Reducing warnings in Sycl backend.

1 files changed, 44 insertions, 44 deletions

diff --git a/unsupported/test/cxx11_tensor_reduction_sycl.cpp b/unsupported/test/cxx11_tensor_reduction_sycl.cpp
index 941469029..98a59a14c 100644
--- a/unsupported/test/cxx11_tensor_reduction_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_reduction_sycl.cpp
@@ -14,23 +14,23 @@
 #define EIGEN_TEST_NO_LONGDOUBLE
 #define EIGEN_TEST_NO_COMPLEX
 #define EIGEN_TEST_FUNC cxx11_tensor_reduction_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>
 
 
-template <typename DataType, int DataLayout>
+template <typename DataType, int DataLayout, typename IndexType>
 static void test_full_reductions_sycl(const Eigen::SyclDevice&  sycl_device) {
 
-  const int num_rows = 452;
-  const int num_cols = 765;
-  array<int, 2> tensorRange = {{num_rows, num_cols}};
+  const IndexType num_rows = 452;
+  const IndexType num_cols = 765;
+  array<IndexType, 2> tensorRange = {{num_rows, num_cols}};
 
-  Tensor<DataType, 2, DataLayout> in(tensorRange);
-  Tensor<DataType, 0, DataLayout> full_redux;
-  Tensor<DataType, 0, DataLayout> full_redux_gpu;
+  Tensor<DataType, 2, DataLayout, IndexType> in(tensorRange);
+  Tensor<DataType, 0, DataLayout, IndexType> full_redux;
+  Tensor<DataType, 0, DataLayout, IndexType> full_redux_gpu;
 
   in.setRandom();
 
@@ -39,8 +39,8 @@ static void test_full_reductions_sycl(const Eigen::SyclDevice&  sycl_device) {
   DataType* gpu_in_data = static_cast<DataType*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(DataType)));
   DataType* gpu_out_data =(DataType*)sycl_device.allocate(sizeof(DataType));
 
-  TensorMap<Tensor<DataType, 2, DataLayout> >  in_gpu(gpu_in_data, tensorRange);
-  TensorMap<Tensor<DataType, 0, DataLayout> >  out_gpu(gpu_out_data);
+  TensorMap<Tensor<DataType, 2, DataLayout, IndexType> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<DataType, 0, DataLayout, IndexType> >  out_gpu(gpu_out_data);
 
   sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(DataType));
   out_gpu.device(sycl_device) = in_gpu.sum();
@@ -51,21 +51,21 @@ static void test_full_reductions_sycl(const Eigen::SyclDevice&  sycl_device) {
   sycl_device.deallocate(gpu_in_data);
   sycl_device.deallocate(gpu_out_data);
 }
-template <typename DataType, int DataLayout>
+template <typename DataType, int DataLayout, typename IndexType>
 static void test_first_dim_reductions_sycl(const Eigen::SyclDevice& sycl_device) {
 
-  int dim_x = 145;
-  int dim_y = 1;
-  int dim_z = 67;
+  IndexType dim_x = 145;
+  IndexType dim_y = 1;
+  IndexType dim_z = 67;
 
-  array<int, 3> tensorRange = {{dim_x, dim_y, dim_z}};
-  Eigen::array<int, 1> red_axis;
+  array<IndexType, 3> tensorRange = {{dim_x, dim_y, dim_z}};
+  Eigen::array<IndexType, 1> red_axis;
   red_axis[0] = 0;
-  array<int, 2> reduced_tensorRange = {{dim_y, dim_z}};
+  array<IndexType, 2> reduced_tensorRange = {{dim_y, dim_z}};
 
-  Tensor<DataType, 3, DataLayout> in(tensorRange);
-  Tensor<DataType, 2, DataLayout> redux(reduced_tensorRange);
-  Tensor<DataType, 2, DataLayout> redux_gpu(reduced_tensorRange);
+  Tensor<DataType, 3, DataLayout, IndexType> in(tensorRange);
+  Tensor<DataType, 2, DataLayout, IndexType> redux(reduced_tensorRange);
+  Tensor<DataType, 2, DataLayout, IndexType> redux_gpu(reduced_tensorRange);
 
   in.setRandom();
 
@@ -74,37 +74,37 @@ static void test_first_dim_reductions_sycl(const Eigen::SyclDevice& sycl_device)
   DataType* gpu_in_data = static_cast<DataType*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(DataType)));
   DataType* gpu_out_data = static_cast<DataType*>(sycl_device.allocate(redux_gpu.dimensions().TotalSize()*sizeof(DataType)));
 
-  TensorMap<Tensor<DataType, 3, DataLayout> >  in_gpu(gpu_in_data, tensorRange);
-  TensorMap<Tensor<DataType, 2, DataLayout> >  out_gpu(gpu_out_data, reduced_tensorRange);
+  TensorMap<Tensor<DataType, 3, DataLayout, IndexType> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<DataType, 2, DataLayout, IndexType> >  out_gpu(gpu_out_data, reduced_tensorRange);
 
   sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(DataType));
   out_gpu.device(sycl_device) = in_gpu.sum(red_axis);
   sycl_device.memcpyDeviceToHost(redux_gpu.data(), gpu_out_data, redux_gpu.dimensions().TotalSize()*sizeof(DataType));
 
   // Check that the CPU and GPU reductions return the same result.
-  for(int j=0; j<reduced_tensorRange[0]; j++ )
-    for(int k=0; k<reduced_tensorRange[1]; k++ )
+  for(IndexType j=0; j<reduced_tensorRange[0]; j++ )
+    for(IndexType k=0; k<reduced_tensorRange[1]; k++ )
       VERIFY_IS_APPROX(redux_gpu(j,k), redux(j,k));
 
   sycl_device.deallocate(gpu_in_data);
   sycl_device.deallocate(gpu_out_data);
 }
 
-template <typename DataType, int DataLayout>
+template <typename DataType, int DataLayout, typename IndexType>
 static void test_last_dim_reductions_sycl(const Eigen::SyclDevice &sycl_device) {
 
-  int dim_x = 567;
-  int dim_y = 1;
-  int dim_z = 47;
+  IndexType dim_x = 567;
+  IndexType dim_y = 1;
+  IndexType dim_z = 47;
 
-  array<int, 3> tensorRange = {{dim_x, dim_y, dim_z}};
-  Eigen::array<int, 1> red_axis;
+  array<IndexType, 3> tensorRange = {{dim_x, dim_y, dim_z}};
+  Eigen::array<IndexType, 1> red_axis;
   red_axis[0] = 2;
-  array<int, 2> reduced_tensorRange = {{dim_x, dim_y}};
+  array<IndexType, 2> reduced_tensorRange = {{dim_x, dim_y}};
 
-  Tensor<DataType, 3, DataLayout> in(tensorRange);
-  Tensor<DataType, 2, DataLayout> redux(reduced_tensorRange);
-  Tensor<DataType, 2, DataLayout> redux_gpu(reduced_tensorRange);
+  Tensor<DataType, 3, DataLayout, IndexType> in(tensorRange);
+  Tensor<DataType, 2, DataLayout, IndexType> redux(reduced_tensorRange);
+  Tensor<DataType, 2, DataLayout, IndexType> redux_gpu(reduced_tensorRange);
 
   in.setRandom();
 
@@ -113,15 +113,15 @@ static void test_last_dim_reductions_sycl(const Eigen::SyclDevice &sycl_device)
   DataType* gpu_in_data = static_cast<DataType*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(DataType)));
   DataType* gpu_out_data = static_cast<DataType*>(sycl_device.allocate(redux_gpu.dimensions().TotalSize()*sizeof(DataType)));
 
-  TensorMap<Tensor<DataType, 3, DataLayout> >  in_gpu(gpu_in_data, tensorRange);
-  TensorMap<Tensor<DataType, 2, DataLayout> >  out_gpu(gpu_out_data, reduced_tensorRange);
+  TensorMap<Tensor<DataType, 3, DataLayout, IndexType> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<DataType, 2, DataLayout, IndexType> >  out_gpu(gpu_out_data, reduced_tensorRange);
 
   sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(DataType));
   out_gpu.device(sycl_device) = in_gpu.sum(red_axis);
   sycl_device.memcpyDeviceToHost(redux_gpu.data(), gpu_out_data, redux_gpu.dimensions().TotalSize()*sizeof(DataType));
   // Check that the CPU and GPU reductions return the same result.
-  for(int j=0; j<reduced_tensorRange[0]; j++ )
-    for(int k=0; k<reduced_tensorRange[1]; k++ )
+  for(IndexType j=0; j<reduced_tensorRange[0]; j++ )
+    for(IndexType k=0; k<reduced_tensorRange[1]; k++ )
       VERIFY_IS_APPROX(redux_gpu(j,k), redux(j,k));
 
   sycl_device.deallocate(gpu_in_data);
@@ -133,12 +133,12 @@ template<typename DataType> void sycl_reduction_test_per_device(const cl::sycl::
   QueueInterface queueInterface(d);
   auto sycl_device = Eigen::SyclDevice(&queueInterface);
 
-  test_full_reductions_sycl<DataType, RowMajor>(sycl_device);
-  test_first_dim_reductions_sycl<DataType, RowMajor>(sycl_device);
-  test_last_dim_reductions_sycl<DataType, RowMajor>(sycl_device);
-  test_full_reductions_sycl<DataType, ColMajor>(sycl_device);
-  test_first_dim_reductions_sycl<DataType, ColMajor>(sycl_device);
-  test_last_dim_reductions_sycl<DataType, ColMajor>(sycl_device);
+  test_full_reductions_sycl<DataType, RowMajor, int64_t>(sycl_device);
+  test_first_dim_reductions_sycl<DataType, RowMajor, int64_t>(sycl_device);
+  test_last_dim_reductions_sycl<DataType, RowMajor, int64_t>(sycl_device);
+  test_full_reductions_sycl<DataType, ColMajor, int64_t>(sycl_device);
+  test_first_dim_reductions_sycl<DataType, ColMajor, int64_t>(sycl_device);
+  test_last_dim_reductions_sycl<DataType, ColMajor, int64_t>(sycl_device);
 }
 void test_cxx11_tensor_reduction_sycl() {
   for (const auto& device :Eigen::get_sycl_supported_devices()) {