def _compute_log_acceptance_correction(current_momentums,
                                       proposed_momentums,
                                       independent_chain_ndims,
                                       name=None):
  """
  """
  with tf.compat.v1.name_scope(
      name, 'compute_log_acceptance_correction',
      [independent_chain_ndims, current_momentums, proposed_momentums]):
    log_current_kinetic, log_proposed_kinetic = [], []
    for current_momentum, proposed_momentum in zip(
        current_momentums, proposed_momentums):
      axis = tf.range(independent_chain_ndims, tf.rank(current_momentum))
      log_current_kinetic.append(_log_sum_sq(current_momentum, axis))
      log_proposed_kinetic.append(_log_sum_sq(proposed_momentum, axis))
    current_kinetic = 0.5 * tf.exp(
        tf.reduce_logsumexp(
            input_tensor=tf.stack(log_current_kinetic, axis=-1), axis=-1))
    proposed_kinetic = 0.5 * tf.exp(
        tf.reduce_logsumexp(
            input_tensor=tf.stack(log_proposed_kinetic, axis=-1), axis=-1))
    return mcmc_util.safe_sum([current_kinetic, -proposed_kinetic])