devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

Adding TensorShuffling backend for sycl; adding TensorReshaping backend for sycl; cleaning up the sycl backend.

Browse Source
This commit is contained in:
Mehdi Goli
2016-11-29 15:30:42 +00:00
parent 02080e2b67
commit 577ce78085
15 changed files with 626 additions and 301 deletions
Download Patch File Download Diff File Expand all files Collapse all files

120
unsupported/test/cxx11_tensor_shuffling_sycl.cpp Normal file
View File

@@ -0,0 +1,120 @@
// 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_shuffling_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;
template <typename DataType, int DataLayout, typename IndexTypes>
static void test_simple_shuffling_sycl(const Eigen::SyclDevice& sycl_device)
{
IndexTypes sizeDim1 = 2;
IndexTypes sizeDim2 = 3;
IndexTypes sizeDim3 = 5;
IndexTypes sizeDim4 = 7;
array<IndexTypes, 4> tensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4}};
Tensor<DataType, 4, DataLayout,IndexTypes> tensor(tensorRange);
Tensor<DataType, 4, DataLayout,IndexTypes> no_shuffle(tensorRange);
tensor.setRandom();
const size_t buffSize =tensor.size()*sizeof(DataType);
array<IndexTypes, 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,IndexTypes>> gpu1(gpu_data1, tensorRange);
TensorMap<Tensor<DataType, 4, DataLayout,IndexTypes>> 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);
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 (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
for (int 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<IndexTypes, 4> tensorrangeShuffle = {{sizeDim3, sizeDim4, sizeDim2, sizeDim1}};
Tensor<DataType, 4, DataLayout,IndexTypes> shuffle(tensorrangeShuffle);
DataType* gpu_data3 = static_cast<DataType*>(sycl_device.allocate(buffSize));
TensorMap<Tensor<DataType, 4,DataLayout,IndexTypes>> gpu3(gpu_data3, tensorrangeShuffle);
gpu3.device(sycl_device)=gpu1.shuffle(shuffles);
sycl_device.memcpyDeviceToHost(shuffle.data(), gpu_data3, buffSize);
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 (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
for (int 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, int>(sycl_device);
test_simple_shuffling_sycl<DataType, ColMajor, int>(sycl_device);
test_simple_shuffling_sycl<DataType, RowMajor, int64_t>(sycl_device);
test_simple_shuffling_sycl<DataType, ColMajor, int64_t>(sycl_device);
}
void test_cxx11_tensor_shuffling_sycl()
{
for (const auto& device :Eigen::get_sycl_supported_devices()) {
CALL_SUBTEST(sycl_shuffling_test_per_device<float>(device));
}
}