return a (b, 1) logits

def discriminator(self, imgs):
        """ return a (b, 1) logits"""
        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