Remove the deprecated decorator of KerasPruningCallback

optuna_integration/keras.py

@@ -3,7 +3,6 @@
 import warnings
 
 import optuna
-from optuna._deprecated import deprecated_class
 
 from optuna_integration._imports import try_import
 
@@ -14,19 +13,7 @@
 if not _imports.is_successful():
     Callback = object  # NOQA
 
-_keras_pruning_callback_deprecated_msg = (
-    "Recent Keras release (2.4.0) simply redirects "
-    "all APIs in the standalone keras package to point to tf.keras. "
-    "There is now only one Keras: tf.keras. "
-    "There may be some breaking changes for some workflows by upgrading to keras 2.4.0. "
-    "Test before upgrading. "
-    "REF: https://github.com/keras-team/keras/releases/tag/2.4.0. "
-    "There is an alternative callback function that can be used instead: "
-    ":class:`~optuna_integration.TFKerasPruningCallback`"
-)
 
-
-@deprecated_class("2.1.0", "4.0.0", text=_keras_pruning_callback_deprecated_msg)
 class KerasPruningCallback(Callback):
     """Keras callback to prune unpromising trials.
 

tests/test_keras.py

@@ -12,13 +12,15 @@
 with try_import():
     from keras import Sequential
     from keras.layers import Dense
+    from keras.layers import Input
 
 
 @pytest.mark.parametrize("interval, epochs", [(1, 1), (2, 1), (2, 2)])
 def test_keras_pruning_callback(interval: int, epochs: int) -> None:
     def objective(trial: optuna.trial.Trial) -> float:
         model = Sequential()
-        model.add(Dense(1, activation="sigmoid", input_dim=20))
+        model.add(Input(shape=(20,)))
+        model.add(Dense(1, activation="sigmoid"))
         model.compile(optimizer="rmsprop", loss="binary_crossentropy", metrics=["accuracy"])
         model.fit(
             np.zeros((16, 20), np.float32),