message: Set _HAS_AGGREGATE_GRAD in LossScaleOptimizer.
  This will fix once cherrypicked into 2.2.
diff: @@ -107,6 +107,8 @@ class LossScaleOptimizer(optimizer_v2.OptimizerV2):
  0.25
  """
  + _HAS_AGGREGATE_GRAD = True
  +
  def __init__(self, optimizer, loss_scale):
  """Initializes this loss scale optimizer.
  @@ -271,9 +273,12 @@ class LossScaleOptimizer(optimizer_v2.OptimizerV2):
  def _apply_gradients(self, grads, wrapped_vars, name,
  experimental_aggregate_gradients):
  + # TODO(reedwm): This will raise a fairly cryptic error message if
  + # self._optimizer.apply_gradients does not take
  + # experimental_aggregate_gradients.
  return self._optimizer.apply_gradients(
  list(zip(grads, wrapped_vars.value)), name,
  - experimental_aggregate_gradients)
  + experimental_aggregate_gradients=experimental_aggregate_gradients)
  def get_config(self):
  serialized_optimizer = optimizers.serialize(self._optimizer)
  