Use double data type when normalizing vector.

2 files changed, 5 insertions, 4 deletions

diff --git a/ann_benchmark/src/tests/ann_benchmark/test_angular.py b/ann_benchmark/src/tests/ann_benchmark/test_angular.py
index 6fe15bf3c58..15e718906d6 100644
--- a/ann_benchmark/src/tests/ann_benchmark/test_angular.py
+++ b/ann_benchmark/src/tests/ann_benchmark/test_angular.py
@@ -21,7 +21,7 @@ class Fixture:
         top = self.find(10, [1, 1])
         assert [top[0][0], top[1][0]] == [0, 1]
         # Allow some rounding errors
-        epsilon = 5e-8
+        epsilon = 6e-8
         assert abs((1 - top[0][1]) - math.sqrt(0.5)) < epsilon
         assert abs((1 - top[1][1]) - 1) < epsilon
         top2 = self.find(10, [0, 2])
diff --git a/ann_benchmark/src/vespa/ann_benchmark/vespa_ann_benchmark.cpp b/ann_benchmark/src/vespa/ann_benchmark/vespa_ann_benchmark.cpp
index f9a4d5b43cc..fe7fd9d25fb 100644
--- a/ann_benchmark/src/vespa/ann_benchmark/vespa_ann_benchmark.cpp
+++ b/ann_benchmark/src/vespa/ann_benchmark/vespa_ann_benchmark.cpp
@@ -132,11 +132,12 @@ HnswIndex::get_typed_cells(const std::vector<float>& value, std::vector<float>&
     if (!_normalize_vectors) {
         return {&value[0], CellType::FLOAT, value.size()};
     }
-    float sum_of_squared = 0.0f;
+    double sum_of_squared = 0.0;
     for (auto elem : value) {
-        sum_of_squared += elem * elem;
+        double delem = elem;
+        sum_of_squared += delem * delem;
     }
-    float factor = 1.0f / (sqrtf(sum_of_squared) + 1e-40f);
+    double factor = 1.0 / (sqrt(sum_of_squared) + 1e-40);
     normalized_value.reserve(value.size());
     normalized_value.clear();
     for (auto elem : value) {