| // 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; |
| |
| using Eigen::Tensor; |
| using Eigen::RowMajor; |
| template <typename DataType, int DataLayout, typename IndexType> |
| static void test_image_op_sycl(const Eigen::SyclDevice &sycl_device) |
| { |
| IndexType sizeDim1 = 245; |
| IndexType sizeDim2 = 343; |
| IndexType sizeDim3 = 577; |
| |
| array<IndexType, 3> input_range ={{sizeDim1, sizeDim2, sizeDim3}}; |
| array<IndexType, 3> slice_range ={{sizeDim1-1, sizeDim2, sizeDim3}}; |
| |
| Tensor<DataType, 3,DataLayout, IndexType> tensor1(input_range); |
| Tensor<DataType, 3,DataLayout, IndexType> tensor2(input_range); |
| Tensor<DataType, 3, DataLayout, IndexType> tensor3(slice_range); |
| Tensor<DataType, 3, DataLayout, IndexType> tensor3_cpu(slice_range); |
| |
| |
| |
| typedef Eigen::DSizes<IndexType, 3> Index3; |
| Index3 strides1(1L,1L, 1L); |
| Index3 indicesStart1(1L, 0L, 0L); |
| Index3 indicesStop1(sizeDim1, sizeDim2, sizeDim3); |
| |
| Index3 strides2(1L,1L, 1L); |
| Index3 indicesStart2(0L, 0L, 0L); |
| Index3 indicesStop2(sizeDim1-1, sizeDim2, sizeDim3); |
| Eigen::DSizes<IndexType, 3> sizes(sizeDim1-1,sizeDim2,sizeDim3); |
| |
| tensor1.setRandom(); |
| tensor2.setRandom(); |
| |
| |
| DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(tensor1.size()*sizeof(DataType))); |
| DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(tensor2.size()*sizeof(DataType))); |
| DataType* gpu_data3 = static_cast<DataType*>(sycl_device.allocate(tensor3.size()*sizeof(DataType))); |
| |
| TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu1(gpu_data1, input_range); |
| TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu2(gpu_data2, input_range); |
| TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu3(gpu_data3, slice_range); |
| |
| sycl_device.memcpyHostToDevice(gpu_data1, tensor1.data(),(tensor1.size())*sizeof(DataType)); |
| sycl_device.memcpyHostToDevice(gpu_data2, tensor2.data(),(tensor2.size())*sizeof(DataType)); |
| gpu3.device(sycl_device)= gpu1.slice(indicesStart1, sizes) - gpu2.slice(indicesStart2, sizes); |
| sycl_device.memcpyDeviceToHost(tensor3.data(), gpu_data3,(tensor3.size())*sizeof(DataType)); |
| |
| tensor3_cpu = tensor1.stridedSlice(indicesStart1,indicesStop1,strides1) - tensor2.stridedSlice(indicesStart2,indicesStop2,strides2); |
| |
| |
| for (IndexType i = 0; i <slice_range[0] ; ++i) { |
| for (IndexType j = 0; j < slice_range[1]; ++j) { |
| for (IndexType k = 0; k < slice_range[2]; ++k) { |
| VERIFY_IS_EQUAL(tensor3_cpu(i,j,k), tensor3(i,j,k)); |
| } |
| } |
| } |
| sycl_device.deallocate(gpu_data1); |
| sycl_device.deallocate(gpu_data2); |
| sycl_device.deallocate(gpu_data3); |
| } |
| |
| |
| 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_image_op_sycl<DataType, RowMajor, int64_t>(sycl_device); |
| } |
| |
| EIGEN_DECLARE_TEST(cxx11_tensor_image_op_sycl) { |
| for (const auto& device :Eigen::get_sycl_supported_devices()) { |
| CALL_SUBTEST(sycl_computing_test_per_device<half>(device)); |
| CALL_SUBTEST(sycl_computing_test_per_device<float>(device)); |
| #ifdef EIGEN_SYCL_DOUBLE_SUPPORT |
| CALL_SUBTEST(sycl_computing_test_per_device<double>(device)); |
| #endif |
| } |
| } |