diff options
Diffstat (limited to 'searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp')
| -rw-r--r-- | searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp | 84 |
1 files changed, 14 insertions, 70 deletions
diff --git a/searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp b/searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp index 9b8ad0d26ce..a1b29c90986 100644 --- a/searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp +++ b/searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp @@ -76,10 +76,6 @@ namespace { const double sq_root_half = std::sqrt(0.5); } TEST(DistanceFunctionsTest, euclidean_gives_expected_score) { - auto ct = vespalib::eval::CellType::DOUBLE; - - auto euclid = make_distance_function(DistanceMetric::Euclidean, ct); - std::vector<double> p0{0.0, 0.0, 0.0}; std::vector<double> p1{1.0, 0.0, 0.0}; std::vector<double> p2{0.0, 1.0, 0.0}; @@ -92,6 +88,9 @@ TEST(DistanceFunctionsTest, euclidean_gives_expected_score) EXPECT_FLOAT_EQ(n4, 1.0); double d12 = computeEuclideanChecked(t(p1), t(p2)); EXPECT_EQ(d12, 2.0); + + EuclideanDistanceFunctionFactory<double> dff; + auto euclid = dff.for_query_vector(t(p0)); EXPECT_DOUBLE_EQ(euclid->to_rawscore(d12), 1.0/(1.0 + sqrt(2.0))); double threshold = euclid->convert_threshold(8.0); EXPECT_EQ(threshold, 64.0); @@ -142,10 +141,6 @@ TEST(DistanceFunctionsTest, euclidean_gives_expected_score) TEST(DistanceFunctionsTest, euclidean_int8_smoketest) { - auto ct = vespalib::eval::CellType::INT8; - - auto euclid = make_distance_function(DistanceMetric::Euclidean, ct); - std::vector<Int8Float> p0{0.0, 0.0, 0.0}; std::vector<Int8Float> p1{1.0, 0.0, 0.0}; std::vector<Int8Float> p5{0.0,-1.0, 0.0}; @@ -345,60 +340,10 @@ TEST(DistanceFunctionsTest, prenormalized_angular_gives_expected_score) EXPECT_DOUBLE_EQ(threshold, 1.0); } -TEST(DistanceFunctionsTest, innerproduct_gives_expected_score) -{ - auto ct = vespalib::eval::CellType::DOUBLE; - - auto innerproduct = make_distance_function(DistanceMetric::InnerProduct, ct); - - std::vector<double> p0{0.0, 0.0, 0.0}; - std::vector<double> p1{1.0, 0.0, 0.0}; - std::vector<double> p2{0.0, 1.0, 0.0}; - std::vector<double> p3{0.0, 0.0, 1.0}; - std::vector<double> p4{0.5, 0.5, sq_root_half}; - std::vector<double> p5{0.0,-1.0, 0.0}; - std::vector<double> p6{1.0, 2.0, 2.0}; - - double i12 = innerproduct->calc(t(p1), t(p2)); - double i13 = innerproduct->calc(t(p1), t(p3)); - double i23 = innerproduct->calc(t(p2), t(p3)); - EXPECT_DOUBLE_EQ(i12, 1.0); - EXPECT_DOUBLE_EQ(i13, 1.0); - EXPECT_DOUBLE_EQ(i23, 1.0); - - double i14 = innerproduct->calc(t(p1), t(p4)); - double i24 = innerproduct->calc(t(p2), t(p4)); - EXPECT_DOUBLE_EQ(i14, 0.5); - EXPECT_DOUBLE_EQ(i24, 0.5); - double i34 = innerproduct->calc(t(p3), t(p4)); - EXPECT_FLOAT_EQ(i34, 1.0 - sq_root_half); - - double i25 = innerproduct->calc(t(p2), t(p5)); - EXPECT_DOUBLE_EQ(i25, 2.0); - - double i44 = innerproduct->calc(t(p4), t(p4)); - EXPECT_GE(i44, 0.0); - EXPECT_LT(i44, 0.000001); - - double i66 = innerproduct->calc(t(p6), t(p6)); - EXPECT_GE(i66, 0.0); - EXPECT_LT(i66, 0.000001); - - double threshold = innerproduct->convert_threshold(0.25); - EXPECT_DOUBLE_EQ(threshold, 0.25); - threshold = innerproduct->convert_threshold(0.5); - EXPECT_DOUBLE_EQ(threshold, 0.5); - threshold = innerproduct->convert_threshold(1.0); - EXPECT_DOUBLE_EQ(threshold, 1.0); -} TEST(DistanceFunctionsTest, hamming_gives_expected_score) { - static HammingDistanceFunctionFactory<Int8Float> dff; - auto ct = vespalib::eval::CellType::DOUBLE; - - auto hamming = make_distance_function(DistanceMetric::Hamming, ct); - + static HammingDistanceFunctionFactory<double> dff; std::vector<std::vector<double>> points{{0.0, 0.0, 0.0}, {1.0, 0.0, 0.0}, @@ -407,31 +352,30 @@ TEST(DistanceFunctionsTest, hamming_gives_expected_score) {0.5, 0.5, 0.5}, {0.0,-1.0, 1.0}, {1.0, 1.0, 1.0}}; + auto hamming = dff.for_query_vector(t(points[0])); for (const auto & p : points) { - double h0 = hamming->calc(t(p), t(p)); - EXPECT_EQ(h0, 0.0); - EXPECT_EQ(hamming->to_rawscore(h0), 1.0); auto dist_fun = dff.for_query_vector(t(p)); - EXPECT_EQ(dist_fun->calc(t(p)), 0.0); + double h0 = dist_fun->calc(t(p)); + EXPECT_EQ(h0, 0.0); EXPECT_EQ(dist_fun->to_rawscore(h0), 1.0); } - double d12 = hamming->calc(t(points[1]), t(points[2])); + double d12 = dff.for_query_vector(t(points[1]))->calc(t(points[2])); EXPECT_EQ(d12, 3.0); EXPECT_DOUBLE_EQ(hamming->to_rawscore(d12), 1.0/(1.0 + 3.0)); - double d16 = hamming->calc(t(points[1]), t(points[6])); + double d16 = dff.for_query_vector(t(points[1]))->calc(t(points[6])); EXPECT_EQ(d16, 2.0); EXPECT_DOUBLE_EQ(hamming->to_rawscore(d16), 1.0/(1.0 + 2.0)); - double d23 = hamming->calc(t(points[2]), t(points[3])); + double d23 = dff.for_query_vector(t(points[2]))->calc(t(points[3])); EXPECT_EQ(d23, 3.0); EXPECT_DOUBLE_EQ(hamming->to_rawscore(d23), 1.0/(1.0 + 3.0)); - double d24 = hamming->calc(t(points[2]), t(points[4])); + double d24 = dff.for_query_vector(t(points[2]))->calc(t(points[4])); EXPECT_EQ(d24, 3.0); EXPECT_DOUBLE_EQ(hamming->to_rawscore(d24), 1.0/(1.0 + 3.0)); - double d25 = hamming->calc(t(points[2]), t(points[5])); + double d25 = dff.for_query_vector(t(points[2]))->calc(t(points[5])); EXPECT_EQ(d25, 1.0); EXPECT_DOUBLE_EQ(hamming->to_rawscore(d25), 1.0/(1.0 + 1.0)); @@ -445,8 +389,8 @@ TEST(DistanceFunctionsTest, hamming_gives_expected_score) std::vector<Int8Float> bytes_a = { 0, 1, 2, 4, 8, 16, 32, 64, -128, 0, 1, 2, 4, 8, 16, 32, 64, -128, 0, 1, 2 }; std::vector<Int8Float> bytes_b = { 1, 2, 2, 4, 8, 16, 32, 65, -128, 0, 1, 0, 4, 8, 16, 32, 64, -128, 0, 1, -1 }; // expect diff: 1 2 1 1 7 - EXPECT_EQ(hamming->calc(TypedCells(bytes_a), TypedCells(bytes_b)), 12.0); - auto dist_fun = dff.for_query_vector(TypedCells(bytes_a)); + HammingDistanceFunctionFactory<Int8Float> factory_int8; + auto dist_fun = factory_int8.for_query_vector(TypedCells(bytes_a)); EXPECT_EQ(dist_fun->calc(TypedCells(bytes_b)), 12.0); } |