def test_without_noise(self):
with patch("pipeline_dp.dp_computations.add_noise_vector",
new=mock_add_noise_vector):
params = dp_computations.AdditiveVectorNoiseParams(
eps_per_coordinate=0,
delta_per_coordinate=0,
max_norm=0,
l0_sensitivity=0,
linf_sensitivity=0,
norm_kind="linf",
noise_kind=pipeline_dp.NoiseKind.GAUSSIAN)
vec_sum_accumulator = accumulator.VectorSummationAccumulator(
params=params, values=[(1, 2), (3, 4), (5, 6)])
self.assertEqual(tuple(vec_sum_accumulator.compute_metrics()),
(9, 12))
vec_sum_accumulator.add_value((7, 8))
self.assertTrue(
np.all(vec_sum_accumulator.compute_metrics() == np.array(
[16, 20])))
vec_sum_accumulator_2 = accumulator.VectorSummationAccumulator(
params=params, values=[(1, 2), (1, 4), (1, 8), (1, 16)])
vec_sum_accumulator.add_accumulator(vec_sum_accumulator_2)
self.assertEqual(tuple(vec_sum_accumulator.compute_metrics()),
(20, 50))
def test_merge_accumulators(self):
mean_accumulator1 = MeanAccumulator(params=[], values=[15])
mean_accumulator2 = MeanAccumulator(params=[], values=[5])
merged_accumulator = accumulator.merge(
[mean_accumulator1, mean_accumulator2])
self.assertEqual(merged_accumulator.compute_metrics(), 10)
vec_params = dp_computations.AdditiveVectorNoiseParams(
eps_per_coordinate=0,
delta_per_coordinate=0,
max_norm=0,
l0_sensitivity=0,
linf_sensitivity=0,
norm_kind="linf",
noise_kind=pipeline_dp.NoiseKind.GAUSSIAN)
vec_sum_accumulator1 = accumulator.VectorSummationAccumulator(
params=vec_params, values=[(15, 2)])
vec_sum_accumulator2 = accumulator.VectorSummationAccumulator(
params=vec_params, values=[(27, 40)])
merged_accumulator = accumulator.merge(
[vec_sum_accumulator1, vec_sum_accumulator2])
with patch("pipeline_dp.dp_computations.add_noise_vector",
new=mock_add_noise_vector):
self.assertEqual(tuple(merged_accumulator.compute_metrics()),
(42, 42))
def test_merge_diff_type_throws_type_error(self):
mean_accumulator1 = MeanAccumulator(params=[], values=[15])
sum_squares_acc = SumOfSquaresAccumulator(params=[], values=[1])
vec_params = dp_computations.AdditiveVectorNoiseParams(
eps_per_coordinate=0,
delta_per_coordinate=0,
max_norm=0,
l0_sensitivity=0,
linf_sensitivity=0,
norm_kind="linf",
noise_kind=pipeline_dp.NoiseKind.GAUSSIAN)
vec_sum_accumulator = accumulator.VectorSummationAccumulator(
params=vec_params, values=[(27, 40)])
with self.assertRaises(TypeError) as context:
accumulator.merge([mean_accumulator1, sum_squares_acc])
self.assertIn("The accumulator to be added is not of the same type"
"", str(context.exception))
with self.assertRaises(TypeError) as context:
accumulator.merge([vec_sum_accumulator, sum_squares_acc])
self.assertIn("The accumulator to be added is not of the same type"
"", str(context.exception))