eigen/unsupported/test/cxx11_tensor_shuffling.cpp
2018-09-11 13:32:32 -07:00

229 lines
6.1 KiB
C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 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/.
#include "main.h"
#include <Eigen/CXX11/Tensor>
using Eigen::Tensor;
using Eigen::array;
template <int DataLayout>
static void test_simple_shuffling()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
array<ptrdiff_t, 4> shuffles;
shuffles[0] = 0;
shuffles[1] = 1;
shuffles[2] = 2;
shuffles[3] = 3;
Tensor<float, 4, DataLayout> no_shuffle;
no_shuffle = tensor.shuffle(shuffles);
VERIFY_IS_EQUAL(no_shuffle.dimension(0), 2);
VERIFY_IS_EQUAL(no_shuffle.dimension(1), 3);
VERIFY_IS_EQUAL(no_shuffle.dimension(2), 5);
VERIFY_IS_EQUAL(no_shuffle.dimension(3), 7);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 7; ++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;
Tensor<float, 4, DataLayout> shuffle;
shuffle = tensor.shuffle(shuffles);
VERIFY_IS_EQUAL(shuffle.dimension(0), 5);
VERIFY_IS_EQUAL(shuffle.dimension(1), 7);
VERIFY_IS_EQUAL(shuffle.dimension(2), 3);
VERIFY_IS_EQUAL(shuffle.dimension(3), 2);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 7; ++l) {
VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(k,l,j,i));
}
}
}
}
}
template <int DataLayout>
static void test_expr_shuffling()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
array<ptrdiff_t, 4> shuffles;
shuffles[0] = 2;
shuffles[1] = 3;
shuffles[2] = 1;
shuffles[3] = 0;
Tensor<float, 4, DataLayout> expected;
expected = tensor.shuffle(shuffles);
Tensor<float, 4, DataLayout> result(5, 7, 3, 2);
array<ptrdiff_t, 4> src_slice_dim({2, 3, 1, 7});
array<ptrdiff_t, 4> src_slice_start({0, 0, 0, 0});
array<ptrdiff_t, 4> dst_slice_dim({1, 7, 3, 2});
array<ptrdiff_t, 4> dst_slice_start({0, 0, 0, 0});
for (int i = 0; i < 5; ++i) {
result.slice(dst_slice_start, dst_slice_dim) =
tensor.slice(src_slice_start, src_slice_dim).shuffle(shuffles);
src_slice_start[2] += 1;
dst_slice_start[0] += 1;
}
VERIFY_IS_EQUAL(result.dimension(0), 5);
VERIFY_IS_EQUAL(result.dimension(1), 7);
VERIFY_IS_EQUAL(result.dimension(2), 3);
VERIFY_IS_EQUAL(result.dimension(3), 2);
for (int i = 0; i < expected.dimension(0); ++i) {
for (int j = 0; j < expected.dimension(1); ++j) {
for (int k = 0; k < expected.dimension(2); ++k) {
for (int l = 0; l < expected.dimension(3); ++l) {
VERIFY_IS_EQUAL(result(i,j,k,l), expected(i,j,k,l));
}
}
}
}
dst_slice_start[0] = 0;
result.setRandom();
for (int i = 0; i < 5; ++i) {
result.slice(dst_slice_start, dst_slice_dim) =
tensor.shuffle(shuffles).slice(dst_slice_start, dst_slice_dim);
dst_slice_start[0] += 1;
}
for (int i = 0; i < expected.dimension(0); ++i) {
for (int j = 0; j < expected.dimension(1); ++j) {
for (int k = 0; k < expected.dimension(2); ++k) {
for (int l = 0; l < expected.dimension(3); ++l) {
VERIFY_IS_EQUAL(result(i,j,k,l), expected(i,j,k,l));
}
}
}
}
}
template <int DataLayout>
static void test_shuffling_as_value()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
array<ptrdiff_t, 4> shuffles;
shuffles[2] = 0;
shuffles[3] = 1;
shuffles[1] = 2;
shuffles[0] = 3;
Tensor<float, 4, DataLayout> shuffle(5,7,3,2);
shuffle.shuffle(shuffles) = tensor;
VERIFY_IS_EQUAL(shuffle.dimension(0), 5);
VERIFY_IS_EQUAL(shuffle.dimension(1), 7);
VERIFY_IS_EQUAL(shuffle.dimension(2), 3);
VERIFY_IS_EQUAL(shuffle.dimension(3), 2);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 7; ++l) {
VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(k,l,j,i));
}
}
}
}
array<ptrdiff_t, 4> no_shuffle;
no_shuffle[0] = 0;
no_shuffle[1] = 1;
no_shuffle[2] = 2;
no_shuffle[3] = 3;
Tensor<float, 4, DataLayout> shuffle2(5,7,3,2);
shuffle2.shuffle(shuffles) = tensor.shuffle(no_shuffle);
for (int i = 0; i < 5; ++i) {
for (int j = 0; j < 7; ++j) {
for (int k = 0; k < 3; ++k) {
for (int l = 0; l < 2; ++l) {
VERIFY_IS_EQUAL(shuffle2(i,j,k,l), shuffle(i,j,k,l));
}
}
}
}
}
template <int DataLayout>
static void test_shuffle_unshuffle()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
// Choose a random permutation.
array<ptrdiff_t, 4> shuffles;
for (int i = 0; i < 4; ++i) {
shuffles[i] = i;
}
array<ptrdiff_t, 4> shuffles_inverse;
for (int i = 0; i < 4; ++i) {
const ptrdiff_t index = internal::random<ptrdiff_t>(i, 3);
shuffles_inverse[shuffles[index]] = i;
std::swap(shuffles[i], shuffles[index]);
}
Tensor<float, 4, DataLayout> shuffle;
shuffle = tensor.shuffle(shuffles).shuffle(shuffles_inverse);
VERIFY_IS_EQUAL(shuffle.dimension(0), 2);
VERIFY_IS_EQUAL(shuffle.dimension(1), 3);
VERIFY_IS_EQUAL(shuffle.dimension(2), 5);
VERIFY_IS_EQUAL(shuffle.dimension(3), 7);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 7; ++l) {
VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(i,j,k,l));
}
}
}
}
}
EIGEN_DECLARE_TEST(cxx11_tensor_shuffling)
{
CALL_SUBTEST(test_simple_shuffling<ColMajor>());
CALL_SUBTEST(test_simple_shuffling<RowMajor>());
CALL_SUBTEST(test_expr_shuffling<ColMajor>());
CALL_SUBTEST(test_expr_shuffling<RowMajor>());
CALL_SUBTEST(test_shuffling_as_value<ColMajor>());
CALL_SUBTEST(test_shuffling_as_value<RowMajor>());
CALL_SUBTEST(test_shuffle_unshuffle<ColMajor>());
CALL_SUBTEST(test_shuffle_unshuffle<RowMajor>());
}