forked from 626_privacy/tensorflow_privacy
c8cb3c6b70
1. Rename PrivateQuery to DPQuery. 2. Move construction of DPQuery to outside of optimizer. 3. Remove PrivateAverageQuery and PrivateSumQuery, and rename DPQuery's 'get_query_result' method to 'get_noised_result'. Rename private_queries.py to dp_query.py. 4. Remove thrice-replicated run_query function from the test classes and replace with a single function in new test_utils.py. 5. Add functions gaussian_sum_query_from_noise_multplier and gaussian_average_query_from_noise_multplier. PiperOrigin-RevId: 230595991
93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
# Copyright 2018, The TensorFlow Authors.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
"""Tests for NoPrivacyAverageQuery."""
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
from absl.testing import parameterized
|
|
import tensorflow as tf
|
|
|
|
from privacy.optimizers import no_privacy_query
|
|
from privacy.optimizers import test_utils
|
|
|
|
|
|
class NoPrivacyQueryTest(tf.test.TestCase, parameterized.TestCase):
|
|
|
|
def test_no_privacy_sum(self):
|
|
with self.cached_session() as sess:
|
|
record1 = tf.constant([2.0, 0.0])
|
|
record2 = tf.constant([-1.0, 1.0])
|
|
|
|
query = no_privacy_query.NoPrivacySumQuery()
|
|
query_result = test_utils.run_query(query, [record1, record2])
|
|
result = sess.run(query_result)
|
|
expected = [1.0, 1.0]
|
|
self.assertAllClose(result, expected)
|
|
|
|
def test_no_privacy_weighted_sum(self):
|
|
with self.cached_session() as sess:
|
|
record1 = tf.constant([2.0, 0.0])
|
|
record2 = tf.constant([-1.0, 1.0])
|
|
|
|
weight1 = 1
|
|
weight2 = 2
|
|
|
|
query = no_privacy_query.NoPrivacySumQuery()
|
|
query_result = test_utils.run_query(
|
|
query, [record1, record2], [weight1, weight2])
|
|
result = sess.run(query_result)
|
|
expected = [0.0, 2.0]
|
|
self.assertAllClose(result, expected)
|
|
|
|
def test_no_privacy_average(self):
|
|
with self.cached_session() as sess:
|
|
record1 = tf.constant([5.0, 0.0])
|
|
record2 = tf.constant([-1.0, 2.0])
|
|
|
|
query = no_privacy_query.NoPrivacyAverageQuery()
|
|
query_result = test_utils.run_query(query, [record1, record2])
|
|
result = sess.run(query_result)
|
|
expected = [2.0, 1.0]
|
|
self.assertAllClose(result, expected)
|
|
|
|
def test_no_privacy_weighted_average(self):
|
|
with self.cached_session() as sess:
|
|
record1 = tf.constant([4.0, 0.0])
|
|
record2 = tf.constant([-1.0, 1.0])
|
|
|
|
weight1 = 1
|
|
weight2 = 3
|
|
|
|
query = no_privacy_query.NoPrivacyAverageQuery()
|
|
query_result = test_utils.run_query(
|
|
query, [record1, record2], [weight1, weight2])
|
|
result = sess.run(query_result)
|
|
expected = [0.25, 0.75]
|
|
self.assertAllClose(result, expected)
|
|
|
|
@parameterized.named_parameters(
|
|
('type_mismatch', [1.0], (1.0,), TypeError),
|
|
('too_few_on_left', [1.0], [1.0, 1.0], ValueError),
|
|
('too_few_on_right', [1.0, 1.0], [1.0], ValueError))
|
|
def test_incompatible_records(self, record1, record2, error_type):
|
|
query = no_privacy_query.NoPrivacySumQuery()
|
|
with self.assertRaises(error_type):
|
|
test_utils.run_query(query, [record1, record2])
|
|
|
|
|
|
if __name__ == '__main__':
|
|
tf.test.main()
|