Unable to train model in Variational Autoencoders.ipynb about autoencoders HOT 2 OPEN

def vae_loss(x, x_decoded_mean):
    xent_loss = original_dim * binary_crossentropy(x, x_decoded_mean)
    kl_loss = - 0.5 * K.sum(1 + z_log_var - K.square(z_mean) - K.exp(z_log_var), axis=-1)
    return K.mean(xent_loss + kl_loss)

vae = Model(x, x_decoded_mean)
vae.compile(optimizer='rmsprop', loss = vae_loss)
vae.summary()

vae = Model(x, x_decoded_mean)

xent_loss = original_dim * binary_crossentropy(x, x_decoded_mean)
kl_loss = - 0.5 * K.sum(1 + z_log_var - K.square(z_mean) - K.exp(z_log_var), axis=-1)
vae_loss = K.mean(xent_loss + kl_loss)

vae.add_loss(vae_loss)
vae.compile(optimizer='rmsprop')
vae.summary()