fix NNS distance for new cell types

This reverts commit f167fe4362c5e4e20a7605b99205cfbee77c569a.

3 files changed, 8 insertions, 4 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 ee0a2aff80e..6f8c9b4c885 100644
--- a/searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp
+++ b/searchlib/src/tests/tensor/distance_functions/distance_functions_test.cpp
@@ -10,6 +10,7 @@
 LOG_SETUP("distance_function_test");
 
 using namespace search::tensor;
+using vespalib::eval::Int8Float;
 using vespalib::eval::TypedCells;
 using search::attribute::DistanceMetric;
 
@@ -212,6 +213,11 @@ TEST(DistanceFunctionsTest, hamming_gives_expected_score)
     EXPECT_DOUBLE_EQ(threshold, 0.5);
     threshold = hamming->convert_threshold(1.0);
     EXPECT_DOUBLE_EQ(threshold, 1.0);
+
+    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);
 }
 
 TEST(GeoDegreesTest, gives_expected_score)
diff --git a/searchlib/src/tests/tensor/hnsw_index/hnsw_index_test.cpp b/searchlib/src/tests/tensor/hnsw_index/hnsw_index_test.cpp
index 20dc55df329..6ffe118aa65 100644
--- a/searchlib/src/tests/tensor/hnsw_index/hnsw_index_test.cpp
+++ b/searchlib/src/tests/tensor/hnsw_index/hnsw_index_test.cpp
@@ -51,7 +51,6 @@ struct LevelGenerator : public RandomLevelGenerator {
 };
 
 using FloatVectors = MyDocVectorAccess<float>;
-using FloatSqEuclideanDistance = SquaredEuclideanDistance<float>;
 using HnswIndexUP = std::unique_ptr<HnswIndex>;
 
 class HnswIndexTest : public ::testing::Test {
@@ -79,7 +78,7 @@ public:
     void init(bool heuristic_select_neighbors) {
         auto generator = std::make_unique<LevelGenerator>();
         level_generator = generator.get();
-        index = std::make_unique<HnswIndex>(vectors, std::make_unique<FloatSqEuclideanDistance>(),
+        index = std::make_unique<HnswIndex>(vectors, std::make_unique<SquaredEuclideanDistance>(),
                                             std::move(generator),
                                             HnswIndex::Config(5, 2, 10, 0, heuristic_select_neighbors));
     }
diff --git a/searchlib/src/tests/tensor/hnsw_index/stress_hnsw_mt.cpp b/searchlib/src/tests/tensor/hnsw_index/stress_hnsw_mt.cpp
index 8e3bb95a776..7acdb4df983 100644
--- a/searchlib/src/tests/tensor/hnsw_index/stress_hnsw_mt.cpp
+++ b/searchlib/src/tests/tensor/hnsw_index/stress_hnsw_mt.cpp
@@ -117,7 +117,6 @@ public:
     }
 };
 
-using FloatSqEuclideanDistance = SquaredEuclideanDistance<float>;
 using HnswIndexUP = std::unique_ptr<HnswIndex>;
 
 class Stressor : public ::testing::Test {
@@ -232,7 +231,7 @@ public:
 
     void init() {
         uint32_t m = 16;
-        index = std::make_unique<HnswIndex>(vectors, std::make_unique<FloatSqEuclideanDistance>(),
+        index = std::make_unique<HnswIndex>(vectors, std::make_unique<SquaredEuclideanDistance>(),
                                             std::make_unique<InvLogLevelGenerator>(m),
                                             HnswIndex::Config(2*m, m, 200, 10, true));
     }