message: added note about weights gradient in compute_weighted_loss
diff: @@ -157,6 +157,13 @@ def compute_weighted_loss(
  ValueError: If `weights` is `None` or the shape is not compatible with
  `losses`, or if the number of dimensions (rank) of either `losses` or
  `weights` is missing.
  +
  + Note:
  + When calculating the gradient of a weighted loss contributions from
  + both `losses` and `weights` are considered. If your `weights` depend
  + on some model parameters but you do not want this to affect the loss
  + gradient, you need to apply @{tf.stop_gradient} to `weights` before
  + passing them to `compute_weighted_loss`.
  """
  Reduction.validate(reduction)
  with ops.name_scope(scope, "weighted_loss", (losses, weights)):
  