mirror of
https://gitlab.com/libeigen/eigen.git
synced 2025-05-22 12:37:35 +08:00
85 lines
3.0 KiB
C++
85 lines
3.0 KiB
C++
// 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_TEST_FUNC cxx11_tensor_morphing_sycl
|
|
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
|
|
#define EIGEN_USE_SYCL
|
|
|
|
|
|
#include "main.h"
|
|
#include <unsupported/Eigen/CXX11/Tensor>
|
|
|
|
using Eigen::array;
|
|
using Eigen::SyclDevice;
|
|
using Eigen::Tensor;
|
|
using Eigen::TensorMap;
|
|
|
|
|
|
static void test_simple_slice(const Eigen::SyclDevice &sycl_device)
|
|
{
|
|
int sizeDim1 = 2;
|
|
int sizeDim2 = 3;
|
|
int sizeDim3 = 5;
|
|
int sizeDim4 = 7;
|
|
int sizeDim5 = 11;
|
|
array<int, 5> tensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4, sizeDim5}};
|
|
Tensor<float, 5> tensor(tensorRange);
|
|
tensor.setRandom();
|
|
array<int, 5> slice1_range ={{1, 1, 1, 1, 1}};
|
|
Tensor<float, 5> slice1(slice1_range);
|
|
|
|
float* gpu_data1 = static_cast<float*>(sycl_device.allocate(tensor.size()*sizeof(float)));
|
|
float* gpu_data2 = static_cast<float*>(sycl_device.allocate(slice1.size()*sizeof(float)));
|
|
TensorMap<Tensor<float, 5>> gpu1(gpu_data1, tensorRange);
|
|
TensorMap<Tensor<float, 5>> gpu2(gpu_data2, slice1_range);
|
|
Eigen::DSizes<ptrdiff_t, 5> indices(1,2,3,4,5);
|
|
Eigen::DSizes<ptrdiff_t, 5> sizes(1,1,1,1,1);
|
|
sycl_device.memcpyHostToDevice(gpu_data1, tensor.data(),(tensor.size())*sizeof(float));
|
|
gpu2.device(sycl_device)=gpu1.slice(indices, sizes);
|
|
sycl_device.memcpyDeviceToHost(slice1.data(), gpu_data2,(slice1.size())*sizeof(float));
|
|
VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5));
|
|
|
|
|
|
array<int, 5> slice2_range ={{1,1,2,2,3}};
|
|
Tensor<float, 5> slice2(slice2_range);
|
|
float* gpu_data3 = static_cast<float*>(sycl_device.allocate(slice2.size()*sizeof(float)));
|
|
TensorMap<Tensor<float, 5>> gpu3(gpu_data3, slice2_range);
|
|
Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5);
|
|
Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3);
|
|
gpu3.device(sycl_device)=gpu1.slice(indices2, sizes2);
|
|
sycl_device.memcpyDeviceToHost(slice2.data(), gpu_data3,(slice2.size())*sizeof(float));
|
|
for (int i = 0; i < 2; ++i) {
|
|
for (int j = 0; j < 2; ++j) {
|
|
for (int k = 0; k < 3; ++k) {
|
|
VERIFY_IS_EQUAL(slice2(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k));
|
|
}
|
|
}
|
|
}
|
|
sycl_device.deallocate(gpu_data1);
|
|
sycl_device.deallocate(gpu_data2);
|
|
sycl_device.deallocate(gpu_data3);
|
|
}
|
|
|
|
void test_cxx11_tensor_morphing_sycl()
|
|
{
|
|
/// Currentlly it only works on cpu. Adding GPU cause LLVM ERROR in cunstructing OpenCL Kernel at runtime.
|
|
cl::sycl::cpu_selector s;
|
|
Eigen::SyclDevice sycl_device(s);
|
|
CALL_SUBTEST(test_simple_slice(sycl_device));
|
|
|
|
}
|