Update to the latest version of Google DP library (#442)

* update commit

* compilation fix

* compilation fix

* test fixes

* Fix style in partition_selection.py

* Fix style in partition_selection.py

Author: dvadym

prereqs_linux.sh

@@ -60,7 +60,7 @@ git submodule update --init --recursive
 
 
 # checkout out to particular commit
-cd third_party/differential-privacy && git checkout d93052f71960cefc533b64c7201a35fce2deeb9e && \
+cd third_party/differential-privacy && git checkout 2a1e55484aeb9ca444a3b34dcf128d454e80f255 && \
 cd -
 # renaming workspace.bazel to workspace
 mv third_party/differential-privacy/cc/WORKSPACE.bazel third_party/differential-privacy/cc/WORKSPACE

prereqs_mac.sh

@@ -49,7 +49,7 @@ fi
 git submodule update --init --recursive
 
 # checkout out to particular commit
-cd third_party/differential-privacy && git checkout d93052f71960cefc533b64c7201a35fce2deeb9e && \
+cd third_party/differential-privacy && git checkout 2a1e55484aeb9ca444a3b34dcf128d454e80f255 && \
 cd -
 # renaming workspace.bazel to workspace
 mv third_party/differential-privacy/cc/WORKSPACE.bazel third_party/differential-privacy/cc/WORKSPACE
@@ -61,4 +61,4 @@ rm -rf third_party/differential-privacy/java third_party/differential-privacy/ex
 rm -rf third_party/differential-privacy/go third_party/differential-privacy/examples/go
 
 # Removing the Privacy on Beam part
-rm -rf third_party/differential-privacy/privacy-on-beam
+rm -rf third_party/differential-privacy/privacy-on-beam

src/bindings/PyDP/algorithms/distributions.cpp

@@ -24,15 +24,10 @@ class declareLaplaceDistributionClass {
              py::arg("epsilon") = 0., py::arg("sensitivity"))
         .def("get_uniform_double", &dpi::LaplaceDistribution::GetUniformDouble,
              R"pbdoc(Returns a uniform random integer of in range [0, 2^53).)pbdoc")
-        .def("sample", py::overload_cast<double>(&dpi::LaplaceDistribution::Sample),
-             py::arg("scale") = 1.0,
+        .def("sample", &dpi::LaplaceDistribution::Sample,
              R"pbdoc(
-                         Samples the Laplacian distribution Laplace(u, scale*b).
-
-                         Parameters
-                         ----------
-                         scale
-                              A factor to scale b.
+                         Samples the Laplacian distribution Laplace(u, b).
+                        
                     )pbdoc");
     laplace_dist.def("get_diversity", &dpi::LaplaceDistribution::GetDiversity,
                      R"pbdoc(

src/pydp/algorithms/partition_selection.py

@@ -22,7 +22,7 @@ def should_keep(self, num_users: int) -> bool:
         """
         Decides whether or not to keep a partition with `num_users` based on differential privacy parameters and strategy.
         """
-        ...
+        raise NotImplementedError("PartitionSelectionStrategy is an abstract class.")
 
 
 def create_partition_strategy(

tests/algorithms/test_distributions.py

@@ -63,7 +63,7 @@ def test_diversity_getter(self):
     def test_check_statistics_for_geo_unit_values(self):
 
         ld = LaplaceDistribution(epsilon=1.0, sensitivity=1.0)
-        samples = [ld.sample(scale=1.0) for _ in range(k_num_geometric_samples)]
+        samples = [ld.sample() for _ in range(k_num_geometric_samples)]
         mean = dp.util.mean(samples)
         var = dp.util.variance(samples)
 
@@ -88,14 +88,9 @@ def test_LaplaceDistributionTypes(self):
         sud = ld.get_uniform_double()
         assert isinstance(sud, float)
         lds = ld.sample()
-        lds1 = ld.sample(4.0)
         assert isinstance(lds, float)
-        assert isinstance(lds1, float)
         ldg = ld.get_diversity()
         assert isinstance(ldg, float)
-        # TODO
-        # lcdf = ld.cdf(2.0, 0.5)
-        # assert isinstance(lcdf, float)
 
 
 class TestGaussianDistributionDataTypes:
@@ -104,9 +99,7 @@ def test_GaussianDistributionTypes(self):
         assert isinstance(gd, GaussianDistribution)
 
         gds = gd.sample()
-        gds1 = gd.sample(1.0)
         assert isinstance(gds, float)
-        assert isinstance(gds1, float)
         gdstd = gd.stddev
         assert isinstance(gdstd, float)
 

tests/algorithms/test_partition_selection.py

@@ -89,7 +89,7 @@ def test_laplace_keep_and_return_noised_value(
         ],
         [
             (10, 1, 1e-5, 1, 0.017845473615190732),
-            (1100, 0.2, 1e-7, 10, 0.007884076914531857),
+            (1100, 0.2, 1e-7, 10, 1.0),
         ],
     )
     def test_gaussian_keep_and_return_noised_value(