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[workspace] Switch conex to use hidden namespace
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178 changes: 178 additions & 0 deletions
178
tools/workspace/conex_internal/patches/eigen_namespace_pollution.patch
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,178 @@ | ||
| [conex] Fix RLDLT to live in the conex namespace | ||
|
|
||
| Projects must not define classes in another project's namespace. | ||
| When we fork code from another project, we need to switch it to | ||
| our own namespace. | ||
|
|
||
| This is a copy of https://github.com/ToyotaResearchInstitute/conex/pull/6. | ||
|
|
||
| --- conex/RLDLT.h | ||
| +++ conex/RLDLT.h | ||
| @@ -1,6 +1,6 @@ | ||
| -#include "conex/debug_macros.h" | ||
| -#include <Eigen/Dense> | ||
| -// This file is part of Eigen, a lightweight C++ template library | ||
| +#pragma once | ||
| + | ||
| +// This file was copied from Eigen, a lightweight C++ template library | ||
| // for linear algebra. | ||
| // | ||
| // Copyright (C) 2008-2011 Gael Guennebaud <[email protected]> | ||
| @@ -12,19 +12,20 @@ | ||
| // 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/. | ||
|
|
||
| -#ifndef EIGEN_RLDLT_H | ||
| -#define EIGEN_RLDLT_H | ||
| +#include <Eigen/Dense> | ||
| + | ||
| +#include "conex/debug_macros.h" | ||
| + | ||
| +namespace conex { | ||
| +namespace eigen_stuff { | ||
|
|
||
| -namespace Eigen { | ||
| +using namespace Eigen; | ||
| +namespace internal = Eigen::internal; | ||
|
|
||
| -namespace internal { | ||
| +namespace detail { | ||
| template <typename MatrixType, int UpLo> | ||
| struct RLDLT_Traits; | ||
| - | ||
| -// PositiveSemiDef means positive semi-definite and non-zero; same for | ||
| -// NegativeSemiDef | ||
| -// enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite }; | ||
| -} // namespace internal | ||
| +} // namespace detail | ||
|
|
||
| /** \ingroup Cholesky_Module | ||
| * | ||
| @@ -78,7 +79,7 @@ class RLDLT { | ||
| typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> | ||
| PermutationType; | ||
|
|
||
| - typedef internal::LDLT_Traits<MatrixType, UpLo> Traits; | ||
| + typedef detail::RLDLT_Traits<MatrixType, UpLo> Traits; | ||
|
|
||
| /** \brief Default Constructor. | ||
| * | ||
| @@ -289,7 +290,9 @@ class RLDLT { | ||
| ComputationInfo m_info; | ||
| }; | ||
|
|
||
| -namespace internal { | ||
| +namespace detail { | ||
| + | ||
| +using namespace Eigen::internal; | ||
|
|
||
| template <int UpLo> | ||
| struct rldlt_inplace; | ||
| @@ -564,7 +567,7 @@ RLDLT<MatrixType, _UpLo>& RLDLT<MatrixType, _UpLo>::compute( | ||
| m_temporary.resize(size); | ||
| m_sign = internal::ZeroSign; | ||
|
|
||
| - m_regularization_used = !internal::rldlt_inplace<UpLo>::unblocked( | ||
| + m_regularization_used = !detail::rldlt_inplace<UpLo>::unblocked( | ||
| m_matrix, m_transpositions, m_temporary, m_sign); | ||
|
|
||
| m_info = Success; | ||
| @@ -598,7 +601,7 @@ RLDLT<MatrixType, _UpLo>& RLDLT<MatrixType, _UpLo>::rankUpdate( | ||
| m_isInitialized = true; | ||
| } | ||
|
|
||
| - internal::rldlt_inplace<UpLo>::update(m_matrix, m_transpositions, m_temporary, | ||
| + detail::rldlt_inplace<UpLo>::update(m_matrix, m_transpositions, m_temporary, | ||
| w, sigma); | ||
|
|
||
| return *this; | ||
| @@ -696,6 +699,5 @@ MatrixType RLDLT<MatrixType, _UpLo>::reconstructedMatrix() const { | ||
| return res; | ||
| } | ||
|
|
||
| -} // end namespace Eigen | ||
| - | ||
| -#endif // EIGEN_RLDLT_H | ||
| +} // namespace eigen_stuff | ||
| +} // namespace conex | ||
| --- conex/block_triangular_operations.cc | ||
| +++ conex/block_triangular_operations.cc | ||
| @@ -221,7 +221,7 @@ bool T::BlockCholeskyInPlace(TriangularMatrixWorkspace* C) { | ||
| // Apply inv(M^T) = inv(L^T P) = P^T inv(L^T) | ||
| void T::ApplyBlockInverseOfMTranspose( | ||
| const TriangularMatrixWorkspace& mat, | ||
| - const std::vector<Eigen::RLDLT<Eigen::Ref<MatrixXd>>> factorization, | ||
| + const std::vector<eigen_stuff::RLDLT<Eigen::Ref<MatrixXd>>> factorization, | ||
| VectorXd* y) { | ||
| PartitionVectorIterator ypart(*y, mat.N, mat.supernode_size); | ||
| // mat.diagonal.back().triangularView<Eigen::Lower>().transpose().solveInPlace(ypart.b_i()); | ||
| @@ -264,7 +264,7 @@ void T::ApplyBlockInverseOfMTranspose( | ||
|
|
||
| void T::ApplyBlockInverseOfMD( | ||
| const TriangularMatrixWorkspace& mat, | ||
| - const std::vector<Eigen::RLDLT<Eigen::Ref<MatrixXd>>> factorization, | ||
| + const std::vector<eigen_stuff::RLDLT<Eigen::Ref<MatrixXd>>> factorization, | ||
| VectorXd* y) { | ||
| // Apply inv(M) = inv(P^T L) = inv(L) P | ||
| PartitionVectorForwardIterator ypart(*y, mat.supernode_size); | ||
| @@ -314,7 +314,7 @@ void T::ApplyBlockInverseOfMD( | ||
| // = inv(D_1) inv(L) P * off_diag | ||
| bool T::BlockLDLTInPlace( | ||
| TriangularMatrixWorkspace* C, | ||
| - std::vector<Eigen::RLDLT<Eigen::Ref<MatrixXd>>>* factorization) { | ||
| + std::vector<eigen_stuff::RLDLT<Eigen::Ref<MatrixXd>>>* factorization) { | ||
| auto& llts = *factorization; | ||
| llts.clear(); | ||
|
|
||
| --- conex/block_triangular_operations.h | ||
| +++ conex/block_triangular_operations.h | ||
| @@ -14,22 +14,22 @@ struct BlockTriangularOperations { | ||
| static bool BlockCholeskyInPlace(TriangularMatrixWorkspace* mat); | ||
| static bool BlockLDLTInPlace( | ||
| TriangularMatrixWorkspace* mat, | ||
| - std::vector<Eigen::RLDLT<Eigen::Ref<Eigen::MatrixXd>>>* factorization); | ||
| + std::vector<eigen_stuff::RLDLT<Eigen::Ref<Eigen::MatrixXd>>>* factorization); | ||
| static void ApplyBlockInverseOfMTranspose( | ||
| const TriangularMatrixWorkspace& mat, | ||
| - const std::vector<Eigen::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> | ||
| + const std::vector<eigen_stuff::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> | ||
| factorization, | ||
| Eigen::VectorXd* y); | ||
|
|
||
| static void ApplyBlockInverseOfMD( | ||
| const TriangularMatrixWorkspace& mat, | ||
| - const std::vector<Eigen::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> | ||
| + const std::vector<eigen_stuff::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> | ||
| factorization, | ||
| Eigen::VectorXd* y); | ||
|
|
||
| static void SolveInPlaceLDLT( | ||
| const TriangularMatrixWorkspace& mat, | ||
| - const std::vector<Eigen::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> | ||
| + const std::vector<eigen_stuff::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> | ||
| factorization, | ||
| Eigen::VectorXd* y) { | ||
| ApplyBlockInverseOfMD(mat, factorization, y); | ||
| --- conex/kkt_solver.h | ||
| +++ conex/kkt_solver.h | ||
| @@ -53,7 +53,7 @@ class SupernodalKKTSolver { | ||
| const std::vector<std::vector<int>> dual_variables_; | ||
| MatrixData data; | ||
| SparseTriangularMatrix mat; | ||
| - std::vector<Eigen::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> factorization; | ||
| + std::vector<eigen_stuff::RLDLT<Eigen::Ref<Eigen::MatrixXd>>> factorization; | ||
| Eigen::PermutationMatrix<-1> Pt; | ||
| mutable Eigen::VectorXd b_permuted_; | ||
| std::vector<SupernodalAssemblerBase*> assembler; | ||
| index 1277cff..1711d5b 100644 | ||
| --- conex/test/block_triangular_operations_test.cc | ||
| +++ conex/test/block_triangular_operations_test.cc | ||
| @@ -202,7 +202,7 @@ void DoLDLTTest(bool diagonal, const std::vector<Clique>& cliques) { | ||
|
|
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| Eigen::MatrixXd X = T::ToDense(mat).selfadjointView<Eigen::Lower>(); | ||
|
|
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| - std::vector<Eigen::RLDLT<Eigen::Ref<MatrixXd>>> factorization; | ||
| + std::vector<eigen_stuff::RLDLT<Eigen::Ref<MatrixXd>>> factorization; | ||
| B::BlockLDLTInPlace(&mat.workspace_, &factorization); | ||
|
|
||
| Eigen::VectorXd z = Eigen::VectorXd::Random(X.cols()); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,13 @@ | ||
| [conex] Use a custom cc_library rule for vendoring | ||
|
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| --- conex/BUILD | ||
| +++ conex/BUILD | ||
| @@ -1,3 +1,8 @@ | ||
| +load( | ||
| + "@drake//tools/workspace/conex_internal:vendor.bzl", | ||
| + cc_library = "conex_cc_library", | ||
| +) | ||
| + | ||
| cc_library( | ||
| name = "test_util", | ||
| srcs = glob(["test/test_util.cc"]), |
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