forked from 626_privacy/tensorflow_privacy
e566967ff6
The global state for DP query is intended for aspects of the query that change across samples under the query's own control. It was therefore unnecessary to wrap "l2_norm_clip" and "sum_stddev" in the namedtuple _GlobalState for the basic GaussianQuery classes. PiperOrigin-RevId: 237528962
135 lines
4.8 KiB
Python
135 lines
4.8 KiB
Python
# Copyright 2018, The TensorFlow Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Tests for GaussianAverageQuery."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from absl.testing import parameterized
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import numpy as np
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from six.moves import xrange
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import tensorflow as tf
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from privacy.optimizers import gaussian_query
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from privacy.optimizers import test_utils
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class GaussianQueryTest(tf.test.TestCase, parameterized.TestCase):
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def test_gaussian_sum_no_clip_no_noise(self):
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with self.cached_session() as sess:
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record1 = tf.constant([2.0, 0.0])
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record2 = tf.constant([-1.0, 1.0])
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query = gaussian_query.GaussianSumQuery(
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l2_norm_clip=10.0, stddev=0.0)
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query_result = test_utils.run_query(query, [record1, record2])
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result = sess.run(query_result)
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expected = [1.0, 1.0]
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self.assertAllClose(result, expected)
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def test_gaussian_sum_with_clip_no_noise(self):
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with self.cached_session() as sess:
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record1 = tf.constant([-6.0, 8.0]) # Clipped to [-3.0, 4.0].
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record2 = tf.constant([4.0, -3.0]) # Not clipped.
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query = gaussian_query.GaussianSumQuery(
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l2_norm_clip=5.0, stddev=0.0)
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query_result = test_utils.run_query(query, [record1, record2])
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result = sess.run(query_result)
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expected = [1.0, 1.0]
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self.assertAllClose(result, expected)
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def test_gaussian_sum_with_changing_clip_no_noise(self):
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with self.cached_session() as sess:
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record1 = tf.constant([-6.0, 8.0]) # Clipped to [-3.0, 4.0].
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record2 = tf.constant([4.0, -3.0]) # Not clipped.
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l2_norm_clip = tf.Variable(5.0)
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l2_norm_clip_placeholder = tf.placeholder(tf.float32)
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assign_l2_norm_clip = tf.assign(l2_norm_clip, l2_norm_clip_placeholder)
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query = gaussian_query.GaussianSumQuery(
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l2_norm_clip=l2_norm_clip, stddev=0.0)
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query_result = test_utils.run_query(query, [record1, record2])
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self.evaluate(tf.global_variables_initializer())
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result = sess.run(query_result)
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expected = [1.0, 1.0]
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self.assertAllClose(result, expected)
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sess.run(assign_l2_norm_clip, {l2_norm_clip_placeholder: 0.0})
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result = sess.run(query_result)
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expected = [0.0, 0.0]
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self.assertAllClose(result, expected)
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def test_gaussian_sum_with_noise(self):
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with self.cached_session() as sess:
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record1, record2 = 2.71828, 3.14159
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stddev = 1.0
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query = gaussian_query.GaussianSumQuery(
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l2_norm_clip=5.0, stddev=stddev)
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query_result = test_utils.run_query(query, [record1, record2])
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noised_sums = []
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for _ in xrange(1000):
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noised_sums.append(sess.run(query_result))
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result_stddev = np.std(noised_sums)
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self.assertNear(result_stddev, stddev, 0.1)
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def test_gaussian_average_no_noise(self):
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with self.cached_session() as sess:
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record1 = tf.constant([5.0, 0.0]) # Clipped to [3.0, 0.0].
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record2 = tf.constant([-1.0, 2.0]) # Not clipped.
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query = gaussian_query.GaussianAverageQuery(
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l2_norm_clip=3.0, sum_stddev=0.0, denominator=2.0)
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query_result = test_utils.run_query(query, [record1, record2])
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result = sess.run(query_result)
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expected_average = [1.0, 1.0]
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self.assertAllClose(result, expected_average)
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def test_gaussian_average_with_noise(self):
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with self.cached_session() as sess:
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record1, record2 = 2.71828, 3.14159
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sum_stddev = 1.0
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denominator = 2.0
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query = gaussian_query.GaussianAverageQuery(
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l2_norm_clip=5.0, sum_stddev=sum_stddev, denominator=denominator)
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query_result = test_utils.run_query(query, [record1, record2])
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noised_averages = []
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for _ in range(1000):
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noised_averages.append(sess.run(query_result))
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result_stddev = np.std(noised_averages)
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avg_stddev = sum_stddev / denominator
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self.assertNear(result_stddev, avg_stddev, 0.1)
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@parameterized.named_parameters(
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('type_mismatch', [1.0], (1.0,), TypeError),
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('too_few_on_left', [1.0], [1.0, 1.0], ValueError),
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('too_few_on_right', [1.0, 1.0], [1.0], ValueError))
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def test_incompatible_records(self, record1, record2, error_type):
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query = gaussian_query.GaussianSumQuery(1.0, 0.0)
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with self.assertRaises(error_type):
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test_utils.run_query(query, [record1, record2])
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if __name__ == '__main__':
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tf.test.main()
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