Python 试图构建我的第一个GAN，但收到错误：预期ndim=3，发现ndim=2

这是我的密码：

#reshape from (samples, timesteps) to (samples, timesteps, n_features)
X=X.reshape((X.shape[0],X.shape[1],n_features))
print(X.shape)

#Define the univariate vanilla LSTM discriminator model
def define_discriminator(n_steps):    
    model = Sequential()
    model.add(LSTM(50, activation='relu', input_shape=(n_steps, 1)))
    model.add(Dense(1, activation='sigmoid'))
    #compile model
    model.compile(optimizer='adam', loss='binary_crossentropy',metrics=['accuracy'])
    return model
   
discriminator=define_discriminator(5)


#Define the generator model
def define_generator(latent_dim,n_outputs=2):
    model = Sequential()
    model.add(Dense(15, activation='relu', input_dim=latent_dim))
    model.add(Dense(n_outputs, activation='linear'))
    return model

generator=define_generator(5)


#Define the combined generator and discriminator model for updating the generator
def define_gan(generator,discriminator):
    # make weights in the discriminator not trainable
    discriminator.trainable = False
    # connect them
    model = Sequential()
    # add generator
    model.add(generator)
    # add the discriminator
    model.add(discriminator)
    # compile model
    model.compile(loss='binary_crossentropy', optimizer='adam')
    return model
    

当我尝试运行此函数时，我从define\u gan函数的“model.add（discriminator）”部分得到了以下错误：

预期ndim=3，发现ndim=2。收到完整形状：[无，2]

我假设这与发电机输出的形状有关，但我不确定如何检查或解决这个问题。有什么建议吗

谢谢

请创建一个最小的示例并提供完整的错误消息。