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// 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;
template<int DataLayout>
static void test_dimension_failures()
{
Tensor<int, 3, DataLayout> left(2, 3, 1);
Tensor<int, 3, DataLayout> right(3, 3, 1);
left.setRandom();
right.setRandom();
// Okay; other dimensions are equal.
Tensor<int, 3, DataLayout> concatenation = left.concatenate(right, 0);
// Dimension mismatches.
VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, 1));
VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, 2));
// Axis > NumDims or < 0.
VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, 3));
VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, -1));
}
template<int DataLayout>
static void test_static_dimension_failure()
{
Tensor<int, 2, DataLayout> left(2, 3);
Tensor<int, 3, DataLayout> right(2, 3, 1);
#ifdef CXX11_TENSOR_CONCATENATION_STATIC_DIMENSION_FAILURE
// Technically compatible, but we static assert that the inputs have same
// NumDims.
Tensor<int, 3, DataLayout> concatenation = left.concatenate(right, 0);
#endif
// This can be worked around in this case.
Tensor<int, 3, DataLayout> concatenation = left
.reshape(Tensor<int, 3>::Dimensions(2, 3, 1))
.concatenate(right, 0);
Tensor<int, 2, DataLayout> alternative = left
.concatenate(right.reshape(Tensor<int, 2>::Dimensions{{{2, 3}}}), 0);
}
template<int DataLayout>
static void test_simple_concatenation()
{
Tensor<int, 3, DataLayout> left(2, 3, 1);
Tensor<int, 3, DataLayout> right(2, 3, 1);
left.setRandom();
right.setRandom();
Tensor<int, 3, DataLayout> concatenation = left.concatenate(right, 0);
VERIFY_IS_EQUAL(concatenation.dimension(0), 4);
VERIFY_IS_EQUAL(concatenation.dimension(1), 3);
VERIFY_IS_EQUAL(concatenation.dimension(2), 1);
for (int j = 0; j < 3; ++j) {
for (int i = 0; i < 2; ++i) {
VERIFY_IS_EQUAL(concatenation(i, j, 0), left(i, j, 0));
}
for (int i = 2; i < 4; ++i) {
VERIFY_IS_EQUAL(concatenation(i, j, 0), right(i - 2, j, 0));
}
}
concatenation = left.concatenate(right, 1);
VERIFY_IS_EQUAL(concatenation.dimension(0), 2);
VERIFY_IS_EQUAL(concatenation.dimension(1), 6);
VERIFY_IS_EQUAL(concatenation.dimension(2), 1);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(concatenation(i, j, 0), left(i, j, 0));
}
for (int j = 3; j < 6; ++j) {
VERIFY_IS_EQUAL(concatenation(i, j, 0), right(i, j - 3, 0));
}
}
concatenation = left.concatenate(right, 2);
VERIFY_IS_EQUAL(concatenation.dimension(0), 2);
VERIFY_IS_EQUAL(concatenation.dimension(1), 3);
VERIFY_IS_EQUAL(concatenation.dimension(2), 2);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(concatenation(i, j, 0), left(i, j, 0));
VERIFY_IS_EQUAL(concatenation(i, j, 1), right(i, j, 0));
}
}
}
// TODO(phli): Add test once we have a real vectorized implementation.
// static void test_vectorized_concatenation() {}
static void test_concatenation_as_lvalue()
{
Tensor<int, 2> t1(2, 3);
Tensor<int, 2> t2(2, 3);
t1.setRandom();
t2.setRandom();
Tensor<int, 2> result(4, 3);
result.setRandom();
t1.concatenate(t2, 0) = result;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(t1(i, j), result(i, j));
VERIFY_IS_EQUAL(t2(i, j), result(i+2, j));
}
}
}
void test_cxx11_tensor_concatenation()
{
CALL_SUBTEST(test_dimension_failures<ColMajor>());
CALL_SUBTEST(test_dimension_failures<RowMajor>());
CALL_SUBTEST(test_static_dimension_failure<ColMajor>());
CALL_SUBTEST(test_static_dimension_failure<RowMajor>());
CALL_SUBTEST(test_simple_concatenation<ColMajor>());
CALL_SUBTEST(test_simple_concatenation<RowMajor>());
// CALL_SUBTEST(test_vectorized_concatenation());
CALL_SUBTEST(test_concatenation_as_lvalue());
}
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