3, 64, 1, 1, name='conv1_1')
               .conv(3, 3, 64, 1, 1, name='conv1_2')
               .max_pool(2, 2, 2, 2, name='pool1')
               .conv(3, 3, 128, 1, 1, name='conv2_1')
               .conv(3, 3, 128, 1, 1, name='conv2_2')
               .max_pool(2, 2, 2, 2, name='pool2')
               .conv(3, 3, 256, 1, 1, name='conv3_1')
               .conv(3, 3, 256, 1, 1, name='conv3_2')
               .conv(3, 3, 256, 1, 1, name='conv3_3')
               .max_pool(2, 2, 2, 2, name='pool3')
               .conv(3, 3, 512, 1, 1, name='conv4_1')
               .conv(3, 3, 512, 1, 1, name='conv4_2')
               .conv(3, 3, 512, 1, 1, name='conv4_3')
               .max_pool(2, 2, 2, 2, name='pool4')
               .conv(3, 3, 512, 1, 1, name='conv5_1')
               .conv(3, 3, 512, 1, 1, name='conv5_2')
               .conv(3, 3, 512, 1, 1, name='conv5_3')
               .max_pool(2, 2, 2, 2, name='feat'))
  
          (self.feed('feat')
               .fc(512, name='fc6', with_bn=True)
               .fc(100, relu=False, name='fc7'))
  
          (self.feed('feat')
              .flip_grad(name='flip_grad',l=factor)
              .fc(512, name='adv_fc2',with_bn=True)
              .fc(2, relu=False, name='adv_fc3'))
  