You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
143 lines
4.5 KiB
143 lines
4.5 KiB
// 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 the mozilla.org home page |
|
|
|
#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 |
|
// Clang compiler break with {{{}}} with an ambiguous error on copy constructor |
|
// the variadic DSize constructor added for #ifndef EIGEN_EMULATE_CXX11_META_H. |
|
// Solution: |
|
// either the code should change to |
|
// Tensor<int, 2>::Dimensions{{2, 3}} |
|
// or Tensor<int, 2>::Dimensions{Tensor<int, 2>::Dimensions{{2, 3}}} |
|
.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)); |
|
} |
|
} |
|
} |
|
|
|
|
|
EIGEN_DECLARE_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()); |
|
|
|
}
|
|
|