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82f0ce2726
This provide several advantages: - more flexibility in designing unit tests - unit tests can be glued to speed up compilation - unit tests are compiled with same predefined macros, which is a requirement for zapcc
63 lines
1.6 KiB
C++
63 lines
1.6 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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#include <Eigen/CXX11/Tensor>
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using Eigen::Tensor;
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static void test_simple_assign()
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{
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Tensor<int, 3> random(2,3,7);
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random.setRandom();
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TensorMap<Tensor<const int, 3> > constant(random.data(), 2, 3, 7);
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Tensor<int, 3> result(2,3,7);
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result = constant;
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for (int i = 0; i < 2; ++i) {
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for (int j = 0; j < 3; ++j) {
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for (int k = 0; k < 7; ++k) {
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VERIFY_IS_EQUAL((result(i,j,k)), random(i,j,k));
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}
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}
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}
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}
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static void test_assign_of_const_tensor()
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{
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Tensor<int, 3> random(2,3,7);
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random.setRandom();
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TensorMap<Tensor<const int, 3> > constant1(random.data(), 2, 3, 7);
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TensorMap<const Tensor<int, 3> > constant2(random.data(), 2, 3, 7);
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const TensorMap<Tensor<int, 3> > constant3(random.data(), 2, 3, 7);
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Tensor<int, 2> result1 = constant1.chip(0, 2);
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Tensor<int, 2> result2 = constant2.chip(0, 2);
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Tensor<int, 2> result3 = constant3.chip(0, 2);
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for (int i = 0; i < 2; ++i) {
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for (int j = 0; j < 3; ++j) {
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VERIFY_IS_EQUAL((result1(i,j)), random(i,j,0));
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VERIFY_IS_EQUAL((result2(i,j)), random(i,j,0));
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VERIFY_IS_EQUAL((result3(i,j)), random(i,j,0));
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}
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}
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}
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EIGEN_DECLARE_TEST(cxx11_tensor_const)
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{
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CALL_SUBTEST(test_simple_assign());
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CALL_SUBTEST(test_assign_of_const_tensor());
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}
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