diff options
author | Mehdi Goli <mehdi.goli@codeplay.com> | 2017-02-01 15:29:53 +0000 |
---|---|---|
committer | Mehdi Goli <mehdi.goli@codeplay.com> | 2017-02-01 15:29:53 +0000 |
commit | bab29936a1cf0a68ffe4ccb1fd9b4807a3ec87ae (patch) | |
tree | c750b36227a31ddb2a1e0d5fd11f0036fda775db /unsupported/test/cxx11_tensor_sycl.cpp | |
parent | 48a20b7d956433713a39e04d39cba443b7a763de (diff) |
Reducing warnings in Sycl backend.
Diffstat (limited to 'unsupported/test/cxx11_tensor_sycl.cpp')
-rw-r--r-- | unsupported/test/cxx11_tensor_sycl.cpp | 144 |
1 files changed, 72 insertions, 72 deletions
diff --git a/unsupported/test/cxx11_tensor_sycl.cpp b/unsupported/test/cxx11_tensor_sycl.cpp index 6f7e29890..5cd0f4c71 100644 --- a/unsupported/test/cxx11_tensor_sycl.cpp +++ b/unsupported/test/cxx11_tensor_sycl.cpp @@ -16,7 +16,7 @@ #define EIGEN_TEST_NO_LONGDOUBLE #define EIGEN_TEST_NO_COMPLEX #define EIGEN_TEST_FUNC cxx11_tensor_sycl -#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int +#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t #define EIGEN_USE_SYCL #include "main.h" @@ -27,24 +27,24 @@ using Eigen::SyclDevice; using Eigen::Tensor; using Eigen::TensorMap; -template <typename DataType, int DataLayout> +template <typename DataType, int DataLayout, typename IndexType> void test_sycl_mem_transfers(const Eigen::SyclDevice &sycl_device) { - int sizeDim1 = 100; - int sizeDim2 = 10; - int sizeDim3 = 20; - array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}}; - Tensor<DataType, 3, DataLayout> in1(tensorRange); - Tensor<DataType, 3, DataLayout> out1(tensorRange); - Tensor<DataType, 3, DataLayout> out2(tensorRange); - Tensor<DataType, 3, DataLayout> out3(tensorRange); + IndexType sizeDim1 = 100; + IndexType sizeDim2 = 10; + IndexType sizeDim3 = 20; + array<IndexType, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}}; + Tensor<DataType, 3, DataLayout, IndexType> in1(tensorRange); + Tensor<DataType, 3, DataLayout, IndexType> out1(tensorRange); + Tensor<DataType, 3, DataLayout, IndexType> out2(tensorRange); + Tensor<DataType, 3, DataLayout, IndexType> out3(tensorRange); in1 = in1.random(); DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(in1.size()*sizeof(DataType))); DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(out1.size()*sizeof(DataType))); - TensorMap<Tensor<DataType, 3, DataLayout>> gpu1(gpu_data1, tensorRange); - TensorMap<Tensor<DataType, 3, DataLayout>> gpu2(gpu_data2, tensorRange); + TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu1(gpu_data1, tensorRange); + TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu2(gpu_data2, tensorRange); sycl_device.memcpyHostToDevice(gpu_data1, in1.data(),(in1.size())*sizeof(DataType)); sycl_device.memcpyHostToDevice(gpu_data2, in1.data(),(in1.size())*sizeof(DataType)); @@ -55,7 +55,7 @@ void test_sycl_mem_transfers(const Eigen::SyclDevice &sycl_device) { sycl_device.memcpyDeviceToHost(out3.data(), gpu_data2,(out3.size())*sizeof(DataType)); sycl_device.synchronize(); - for (int i = 0; i < in1.size(); ++i) { + for (IndexType i = 0; i < in1.size(); ++i) { VERIFY_IS_APPROX(out1(i), in1(i) * 3.14f); VERIFY_IS_APPROX(out2(i), in1(i) * 3.14f); VERIFY_IS_APPROX(out3(i), in1(i) * 2.7f); @@ -65,20 +65,20 @@ void test_sycl_mem_transfers(const Eigen::SyclDevice &sycl_device) { sycl_device.deallocate(gpu_data2); } -template <typename DataType, int DataLayout> +template <typename DataType, int DataLayout, typename IndexType> void test_sycl_mem_sync(const Eigen::SyclDevice &sycl_device) { - int size = 20; - array<int, 1> tensorRange = {{size}}; - Tensor<DataType, 1, DataLayout> in1(tensorRange); - Tensor<DataType, 1, DataLayout> in2(tensorRange); - Tensor<DataType, 1, DataLayout> out(tensorRange); + IndexType size = 20; + array<IndexType, 1> tensorRange = {{size}}; + Tensor<DataType, 1, DataLayout, IndexType> in1(tensorRange); + Tensor<DataType, 1, DataLayout, IndexType> in2(tensorRange); + Tensor<DataType, 1, DataLayout, IndexType> out(tensorRange); in1 = in1.random(); in2 = in1; DataType* gpu_data = static_cast<DataType*>(sycl_device.allocate(in1.size()*sizeof(DataType))); - TensorMap<Tensor<DataType, 1, DataLayout>> gpu1(gpu_data, tensorRange); + TensorMap<Tensor<DataType, 1, DataLayout, IndexType>> gpu1(gpu_data, tensorRange); sycl_device.memcpyHostToDevice(gpu_data, in1.data(),(in1.size())*sizeof(DataType)); sycl_device.synchronize(); in1.setZero(); @@ -86,24 +86,24 @@ void test_sycl_mem_sync(const Eigen::SyclDevice &sycl_device) { sycl_device.memcpyDeviceToHost(out.data(), gpu_data, out.size()*sizeof(DataType)); sycl_device.synchronize(); - for (int i = 0; i < in1.size(); ++i) { + for (IndexType i = 0; i < in1.size(); ++i) { VERIFY_IS_APPROX(out(i), in2(i)); } sycl_device.deallocate(gpu_data); } -template <typename DataType, int DataLayout> +template <typename DataType, int DataLayout, typename IndexType> void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { - int sizeDim1 = 100; - int sizeDim2 = 10; - int sizeDim3 = 20; - array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}}; - Tensor<DataType, 3,DataLayout> in1(tensorRange); - Tensor<DataType, 3,DataLayout> in2(tensorRange); - Tensor<DataType, 3,DataLayout> in3(tensorRange); - Tensor<DataType, 3,DataLayout> out(tensorRange); + IndexType sizeDim1 = 100; + IndexType sizeDim2 = 10; + IndexType sizeDim3 = 20; + array<IndexType, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}}; + Tensor<DataType, 3,DataLayout, IndexType> in1(tensorRange); + Tensor<DataType, 3,DataLayout, IndexType> in2(tensorRange); + Tensor<DataType, 3,DataLayout, IndexType> in3(tensorRange); + Tensor<DataType, 3,DataLayout, IndexType> out(tensorRange); in2 = in2.random(); in3 = in3.random(); @@ -113,19 +113,19 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { DataType * gpu_in3_data = static_cast<DataType*>(sycl_device.allocate(in3.size()*sizeof(DataType))); DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.size()*sizeof(DataType))); - TensorMap<Tensor<DataType, 3, DataLayout>> gpu_in1(gpu_in1_data, tensorRange); - TensorMap<Tensor<DataType, 3, DataLayout>> gpu_in2(gpu_in2_data, tensorRange); - TensorMap<Tensor<DataType, 3, DataLayout>> gpu_in3(gpu_in3_data, tensorRange); - TensorMap<Tensor<DataType, 3, DataLayout>> gpu_out(gpu_out_data, tensorRange); + TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in1(gpu_in1_data, tensorRange); + TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in2(gpu_in2_data, tensorRange); + TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in3(gpu_in3_data, tensorRange); + TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_out(gpu_out_data, tensorRange); /// a=1.2f gpu_in1.device(sycl_device) = gpu_in1.constant(1.2f); sycl_device.memcpyDeviceToHost(in1.data(), gpu_in1_data ,(in1.size())*sizeof(DataType)); sycl_device.synchronize(); - 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(in1(i,j,k), 1.2f); } } @@ -137,9 +137,9 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data ,(out.size())*sizeof(DataType)); sycl_device.synchronize(); - 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) * 1.2f); } @@ -153,9 +153,9 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType)); sycl_device.synchronize(); - 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)); @@ -168,9 +168,9 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { gpu_out.device(sycl_device) = gpu_in1 + gpu_in2; sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType)); sycl_device.synchronize(); - 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)); @@ -183,9 +183,9 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { gpu_out.device(sycl_device) = gpu_in1 * gpu_in1; sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType)); sycl_device.synchronize(); - 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) * in1(i,j,k)); @@ -198,9 +198,9 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { gpu_out.device(sycl_device) = gpu_in1 * gpu_in1.constant(3.14f) + gpu_in2 * gpu_in2.constant(2.7f); sycl_device.memcpyDeviceToHost(out.data(),gpu_out_data,(out.size())*sizeof(DataType)); sycl_device.synchronize(); - 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) * 3.14f + in2(i,j,k) * 2.7f); @@ -214,9 +214,9 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { gpu_out.device(sycl_device) =(gpu_in1 > gpu_in1.constant(0.5f)).select(gpu_in2, gpu_in3); sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType)); sycl_device.synchronize(); - 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) > 0.5f) ? in2(i, j, k) : in3(i, j, k)); @@ -229,26 +229,26 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) { sycl_device.deallocate(gpu_in3_data); sycl_device.deallocate(gpu_out_data); } -template<typename Scalar1, typename Scalar2, int DataLayout> +template<typename Scalar1, typename Scalar2, int DataLayout, typename IndexType> static void test_sycl_cast(const Eigen::SyclDevice& sycl_device){ - int size = 20; - array<int, 1> tensorRange = {{size}}; - Tensor<Scalar1, 1, DataLayout> in(tensorRange); - Tensor<Scalar2, 1, DataLayout> out(tensorRange); - Tensor<Scalar2, 1, DataLayout> out_host(tensorRange); + IndexType size = 20; + array<IndexType, 1> tensorRange = {{size}}; + Tensor<Scalar1, 1, DataLayout, IndexType> in(tensorRange); + Tensor<Scalar2, 1, DataLayout, IndexType> out(tensorRange); + Tensor<Scalar2, 1, DataLayout, IndexType> out_host(tensorRange); in = in.random(); Scalar1* gpu_in_data = static_cast<Scalar1*>(sycl_device.allocate(in.size()*sizeof(Scalar1))); Scalar2 * gpu_out_data = static_cast<Scalar2*>(sycl_device.allocate(out.size()*sizeof(Scalar2))); - TensorMap<Tensor<Scalar1, 1, DataLayout>> gpu_in(gpu_in_data, tensorRange); - TensorMap<Tensor<Scalar2, 1, DataLayout>> gpu_out(gpu_out_data, tensorRange); + TensorMap<Tensor<Scalar1, 1, DataLayout, IndexType>> gpu_in(gpu_in_data, tensorRange); + TensorMap<Tensor<Scalar2, 1, DataLayout, IndexType>> gpu_out(gpu_out_data, tensorRange); sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.size())*sizeof(Scalar1)); gpu_out.device(sycl_device) = gpu_in. template cast<Scalar2>(); sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data, out.size()*sizeof(Scalar2)); out_host = in. template cast<Scalar2>(); - for(int i=0; i< size; i++) + for(IndexType i=0; i< size; i++) { VERIFY_IS_APPROX(out(i), out_host(i)); } @@ -259,14 +259,14 @@ static void test_sycl_cast(const Eigen::SyclDevice& sycl_device){ template<typename DataType, typename dev_Selector> void sycl_computing_test_per_device(dev_Selector s){ QueueInterface queueInterface(s); auto sycl_device = Eigen::SyclDevice(&queueInterface); - test_sycl_mem_transfers<DataType, RowMajor>(sycl_device); - test_sycl_computations<DataType, RowMajor>(sycl_device); - test_sycl_mem_sync<DataType, RowMajor>(sycl_device); - test_sycl_mem_transfers<DataType, ColMajor>(sycl_device); - test_sycl_computations<DataType, ColMajor>(sycl_device); - test_sycl_mem_sync<DataType, ColMajor>(sycl_device); - test_sycl_cast<DataType, int, RowMajor>(sycl_device); - test_sycl_cast<DataType, int, ColMajor>(sycl_device); + test_sycl_mem_transfers<DataType, RowMajor, int64_t>(sycl_device); + test_sycl_computations<DataType, RowMajor, int64_t>(sycl_device); + test_sycl_mem_sync<DataType, RowMajor, int64_t>(sycl_device); + test_sycl_mem_transfers<DataType, ColMajor, int64_t>(sycl_device); + test_sycl_computations<DataType, ColMajor, int64_t>(sycl_device); + test_sycl_mem_sync<DataType, ColMajor, int64_t>(sycl_device); + test_sycl_cast<DataType, int, RowMajor, int64_t>(sycl_device); + test_sycl_cast<DataType, int, ColMajor, int64_t>(sycl_device); } void test_cxx11_tensor_sycl() { |