| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2016 | |
| // Mehdi Goli Codeplay Software Ltd. | |
| // Ralph Potter Codeplay Software Ltd. | |
| // Luke Iwanski Codeplay Software Ltd. | |
| // Contact: <eigen@codeplay.com> | |
| // Benoit Steiner <benoit.steiner.goog@gmail.com> | |
| // | |
| // This Source Code Form is subject to the terms of the Mozilla | |
| // Public License v. 2.0. If a copy of the MPL was not distributed | |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
| #define EIGEN_TEST_NO_LONGDOUBLE | |
| #define EIGEN_TEST_NO_COMPLEX | |
| #define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t | |
| #define EIGEN_USE_SYCL | |
| #include "main.h" | |
| #include <unsupported/Eigen/CXX11/Tensor> | |
| using Eigen::array; | |
| using Eigen::SyclDevice; | |
| using Eigen::Tensor; | |
| using Eigen::TensorMap; | |
| template <typename DataType, int DataLayout, typename IndexType> | |
| static void test_simple_shuffling_sycl(const Eigen::SyclDevice& sycl_device) | |
| { | |
| IndexType sizeDim1 = 2; | |
| IndexType sizeDim2 = 3; | |
| IndexType sizeDim3 = 5; | |
| IndexType sizeDim4 = 7; | |
| array<IndexType, 4> tensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4}}; | |
| Tensor<DataType, 4, DataLayout,IndexType> tensor(tensorRange); | |
| Tensor<DataType, 4, DataLayout,IndexType> no_shuffle(tensorRange); | |
| tensor.setRandom(); | |
| const size_t buffSize =tensor.size()*sizeof(DataType); | |
| array<IndexType, 4> shuffles; | |
| shuffles[0] = 0; | |
| shuffles[1] = 1; | |
| shuffles[2] = 2; | |
| shuffles[3] = 3; | |
| DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(buffSize)); | |
| DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(buffSize)); | |
| TensorMap<Tensor<DataType, 4, DataLayout,IndexType>> gpu1(gpu_data1, tensorRange); | |
| TensorMap<Tensor<DataType, 4, DataLayout,IndexType>> gpu2(gpu_data2, tensorRange); | |
| sycl_device.memcpyHostToDevice(gpu_data1, tensor.data(), buffSize); | |
| gpu2.device(sycl_device)=gpu1.shuffle(shuffles); | |
| sycl_device.memcpyDeviceToHost(no_shuffle.data(), gpu_data2, buffSize); | |
| sycl_device.synchronize(); | |
| VERIFY_IS_EQUAL(no_shuffle.dimension(0), sizeDim1); | |
| VERIFY_IS_EQUAL(no_shuffle.dimension(1), sizeDim2); | |
| VERIFY_IS_EQUAL(no_shuffle.dimension(2), sizeDim3); | |
| VERIFY_IS_EQUAL(no_shuffle.dimension(3), sizeDim4); | |
| for (IndexType i = 0; i < sizeDim1; ++i) { | |
| for (IndexType j = 0; j < sizeDim2; ++j) { | |
| for (IndexType k = 0; k < sizeDim3; ++k) { | |
| for (IndexType l = 0; l < sizeDim4; ++l) { | |
| VERIFY_IS_EQUAL(tensor(i,j,k,l), no_shuffle(i,j,k,l)); | |
| } | |
| } | |
| } | |
| } | |
| shuffles[0] = 2; | |
| shuffles[1] = 3; | |
| shuffles[2] = 1; | |
| shuffles[3] = 0; | |
| array<IndexType, 4> tensorrangeShuffle = {{sizeDim3, sizeDim4, sizeDim2, sizeDim1}}; | |
| Tensor<DataType, 4, DataLayout,IndexType> shuffle(tensorrangeShuffle); | |
| DataType* gpu_data3 = static_cast<DataType*>(sycl_device.allocate(buffSize)); | |
| TensorMap<Tensor<DataType, 4,DataLayout,IndexType>> gpu3(gpu_data3, tensorrangeShuffle); | |
| gpu3.device(sycl_device)=gpu1.shuffle(shuffles); | |
| sycl_device.memcpyDeviceToHost(shuffle.data(), gpu_data3, buffSize); | |
| sycl_device.synchronize(); | |
| VERIFY_IS_EQUAL(shuffle.dimension(0), sizeDim3); | |
| VERIFY_IS_EQUAL(shuffle.dimension(1), sizeDim4); | |
| VERIFY_IS_EQUAL(shuffle.dimension(2), sizeDim2); | |
| VERIFY_IS_EQUAL(shuffle.dimension(3), sizeDim1); | |
| for (IndexType i = 0; i < sizeDim1; ++i) { | |
| for (IndexType j = 0; j < sizeDim2; ++j) { | |
| for (IndexType k = 0; k < sizeDim3; ++k) { | |
| for (IndexType l = 0; l < sizeDim4; ++l) { | |
| VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(k,l,j,i)); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| template<typename DataType, typename dev_Selector> void sycl_shuffling_test_per_device(dev_Selector s){ | |
| QueueInterface queueInterface(s); | |
| auto sycl_device = Eigen::SyclDevice(&queueInterface); | |
| test_simple_shuffling_sycl<DataType, RowMajor, int64_t>(sycl_device); | |
| test_simple_shuffling_sycl<DataType, ColMajor, int64_t>(sycl_device); | |
| } | |
| EIGEN_DECLARE_TEST(cxx11_tensor_shuffling_sycl) | |
| { | |
| for (const auto& device :Eigen::get_sycl_supported_devices()) { | |
| CALL_SUBTEST(sycl_shuffling_test_per_device<float>(device)); | |
| } | |
| } |