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Expose differentially private RMSPropOptimizer.

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PiperOrigin-RevId: 311072544
This commit is contained in:
A. Unique TensorFlower 2020-05-12 00:09:05 -07:00
parent 10335f6177
commit da9fb28b37
2 changed files with 20 additions and 6 deletions
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3
tensorflow_privacy/privacy/optimizers/dp_optimizer.py
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@ -228,12 +228,15 @@ def make_gaussian_optimizer_class(cls):
AdagradOptimizer = tf.train.AdagradOptimizer AdagradOptimizer = tf.train.AdagradOptimizer
AdamOptimizer = tf.train.AdamOptimizer AdamOptimizer = tf.train.AdamOptimizer
GradientDescentOptimizer = tf.train.GradientDescentOptimizer GradientDescentOptimizer = tf.train.GradientDescentOptimizer
RMSPropOptimizer = tf.train.RMSPropOptimizer
DPAdagradOptimizer = make_optimizer_class(AdagradOptimizer) DPAdagradOptimizer = make_optimizer_class(AdagradOptimizer)
DPAdamOptimizer = make_optimizer_class(AdamOptimizer) DPAdamOptimizer = make_optimizer_class(AdamOptimizer)
DPGradientDescentOptimizer = make_optimizer_class(GradientDescentOptimizer) DPGradientDescentOptimizer = make_optimizer_class(GradientDescentOptimizer)
DPRMSPropOptimizer = make_optimizer_class(RMSPropOptimizer)
DPAdagradGaussianOptimizer = make_gaussian_optimizer_class(AdagradOptimizer) DPAdagradGaussianOptimizer = make_gaussian_optimizer_class(AdagradOptimizer)
DPAdamGaussianOptimizer = make_gaussian_optimizer_class(AdamOptimizer) DPAdamGaussianOptimizer = make_gaussian_optimizer_class(AdamOptimizer)
DPGradientDescentGaussianOptimizer = make_gaussian_optimizer_class( DPGradientDescentGaussianOptimizer = make_gaussian_optimizer_class(
GradientDescentOptimizer) GradientDescentOptimizer)
DPRMSPropGaussianOptimizer = make_gaussian_optimizer_class(RMSPropOptimizer)

23
tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
View file

@ -48,7 +48,13 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
('DPAdagrad 4', dp_optimizer.DPAdagradOptimizer, 4, [-2.5, -2.5]), ('DPAdagrad 4', dp_optimizer.DPAdagradOptimizer, 4, [-2.5, -2.5]),
('DPAdam 1', dp_optimizer.DPAdamOptimizer, 1, [-2.5, -2.5]), ('DPAdam 1', dp_optimizer.DPAdamOptimizer, 1, [-2.5, -2.5]),
('DPAdam 2', dp_optimizer.DPAdamOptimizer, 2, [-2.5, -2.5]), ('DPAdam 2', dp_optimizer.DPAdamOptimizer, 2, [-2.5, -2.5]),
('DPAdam 4', dp_optimizer.DPAdamOptimizer, 4, [-2.5, -2.5])) ('DPAdam 4', dp_optimizer.DPAdamOptimizer, 4, [-2.5, -2.5]),
('DPRMSPropOptimizer 1', dp_optimizer.DPRMSPropOptimizer, 1,
[-2.5, -2.5]),
('DPRMSPropOptimizer 2', dp_optimizer.DPRMSPropOptimizer, 2,
[-2.5, -2.5]),
('DPRMSPropOptimizer 4', dp_optimizer.DPRMSPropOptimizer, 4, [-2.5, -2.5])
)
def testBaseline(self, cls, num_microbatches, expected_answer): def testBaseline(self, cls, num_microbatches, expected_answer):
with self.cached_session() as sess: with self.cached_session() as sess:
var0 = tf.Variable([1.0, 2.0]) var0 = tf.Variable([1.0, 2.0])
@ -76,7 +82,8 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
@parameterized.named_parameters( @parameterized.named_parameters(
('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer), ('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer),
('DPAdagrad', dp_optimizer.DPAdagradOptimizer), ('DPAdagrad', dp_optimizer.DPAdagradOptimizer),
('DPAdam', dp_optimizer.DPAdamOptimizer)) ('DPAdam', dp_optimizer.DPAdamOptimizer),
('DPRMSPropOptimizer', dp_optimizer.DPRMSPropOptimizer))
def testClippingNorm(self, cls): def testClippingNorm(self, cls):
with self.cached_session() as sess: with self.cached_session() as sess:
var0 = tf.Variable([0.0, 0.0]) var0 = tf.Variable([0.0, 0.0])
@ -99,7 +106,8 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
@parameterized.named_parameters( @parameterized.named_parameters(
('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer), ('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer),
('DPAdagrad', dp_optimizer.DPAdagradOptimizer), ('DPAdagrad', dp_optimizer.DPAdagradOptimizer),
('DPAdam', dp_optimizer.DPAdamOptimizer)) ('DPAdam', dp_optimizer.DPAdamOptimizer),
('DPRMSPropOptimizer', dp_optimizer.DPRMSPropOptimizer))
def testNoiseMultiplier(self, cls): def testNoiseMultiplier(self, cls):
with self.cached_session() as sess: with self.cached_session() as sess:
var0 = tf.Variable([0.0]) var0 = tf.Variable([0.0])
@ -182,7 +190,8 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
@parameterized.named_parameters( @parameterized.named_parameters(
('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer), ('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer),
('DPAdagrad', dp_optimizer.DPAdagradOptimizer), ('DPAdagrad', dp_optimizer.DPAdagradOptimizer),
('DPAdam', dp_optimizer.DPAdamOptimizer)) ('DPAdam', dp_optimizer.DPAdamOptimizer),
('DPRMSPropOptimizer', dp_optimizer.DPRMSPropOptimizer))
def testUnrollMicrobatches(self, cls): def testUnrollMicrobatches(self, cls):
with self.cached_session() as sess: with self.cached_session() as sess:
var0 = tf.Variable([1.0, 2.0]) var0 = tf.Variable([1.0, 2.0])
@ -213,7 +222,8 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
@parameterized.named_parameters( @parameterized.named_parameters(
('DPGradientDescent', dp_optimizer.DPGradientDescentGaussianOptimizer), ('DPGradientDescent', dp_optimizer.DPGradientDescentGaussianOptimizer),
('DPAdagrad', dp_optimizer.DPAdagradGaussianOptimizer), ('DPAdagrad', dp_optimizer.DPAdagradGaussianOptimizer),
('DPAdam', dp_optimizer.DPAdamGaussianOptimizer)) ('DPAdam', dp_optimizer.DPAdamGaussianOptimizer),
('DPRMSPropOptimizer', dp_optimizer.DPRMSPropGaussianOptimizer))
def testDPGaussianOptimizerClass(self, cls): def testDPGaussianOptimizerClass(self, cls):
with self.cached_session() as sess: with self.cached_session() as sess:
var0 = tf.Variable([0.0]) var0 = tf.Variable([0.0])
@ -241,7 +251,8 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
@parameterized.named_parameters( @parameterized.named_parameters(
('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer), ('DPGradientDescent', dp_optimizer.DPGradientDescentOptimizer),
('DPAdagrad', dp_optimizer.DPAdagradOptimizer), ('DPAdagrad', dp_optimizer.DPAdagradOptimizer),
('DPAdam', dp_optimizer.DPAdamOptimizer)) ('DPAdam', dp_optimizer.DPAdamOptimizer),
('DPRMSPropOptimizer', dp_optimizer.DPRMSPropOptimizer))
def testAssertOnNoCallOfComputeGradients(self, cls): def testAssertOnNoCallOfComputeGradients(self, cls):
dp_sum_query = gaussian_query.GaussianSumQuery(1.0e9, 0.0) dp_sum_query = gaussian_query.GaussianSumQuery(1.0e9, 0.0)
opt = cls(dp_sum_query, num_microbatches=1, learning_rate=1.0) opt = cls(dp_sum_query, num_microbatches=1, learning_rate=1.0)