code: def discriminator(self, imgs):
          
          nf = 64
          with argscope(Conv2D, kernel_size=4, strides=2):
              l = (LinearWrap(imgs)
                   .Conv2D('conv0', nf, activation=tf.nn.leaky_relu)
                   .Conv2D('conv1', nf * 2)
                   .BatchNorm('bn1')
                   .tf.nn.leaky_relu()
                   .Conv2D('conv2', nf * 4)
                   .BatchNorm('bn2')
                   .tf.nn.leaky_relu()
                   .Conv2D('conv3', nf * 8)
                   .BatchNorm('bn3')
                   .tf.nn.leaky_relu()
                   .FullyConnected('fct', 1)())
          return l
docs: return a (b, 1) logits