Reducing warnings in Sycl backend.

1 files changed, 17 insertions, 17 deletions

diff --git a/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp b/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
index 4d19a3b2a..aca036cde 100644
--- a/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
@@ -14,23 +14,23 @@
 #define EIGEN_TEST_NO_LONGDOUBLE
 #define EIGEN_TEST_NO_COMPLEX
 #define EIGEN_TEST_FUNC cxx11_tensor_forced_eval_sycl
-#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t
 #define EIGEN_USE_SYCL
 
 #include "main.h"
 #include <unsupported/Eigen/CXX11/Tensor>
 
 using Eigen::Tensor;
-template <typename DataType, int DataLayout>
+template <typename DataType, int DataLayout, typename IndexType>
 void test_forced_eval_sycl(const Eigen::SyclDevice &sycl_device) {
 
-  int sizeDim1 = 100;
-  int sizeDim2 = 20;
-  int sizeDim3 = 20;
-  Eigen::array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
-  Eigen::Tensor<DataType, 3, DataLayout> in1(tensorRange);
-  Eigen::Tensor<DataType, 3, DataLayout> in2(tensorRange);
-  Eigen::Tensor<DataType, 3, DataLayout> out(tensorRange);
+  IndexType sizeDim1 = 100;
+  IndexType sizeDim2 = 20;
+  IndexType sizeDim3 = 20;
+  Eigen::array<IndexType, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
+  Eigen::Tensor<DataType, 3, DataLayout, IndexType> in1(tensorRange);
+  Eigen::Tensor<DataType, 3, DataLayout, IndexType> in2(tensorRange);
+  Eigen::Tensor<DataType, 3, DataLayout, IndexType> out(tensorRange);
 
   DataType * gpu_in1_data  = static_cast<DataType*>(sycl_device.allocate(in1.dimensions().TotalSize()*sizeof(DataType)));
   DataType * gpu_in2_data  = static_cast<DataType*>(sycl_device.allocate(in2.dimensions().TotalSize()*sizeof(DataType)));
@@ -40,17 +40,17 @@ void test_forced_eval_sycl(const Eigen::SyclDevice &sycl_device) {
   in2 = in2.random() + in2.constant(10.0f);
 
   // creating TensorMap from tensor
-  Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout>> gpu_in1(gpu_in1_data, tensorRange);
-  Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout>> gpu_in2(gpu_in2_data, tensorRange);
-  Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout>> gpu_out(gpu_out_data, tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_in1(gpu_in1_data, tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_in2(gpu_in2_data, tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_out(gpu_out_data, tensorRange);
   sycl_device.memcpyHostToDevice(gpu_in1_data, in1.data(),(in1.dimensions().TotalSize())*sizeof(DataType));
   sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in1.dimensions().TotalSize())*sizeof(DataType));
   /// c=(a+b)*b
   gpu_out.device(sycl_device) =(gpu_in1 + gpu_in2).eval() * gpu_in2;
   sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType));
-  for (int i = 0; i < sizeDim1; ++i) {
-    for (int j = 0; j < sizeDim2; ++j) {
-      for (int k = 0; k < sizeDim3; ++k) {
+  for (IndexType i = 0; i < sizeDim1; ++i) {
+    for (IndexType j = 0; j < sizeDim2; ++j) {
+      for (IndexType k = 0; k < sizeDim3; ++k) {
         VERIFY_IS_APPROX(out(i, j, k),
                          (in1(i, j, k) + in2(i, j, k)) * in2(i, j, k));
       }
@@ -66,8 +66,8 @@ void test_forced_eval_sycl(const Eigen::SyclDevice &sycl_device) {
 template <typename DataType, typename Dev_selector> void tensorForced_evalperDevice(Dev_selector s){
   QueueInterface queueInterface(s);
   auto sycl_device = Eigen::SyclDevice(&queueInterface);
-  test_forced_eval_sycl<DataType, RowMajor>(sycl_device);
-  test_forced_eval_sycl<DataType, ColMajor>(sycl_device);
+  test_forced_eval_sycl<DataType, RowMajor, int64_t>(sycl_device);
+  test_forced_eval_sycl<DataType, ColMajor, int64_t>(sycl_device);
 }
 void test_cxx11_tensor_forced_eval_sycl() {
   for (const auto& device :Eigen::get_sycl_supported_devices()) {