test knn labels

dpbench/benchmarks/default/knn/knn_initialize.py

@@ -24,7 +24,7 @@ def _gen_data_x(ip_size, data_dim, seed, dtype):
 
     def _gen_data_y(ip_size, classes_num, seed):
         default_rng.seed(seed)
-        data = default_rng.randint(classes_num, size=ip_size)
+        data = default_rng.randint(classes_num, size=ip_size, dtype=np.int64)
         return data
 
     def _gen_train_data(train_size, data_dim, classes_num, seed_train, dtype):

dpbench/benchmarks/default/knn/knn_sycl_native_ext/knn_sycl/_knn_kernel.hpp

@@ -105,7 +105,7 @@ sycl::event knn_impl(sycl::queue q,
 
 		  size_t ith_idx = i * classes_num;
 		  size_t jth = queue_neighbors[j].label;
-		  out << ith_idx << " " << jth << sycl::endl;
+		  //out << ith_idx << " " << jth << sycl::endl;
 		  //d_votes_to_classes[ith_idx + jth] = jth;
 		  //d_votes_to_classes[(i*classes_num) + (queue_neighbors[j].label)] += 1;
                 }

dpbench/benchmarks/default/knn/knn_sycl_native_ext/knn_sycl/_knn_sycl.cpp

@@ -39,6 +39,19 @@ void knn_sync(dpctl::tensor::usm_ndarray x_train,
                               votes_to_classes))
         throw std::runtime_error("Input arrays are not acceptable.");
 
+    size_t* train_labels = y_train.get_data<size_t>();
+    std::cout << "Labels size = " << y_train.get_size() << std::endl;
+    sycl::queue q = x_train.get_queue();
+
+    size_t h_labels[1024];
+
+    q.memcpy(h_labels,train_labels,sizeof(size_t)*1024);
+    q.wait();
+
+    for (int idx = 0; idx<1024;idx++) {
+      std::cout << "Train labels: "<< h_labels[idx] << std::endl;
+    }
+
     auto typenum = x_train.get_typenum();
     if (typenum == UAR_FLOAT) {
         sycl::event res_ev = knn_impl<float, unsigned int>(