1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2016 5 // Mehdi Goli Codeplay Software Ltd. 6 // Ralph Potter Codeplay Software Ltd. 7 // Luke Iwanski Codeplay Software Ltd. 8 // Contact: <eigen (at) codeplay.com> 9 // 10 // This Source Code Form is subject to the terms of the Mozilla 11 // Public License v. 2.0. If a copy of the MPL was not distributed 12 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 13 14 #define EIGEN_TEST_NO_LONGDOUBLE 15 #define EIGEN_TEST_NO_COMPLEX 16 #define EIGEN_TEST_FUNC cxx11_tensor_broadcast_sycl 17 #define EIGEN_DEFAULT_DENSE_INDEX_TYPE int 18 #define EIGEN_USE_SYCL 19 20 #include "main.h" 21 #include <unsupported/Eigen/CXX11/Tensor> 22 23 using Eigen::array; 24 using Eigen::SyclDevice; 25 using Eigen::Tensor; 26 using Eigen::TensorMap; 27 28 static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){ 29 30 // BROADCAST test: 31 array<int, 4> in_range = {{2, 3, 5, 7}}; 32 array<int, 4> broadcasts = {{2, 3, 1, 4}}; 33 array<int, 4> out_range; // = in_range * broadcasts 34 for (size_t i = 0; i < out_range.size(); ++i) 35 out_range[i] = in_range[i] * broadcasts[i]; 36 37 Tensor<float, 4> input(in_range); 38 Tensor<float, 4> out(out_range); 39 40 for (size_t i = 0; i < in_range.size(); ++i) 41 VERIFY_IS_EQUAL(out.dimension(i), out_range[i]); 42 43 44 for (int i = 0; i < input.size(); ++i) 45 input(i) = static_cast<float>(i); 46 47 float * gpu_in_data = static_cast<float*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(float))); 48 float * gpu_out_data = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float))); 49 50 TensorMap<Tensor<float, 4>> gpu_in(gpu_in_data, in_range); 51 TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range); 52 sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float)); 53 gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts); 54 sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float)); 55 56 for (int i = 0; i < 4; ++i) { 57 for (int j = 0; j < 9; ++j) { 58 for (int k = 0; k < 5; ++k) { 59 for (int l = 0; l < 28; ++l) { 60 VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l)); 61 } 62 } 63 } 64 } 65 printf("Broadcast Test Passed\n"); 66 sycl_device.deallocate(gpu_in_data); 67 sycl_device.deallocate(gpu_out_data); 68 } 69 70 void test_cxx11_tensor_broadcast_sycl() { 71 cl::sycl::gpu_selector s; 72 Eigen::SyclDevice sycl_device(s); 73 CALL_SUBTEST(test_broadcast_sycl(sycl_device)); 74 } 75
