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https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Added support for static list of indices
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@@ -102,6 +102,7 @@ if(EIGEN_TEST_CXX11)
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ei_add_test(cxx11_tensor_symmetry "-std=c++0x")
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ei_add_test(cxx11_tensor_assign "-std=c++0x")
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ei_add_test(cxx11_tensor_dimension "-std=c++0x")
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ei_add_test(cxx11_tensor_index_list "-std=c++0x")
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ei_add_test(cxx11_tensor_comparisons "-std=c++0x")
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ei_add_test(cxx11_tensor_contraction "-std=c++0x")
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ei_add_test(cxx11_tensor_convolution "-std=c++0x")
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133
unsupported/test/cxx11_tensor_index_list.cpp
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133
unsupported/test/cxx11_tensor_index_list.cpp
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@@ -0,0 +1,133 @@
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// 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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static void test_static_index_list()
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{
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Tensor<float, 4> tensor(2,3,5,7);
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tensor.setRandom();
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constexpr auto reduction_axis = make_index_list(0, 1, 2);
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VERIFY_IS_EQUAL(internal::array_get<0>(reduction_axis), 0);
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VERIFY_IS_EQUAL(internal::array_get<1>(reduction_axis), 1);
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VERIFY_IS_EQUAL(internal::array_get<2>(reduction_axis), 2);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[0]), 0);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[1]), 1);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[2]), 2);
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EIGEN_STATIC_ASSERT((internal::array_get<0>(reduction_axis) == 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
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EIGEN_STATIC_ASSERT((internal::array_get<1>(reduction_axis) == 1), YOU_MADE_A_PROGRAMMING_MISTAKE);
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EIGEN_STATIC_ASSERT((internal::array_get<2>(reduction_axis) == 2), YOU_MADE_A_PROGRAMMING_MISTAKE);
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Tensor<float, 1> result = tensor.sum(reduction_axis);
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for (int i = 0; i < result.size(); ++i) {
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float expected = 0.0f;
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for (int j = 0; j < 2; ++j) {
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for (int k = 0; k < 3; ++k) {
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for (int l = 0; l < 5; ++l) {
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expected += tensor(j,k,l,i);
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}
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}
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}
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VERIFY_IS_APPROX(result(i), expected);
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}
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}
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static void test_dynamic_index_list()
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{
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Tensor<float, 4> tensor(2,3,5,7);
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tensor.setRandom();
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int dim1 = 2;
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int dim2 = 1;
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int dim3 = 0;
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auto reduction_axis = make_index_list(dim1, dim2, dim3);
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VERIFY_IS_EQUAL(internal::array_get<0>(reduction_axis), 2);
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VERIFY_IS_EQUAL(internal::array_get<1>(reduction_axis), 1);
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VERIFY_IS_EQUAL(internal::array_get<2>(reduction_axis), 0);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[0]), 2);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[1]), 1);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[2]), 0);
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Tensor<float, 1> result = tensor.sum(reduction_axis);
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for (int i = 0; i < result.size(); ++i) {
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float expected = 0.0f;
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for (int j = 0; j < 2; ++j) {
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for (int k = 0; k < 3; ++k) {
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for (int l = 0; l < 5; ++l) {
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expected += tensor(j,k,l,i);
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}
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}
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}
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VERIFY_IS_APPROX(result(i), expected);
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}
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}
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static void test_mixed_index_list()
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{
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Tensor<float, 4> tensor(2,3,5,7);
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tensor.setRandom();
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int dim2 = 1;
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int dim4 = 3;
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auto reduction_axis = make_index_list(0, dim2, 2, dim4);
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VERIFY_IS_EQUAL(internal::array_get<0>(reduction_axis), 0);
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VERIFY_IS_EQUAL(internal::array_get<1>(reduction_axis), 1);
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VERIFY_IS_EQUAL(internal::array_get<2>(reduction_axis), 2);
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VERIFY_IS_EQUAL(internal::array_get<3>(reduction_axis), 3);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[0]), 0);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[1]), 1);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[2]), 2);
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VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[3]), 3);
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typedef IndexList<type2index<0>, int, type2index<2>, int> ReductionIndices;
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ReductionIndices reduction_indices;
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reduction_indices.set(1, 1);
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reduction_indices.set(3, 3);
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EIGEN_STATIC_ASSERT((internal::array_get<0>(reduction_indices) == 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
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EIGEN_STATIC_ASSERT((internal::array_get<2>(reduction_indices) == 2), YOU_MADE_A_PROGRAMMING_MISTAKE);
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EIGEN_STATIC_ASSERT((internal::index_known_statically<ReductionIndices>()(0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
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EIGEN_STATIC_ASSERT((internal::index_known_statically<ReductionIndices>()(2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
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EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionIndices>()(0, 0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
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EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionIndices>()(2, 2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
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Tensor<float, 1> result1 = tensor.sum(reduction_axis);
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Tensor<float, 1> result2 = tensor.sum(reduction_indices);
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float expected = 0.0f;
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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 < 5; ++k) {
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for (int l = 0; l < 7; ++l) {
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expected += tensor(i,j,k,l);
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}
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}
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}
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}
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VERIFY_IS_APPROX(result1(0), expected);
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VERIFY_IS_APPROX(result2(0), expected);
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}
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void test_cxx11_tensor_index_list()
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{
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CALL_SUBTEST(test_static_index_list());
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CALL_SUBTEST(test_dynamic_index_list());
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CALL_SUBTEST(test_mixed_index_list());
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}
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