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Code changes to get ready for an incoming Keras optimizer migration.

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Because the code subclasses the legacy Keras optimizer, we should explicitly use the legacy optimizer.

PiperOrigin-RevId: 473092233
This commit is contained in:
Chen Qian 2022-09-08 14:56:19 -07:00 committed by A. Unique TensorFlower
parent 407e5c8e11
commit 715fd1a670
2 changed files with 10 additions and 9 deletions
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15
tensorflow_privacy/privacy/optimizers/dp_optimizer_keras.py
View file

@ -20,11 +20,11 @@ from tensorflow_privacy.privacy.dp_query import gaussian_query
def make_keras_optimizer_class(cls): def make_keras_optimizer_class(cls):
"""Given a subclass of `tf.keras.optimizers.Optimizer`, returns a DP-SGD subclass of it. """Given a subclass of `tf.keras.optimizers.legacy.Optimizer`, returns a DP-SGD subclass of it.
Args: Args:
cls: Class from which to derive a DP subclass. Should be a subclass of cls: Class from which to derive a DP subclass. Should be a subclass of
`tf.keras.optimizers.Optimizer`. `tf.keras.optimizers.legacy.Optimizer`.
Returns: Returns:
A DP-SGD subclass of `cls`. A DP-SGD subclass of `cls`.
@ -123,11 +123,11 @@ def make_keras_optimizer_class(cls):
called `steps_per_epoch` times per epoch, and one call only returns called `steps_per_epoch` times per epoch, and one call only returns
`one_step_batch_size` (instead of `effective_batch_size`) examples now. `one_step_batch_size` (instead of `effective_batch_size`) examples now.
""".format( """.format(
base_class='tf.keras.optimizers.' + cls.__name__, base_class='tf.keras.optimizers.legacy' + cls.__name__,
short_base_class=cls.__name__, short_base_class=cls.__name__,
dp_keras_class='DPKeras' + cls.__name__) dp_keras_class='DPKeras' + cls.__name__)
# The class tf.keras.optimizers.Optimizer has two methods to compute # The class tf.keras.optimizers.legacy.Optimizer has two methods to compute
# gradients, `_compute_gradients` and `get_gradients`. The first works # gradients, `_compute_gradients` and `get_gradients`. The first works
# with eager execution, while the second runs in graph mode and is used # with eager execution, while the second runs in graph mode and is used
# by canned estimators. # by canned estimators.
@ -371,6 +371,7 @@ def make_keras_optimizer_class(cls):
DPKerasAdagradOptimizer = make_keras_optimizer_class( DPKerasAdagradOptimizer = make_keras_optimizer_class(
tf.keras.optimizers.Adagrad) tf.keras.optimizers.legacy.Adagrad)
DPKerasAdamOptimizer = make_keras_optimizer_class(tf.keras.optimizers.Adam) DPKerasAdamOptimizer = make_keras_optimizer_class(
DPKerasSGDOptimizer = make_keras_optimizer_class(tf.keras.optimizers.SGD) tf.keras.optimizers.legacy.Adam)
DPKerasSGDOptimizer = make_keras_optimizer_class(tf.keras.optimizers.legacy.SGD)

4
tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
View file

@ -369,12 +369,12 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
def testWriteOutAndReloadAdam(self): def testWriteOutAndReloadAdam(self):
optimizer_class = dp_optimizer.make_gaussian_optimizer_class( optimizer_class = dp_optimizer.make_gaussian_optimizer_class(
tf.keras.optimizers.Adam) tf.keras.optimizers.legacy.Adam)
self._test_write_out_and_reload(optimizer_class) self._test_write_out_and_reload(optimizer_class)
def testWriteOutAndReloadSGD(self): def testWriteOutAndReloadSGD(self):
optimizer_class = dp_optimizer.make_gaussian_optimizer_class( optimizer_class = dp_optimizer.make_gaussian_optimizer_class(
tf.keras.optimizers.SGD) tf.keras.optimizers.legacy.SGD)
self._test_write_out_and_reload(optimizer_class) self._test_write_out_and_reload(optimizer_class)