我将 WGAN-GP 扩展为从此处找到的代码库有条件： https ://github.com/eriklindernoren/Keras-GAN/blob/master/wgan_gp/wgan_gp.py
当我训练模型时，它似乎不受标签的限制。这就是我构建模型的方式。
# The generator takes noise and the target label (states) as input
# and generates the corresponding samples of that label
noise = Input(shape=(self.latent_size, ), name="noise")
label = Input(shape=(self.label_size, ), name="labels")
real_samples = Input(shape=(self.input_size,), name="real")
self.discriminator = self.build_discriminator()
self.generator = self.build_generator([noise, label])
# First we train the discriminator
self.generator.trainable = False
fake_samples = self.generator([noise, label])
fake = self.discriminator([fake_samples, label])
valid = self.discriminator([real_samples, label])
interpolated = Lambda(self.random_weighted_average)([real_samples, fake_samples])
valid_interp = self.discriminator([interpolated, label])
self.d_model = Model([real_samples, noise, label],
[valid, fake, valid_interp],
name="discriminator")
# Time to train the generator
self.discriminator.trainable = False
self.generator.trainable = True
noise_gen = Input(shape=(self.latent_size,), name="noise_gen")
fake_samples = self.generator([noise_gen, label])
valid = self.discriminator([fake_samples, label])
self.g_model = Model([noise_gen, label], valid, name="generator")
self.g_model.compile(loss=self.wasserstein_loss, optimizer=optimizer)
绘制模型结果：
我不知道如何解释右侧的合并箭头。标签应该在鉴别器中连接。我有一种感觉，这条线搞砸了一些东西：
self.d_model = Model([real_samples, noise, label],
[valid, fake, valid_interp],
name="discriminator")
因为我只是传递标签，我不知道 Keras 如何将该输入路由到其他输出..