Format distances_dnnl.h

guangzegu · Oct 22, 2024 · f556407 · f556407
1 parent 9e34323
commit f556407
Showing 1 changed file with 16 additions and 17 deletions.
diff --git a/faiss/cppcontrib/amx/distances_dnnl.h b/faiss/cppcontrib/amx/distances_dnnl.h
@@ -24,7 +24,7 @@ namespace faiss {
 // block sizes for oneDNN/AMX distance computations
 FAISS_API int distance_compute_dnnl_query_bs = 10240;
 FAISS_API int distance_compute_dnnl_database_bs = 10240;
-   
+
 /* Find the nearest neighbors for nx queries in a set of ny vectors using oneDNN/AMX */
 template <class BlockResultHandler>
 void exhaustive_inner_product_seq_dnnl(
@@ -33,11 +33,11 @@ void exhaustive_inner_product_seq_dnnl(
         size_t d,
         size_t nx,
         size_t ny,
-        BlockResultHandler& res) {           
+        BlockResultHandler& res) {
     using SingleResultHandler =
             typename BlockResultHandler::SingleResultHandler;
     [[maybe_unused]] int nt = std::min(int(nx), omp_get_max_threads());
-    
+
     std::unique_ptr<float[]> res_arr(new float[nx * ny]);
 
     comput_f32bf16f32_inner_product(
@@ -50,30 +50,30 @@ void exhaustive_inner_product_seq_dnnl(
             res_arr.get());
 
 #pragma omp parallel num_threads(nt)
-        {
-            SingleResultHandler resi(res);
+    {
+        SingleResultHandler resi(res);
 #pragma omp for
-            for (size_t i = 0; i < nx; i++) {
-                resi.begin(i);
-                for (size_t j = 0; j < ny; j++) {
-                    float ip = res_arr[i * ny + j];
-                    resi.add_result(ip, j);
-                }
-                resi.end();
+        for (size_t i = 0; i < nx; i++) {
+            resi.begin(i);
+            for (size_t j = 0; j < ny; j++) {
+                float ip = res_arr[i * ny + j];
+                resi.add_result(ip, j);
             }
+            resi.end();
         }
+    }
 }
 
-/** Find the nearest neighbors for nx queries in a set of ny vectors using oneDNN/AMX */
+/* Find the nearest neighbors for nx queries in a set of ny vectors using oneDNN/AMX */
 template <class BlockResultHandler>
 void exhaustive_inner_product_blas_dnnl(
         const float* x,
         const float* y,
         size_t d,
         size_t nx,
         size_t ny,
-        BlockResultHandler& res) {     
-    /* block sizes */    
+        BlockResultHandler& res) {
+    /* block sizes */
     const size_t bs_x = distance_compute_dnnl_query_bs;
     const size_t bs_y = distance_compute_dnnl_database_bs;
     std::unique_ptr<float[]> ip_block(new float[bs_x * bs_y]);
@@ -100,12 +100,11 @@ void exhaustive_inner_product_blas_dnnl(
                     const_cast<float*>(y + j0 * d),
                     ip_block.get());
 
-
             res.add_results(j0, j1, ip_block.get());
         }
         res.end_multiple();
         InterruptCallback::check();
     }
 }
 
-}// namespace faiss
+} // namespace faiss