def test_metrics(self):
class QueryWithMetric(dp_query.SumAggregationDPQuery):
def __init__(self, metric_val):
self._metric_val = metric_val
def derive_metrics(self, global_state):
return collections.OrderedDict(metric=self._metric_val)
query1 = QueryWithMetric(1)
query2 = QueryWithMetric(2)
query3 = QueryWithMetric(3)
nested_a = nested_query.NestedSumQuery(query1)
global_state = nested_a.initial_global_state()
metric_val = nested_a.derive_metrics(global_state)
self.assertEqual(metric_val['metric'], 1)
nested_b = nested_query.NestedSumQuery({
'key1': query1,
'key2': [query2, query3]
})
global_state = nested_b.initial_global_state()
metric_val = nested_b.derive_metrics(global_state)
self.assertEqual(metric_val['key1/metric'], 1)
self.assertEqual(metric_val['key2/0/metric'], 2)
self.assertEqual(metric_val['key2/1/metric'], 3)
def test_complex_nested_query(self):
with self.cached_session() as sess:
query_ab = gaussian_query.GaussianSumQuery(l2_norm_clip=1.0,
stddev=0.0)
query_c = gaussian_query.GaussianAverageQuery(l2_norm_clip=10.0,
sum_stddev=0.0,
denominator=2.0)
query_d = gaussian_query.GaussianSumQuery(l2_norm_clip=10.0,
stddev=0.0)
query = nested_query.NestedSumQuery(
[query_ab, {
'c': query_c,
'd': [query_d]
}])
record1 = [{
'a': 0.0,
'b': 2.71828
}, {
'c': (-4.0, 6.0),
'd': [-4.0]
}]
record2 = [{
'a': 3.14159,
'b': 0.0
}, {
'c': (6.0, -4.0),
'd': [5.0]
}]
query_result, _ = test_utils.run_query(query, [record1, record2])
result = sess.run(query_result)
expected = [{'a': 1.0, 'b': 1.0}, {'c': (1.0, 1.0), 'd': [1.0]}]
self.assertAllClose(result, expected)
def test_nested_query_with_noise(self):
with self.cached_session() as sess:
sum_stddev = 2.71828
denominator = 3.14159
query1 = gaussian_query.GaussianSumQuery(l2_norm_clip=1.5,
stddev=sum_stddev)
query2 = gaussian_query.GaussianAverageQuery(
l2_norm_clip=0.5,
sum_stddev=sum_stddev,
denominator=denominator)
query = nested_query.NestedSumQuery((query1, query2))
record1 = (3.0, [2.0, 1.5])
record2 = (0.0, [-1.0, -3.5])
query_result, _ = test_utils.run_query(query, [record1, record2])
noised_averages = []
for _ in range(1000):
noised_averages.append(tf.nest.flatten(sess.run(query_result)))
result_stddev = np.std(noised_averages, 0)
avg_stddev = sum_stddev / denominator
expected_stddev = [sum_stddev, avg_stddev, avg_stddev]
self.assertArrayNear(result_stddev, expected_stddev, 0.1)
def test_raises_with_non_sum(self):
class NonSumDPQuery(dp_query.DPQuery):
def initial_sample_state(self, template=None):
del template # Unused.
return None
def accumulate_preprocessed_record(self, sample_state,
preprocessed_record):
del sample_state, preprocessed_record # Unused.
return None
def merge_sample_states(self, sample_state_1, sample_state_2):
del sample_state_1, sample_state_2 # Unused.
return None
def get_noised_result(self, sample_state, global_state):
del sample_state, global_state # Unused.
return None
non_sum_query = NonSumDPQuery()
# This should work.
nested_query.NestedQuery(non_sum_query)
# This should not.
with self.assertRaises(TypeError):
nested_query.NestedSumQuery(non_sum_query)
def test_metrics(self):
class QueryWithMetric(dp_query.SumAggregationDPQuery):
def __init__(self, metric_val):
self._metric_val = metric_val
def initial_sample_state(self, template=None):
del template # Unused.
return None
def accumulate_preprocessed_record(self, sample_state,
preprocessed_record):
del sample_state, preprocessed_record # Unused.
return None
def merge_sample_states(self, sample_state_1, sample_state_2):
del sample_state_1, sample_state_2 # Unused.
return None
def get_noised_result(self, sample_state, global_state):
del sample_state, global_state # Unused.
return None
def derive_metrics(self, global_state):
return collections.OrderedDict(metric=self._metric_val)
query1 = QueryWithMetric(1)
query2 = QueryWithMetric(2)
query3 = QueryWithMetric(3)
nested_a = nested_query.NestedSumQuery(query1)
global_state = nested_a.initial_global_state()
metric_val = nested_a.derive_metrics(global_state)
self.assertEqual(metric_val['metric'], 1)
nested_b = nested_query.NestedSumQuery({
'key1': query1,
'key2': [query2, query3]
})
global_state = nested_b.initial_global_state()
metric_val = nested_b.derive_metrics(global_state)
self.assertEqual(metric_val['key1/metric'], 1)
self.assertEqual(metric_val['key2/0/metric'], 2)
self.assertEqual(metric_val['key2/1/metric'], 3)
def test_raises_with_non_sum(self):
class NonSumDPQuery(dp_query.DPQuery):
pass
non_sum_query = NonSumDPQuery()
# This should work.
nested_query.NestedQuery(non_sum_query)
# This should not.
with self.assertRaises(TypeError):
nested_query.NestedSumQuery(non_sum_query)
def test_nested_gaussian_sum_no_clip_no_noise(self):
with self.cached_session() as sess:
query1 = gaussian_query.GaussianSumQuery(l2_norm_clip=10.0, stddev=0.0)
query2 = gaussian_query.GaussianSumQuery(l2_norm_clip=10.0, stddev=0.0)
query = nested_query.NestedSumQuery([query1, query2])
record1 = [1.0, [2.0, 3.0]]
record2 = [4.0, [3.0, 2.0]]
query_result, _ = test_utils.run_query(query, [record1, record2])
result = sess.run(query_result)
expected = [5.0, [5.0, 5.0]]
self.assertAllClose(result, expected)
def test_nested_gaussian_average_with_clip_no_noise(self):
with self.cached_session() as sess:
query1 = gaussian_query.GaussianAverageQuery(l2_norm_clip=4.0,
sum_stddev=0.0,
denominator=5.0)
query2 = gaussian_query.GaussianAverageQuery(l2_norm_clip=5.0,
sum_stddev=0.0,
denominator=5.0)
query = nested_query.NestedSumQuery([query1, query2])
record1 = [1.0, [12.0, 9.0]] # Clipped to [1.0, [4.0, 3.0]]
record2 = [5.0, [1.0, 2.0]] # Clipped to [4.0, [1.0, 2.0]]
query_result, _ = test_utils.run_query(query, [record1, record2])
result = sess.run(query_result)
expected = [1.0, [1.0, 1.0]]
self.assertAllClose(result, expected)
def test_record_incompatible_with_query(self, queries, record, error_type):
with self.assertRaises(error_type):
test_utils.run_query(nested_query.NestedSumQuery(queries),
[record])
