code: def vae_kl_divergence(
      z_mean: tf.Tensor,
      z_log_var: tf.Tensor,
  ) -> tf.Tensor:
      """Compute the KL divergence loss for the VAE model.
  
      This function computes the KL divergence of the distribution generated by the
      VAE encoder and the gaussian. This is used as part of the training for
      the VAE model.
  
      Args:
        z_mean: Mean of the conditional distribution generated by the encoder.
        z_log_var: Log variance of the conditional distribution generated by the
          encoder.
  
      Returns:
        The loss tensor for the provided input.
      """
  
      kl_divergence = -0.5 * (
          1 + z_log_var - tf.square(z_mean) - tf.exp(z_log_var)
      )
      loss = tf.reduce_sum(kl_divergence)
      return loss
  
imports: from typing import Optional
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: vae_kl_divergence(z_mean, z_log_var) and returns: loss