Cherrypick for cl/482011499: Throw error on deprecated fields. (#17179)

* Throw error on deprecated fields.

PiperOrigin-RevId: 482011499

* copyedits

Co-authored-by: Chen Qian <chenmoney@google.com>
Co-authored-by: François Chollet <francois.chollet@gmail.com>

Author: 3 people

keras/optimizers/optimizer_experimental/optimizer.py

@@ -101,18 +101,25 @@ def _create_iteration_variable(self):
     def _process_kwargs(self, kwargs):
         # Remove the `is_legacy_optimizer` arg, which is for serialization only.
         kwargs.pop("is_legacy_optimizer", None)
+        lr = kwargs.pop("lr", None)
+        if lr:
+            logging.warning(
+                "`lr` is deprecated, please use "
+                "`learning_rate` instead, or use the legacy optimizer, e.g.,"
+                f"tf.keras.optimizers.legacy.{self.__class__.__name__}."
+            )
         legacy_kwargs = {
-            "lr",
             "decay",
-            "gradient_transformers",
             "gradient_aggregator",
+            "gradient_transformers",
         }
         for k in kwargs:
             if k in legacy_kwargs:
-                logging.warning(
-                    "%s is deprecated in `optimizer_experimental.Optimizer`"
-                    ", please check the docstring for valid arguments.",
-                    k,
+                raise ValueError(
+                    f"{k} is deprecated in the new Keras optimizer, please"
+                    "check the docstring for valid arguments, or use the "
+                    "legacy optimizer, e.g., "
+                    f"tf.keras.optimizers.legacy.{self.__class__.__name__}."
                 )
             else:
                 raise TypeError(

keras/optimizers/optimizer_experimental/optimizer_test.py

@@ -4,11 +4,9 @@
 """
 
 import os
-import re
 
 import numpy as np
 import tensorflow.compat.v2 as tf
-from absl import logging
 from absl.testing import parameterized
 
 import keras
@@ -209,14 +207,9 @@ def testClipGlobalNorm(self):
         clipped_grad = optimizer._clip_gradients(grad)
         self.assertAllClose(clipped_grad[0], [0.5, 0.5])
 
-    def testPassingLegacyArgsRaiseWarning(self):
-        with self.assertLogs(level="WARNING") as log_output:
-            logging.set_verbosity(logging.WARNING)
+    def testPassingLegacyArgsRaiseError(self):
+        with self.assertRaisesRegex(ValueError, "decay is deprecated*"):
             _ = adam_new.Adam(clipnorm=1, decay=0.5)
-            expected_log = "decay is deprecated in"
-            output = log_output[0][0].message
-
-            self.assertTrue(re.search(expected_log, output))
 
     def testPassingLegacyClipnorm(self):
         optimizer = adam_new.Adam(clipnorm=1)