message: Update moving average docs.
  Fixes:
diff: @@ -1644,15 +1644,41 @@ def update_sub(x, decrement):
  @keras_export('keras.backend.moving_average_update')
  def moving_average_update(x, value, momentum):
  - """Compute the moving average of a variable.
  + """Compute the exponential moving average of a value.
  +
  + The moving average 'x' is updated with 'value' following:
  +
  + ```
  + x = x * momentum + value * (1 - momentum)
  + ```
  +
  + For example:
  +
  + >>> x = tf.Variable(0.0)
  + >>> momentum=0.9
  + >>> moving_average_update(x, value = 2.0, momentum=momentum).numpy()
  + >>> x.numpy()
  + 0.2
  +
  + The result will be biased towards the initial value of the variable.
  +
  + If the variable was initialized to zero, you can divide by
  + `1 - momentum ** num_updates` to debias it (Section 3 of
  + [Kingma et al., 2015](https://arxiv.org/abs/1412.6980)):
  +
  + >>> num_updates = 1.0
  + >>> x_zdb = x/(1 - momentum**num_updates)
  + >>> x_zdb.numpy()
  + 2.0
  Arguments:
  - x: A Variable.
  - value: A tensor with the same shape as `variable`.
  + x: A Variable, the moving average.
  + value: A tensor with the same shape as `x`, the new value to be
  + averaged in.
  momentum: The moving average momentum.
  Returns:
  - An Operation to update the variable.
  + The updated variable.
  """
  zero_debias = not tf2.enabled()
  return moving_averages.assign_moving_average(
  