Add better error message for LossScaleOptimizer AttributeError.

Before, the error message would be something like "LossScaleOptimizer object has no attribute _hyper", even if the accessed attribute was not _hyper.

PiperOrigin-RevId: 258462751

tensorflow/python/keras/mixed_precision/experimental/loss_scale_optimizer.py

@@ -136,6 +136,9 @@ class LossScaleOptimizer(optimizer_v2.OptimizerV2):
     self._track_trackable(self._optimizer, 'base_optimizer')
     self._track_trackable(self._loss_scale, 'loss_scale')
 
+    # Needed because the superclass's __getattribute__ checks this.
+    self._hyper = {}
+
   @property
   def loss_scale(self):
     """The `LossScale` instance associated with this optimizer."""

tensorflow/python/keras/mixed_precision/experimental/loss_scale_optimizer_test.py

@@ -265,10 +265,14 @@ class LossScaleOptimizerTest(test.TestCase, parameterized.TestCase):
     opt.beta_1  # pylint: disable=pointless-statement
     opt = loss_scale_optimizer.LossScaleOptimizer(opt, loss_scale=10.)
     # Test that attributes defined by OptimizerV2 subclasses are not exposed in
-    # LossScaleOptimizer.
-    with self.assertRaises(AttributeError):
+    # LossScaleOptimizer, and that the error message is sensible.
+    with self.assertRaisesRegexp(
+        AttributeError,
+        "'LossScaleOptimizer' object has no attribute 'epsilon'"):
       opt.epsilon  # pylint: disable=pointless-statement
-    with self.assertRaises(AttributeError):
+    with self.assertRaisesRegexp(
+        AttributeError,
+        "'LossScaleOptimizer' object has no attribute 'beta_1'"):
       opt.beta_1  # pylint: disable=pointless-statement
 
   @test_util.run_in_graph_and_eager_modes