code: def get_latent_pred_loss(latents_pred, latents_discrete_hot, hparams):
    
    latents_logits = tf.layers.dense(
        latents_pred, 2**hparams.bottleneck_bits, name="extra_logits")
    loss = tf.nn.softmax_cross_entropy_with_logits_v2(
        labels=tf.stop_gradient(latents_discrete_hot), logits=latents_logits)
    return loss
docs: Latent prediction and loss.