1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
|
// 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));
}
}
|
