Example #1
0
    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))
Example #2
0
    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))
Example #3
0
    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))