diff options
Diffstat (limited to 'extern/ceres/internal/ceres/accelerate_sparse.cc')
| -rw-r--r-- | extern/ceres/internal/ceres/accelerate_sparse.cc | 87 |
1 files changed, 43 insertions, 44 deletions
diff --git a/extern/ceres/internal/ceres/accelerate_sparse.cc b/extern/ceres/internal/ceres/accelerate_sparse.cc index eb04e7113d7..d2b642bf5dc 100644 --- a/extern/ceres/internal/ceres/accelerate_sparse.cc +++ b/extern/ceres/internal/ceres/accelerate_sparse.cc @@ -33,18 +33,19 @@ #ifndef CERES_NO_ACCELERATE_SPARSE -#include "ceres/accelerate_sparse.h" - #include <algorithm> #include <string> #include <vector> +#include "ceres/accelerate_sparse.h" #include "ceres/compressed_col_sparse_matrix_utils.h" #include "ceres/compressed_row_sparse_matrix.h" #include "ceres/triplet_sparse_matrix.h" #include "glog/logging.h" -#define CASESTR(x) case x: return #x +#define CASESTR(x) \ + case x: \ + return #x namespace ceres { namespace internal { @@ -68,7 +69,7 @@ const char* SparseStatusToString(SparseStatus_t status) { // aligned to kAccelerateRequiredAlignment and returns a pointer to the // aligned start. void* ResizeForAccelerateAlignment(const size_t required_size, - std::vector<uint8_t> *workspace) { + std::vector<uint8_t>* workspace) { // As per the Accelerate documentation, all workspace memory passed to the // sparse solver functions must be 16-byte aligned. constexpr int kAccelerateRequiredAlignment = 16; @@ -80,29 +81,28 @@ void* ResizeForAccelerateAlignment(const size_t required_size, size_t size_from_aligned_start = workspace->size(); void* aligned_solve_workspace_start = reinterpret_cast<void*>(workspace->data()); - aligned_solve_workspace_start = - std::align(kAccelerateRequiredAlignment, - required_size, - aligned_solve_workspace_start, - size_from_aligned_start); + aligned_solve_workspace_start = std::align(kAccelerateRequiredAlignment, + required_size, + aligned_solve_workspace_start, + size_from_aligned_start); CHECK(aligned_solve_workspace_start != nullptr) << "required_size: " << required_size << ", workspace size: " << workspace->size(); return aligned_solve_workspace_start; } -template<typename Scalar> +template <typename Scalar> void AccelerateSparse<Scalar>::Solve(NumericFactorization* numeric_factor, DenseVector* rhs_and_solution) { // From SparseSolve() documentation in Solve.h - const int required_size = - numeric_factor->solveWorkspaceRequiredStatic + - numeric_factor->solveWorkspaceRequiredPerRHS; - SparseSolve(*numeric_factor, *rhs_and_solution, + const int required_size = numeric_factor->solveWorkspaceRequiredStatic + + numeric_factor->solveWorkspaceRequiredPerRHS; + SparseSolve(*numeric_factor, + *rhs_and_solution, ResizeForAccelerateAlignment(required_size, &solve_workspace_)); } -template<typename Scalar> +template <typename Scalar> typename AccelerateSparse<Scalar>::ASSparseMatrix AccelerateSparse<Scalar>::CreateSparseMatrixTransposeView( CompressedRowSparseMatrix* A) { @@ -112,7 +112,7 @@ AccelerateSparse<Scalar>::CreateSparseMatrixTransposeView( // // Accelerate's columnStarts is a long*, not an int*. These types might be // different (e.g. ARM on iOS) so always make a copy. - column_starts_.resize(A->num_rows() +1); // +1 for final column length. + column_starts_.resize(A->num_rows() + 1); // +1 for final column length. std::copy_n(A->rows(), column_starts_.size(), &column_starts_[0]); ASSparseMatrix At; @@ -136,29 +136,31 @@ AccelerateSparse<Scalar>::CreateSparseMatrixTransposeView( return At; } -template<typename Scalar> +template <typename Scalar> typename AccelerateSparse<Scalar>::SymbolicFactorization AccelerateSparse<Scalar>::AnalyzeCholesky(ASSparseMatrix* A) { return SparseFactor(SparseFactorizationCholesky, A->structure); } -template<typename Scalar> +template <typename Scalar> typename AccelerateSparse<Scalar>::NumericFactorization AccelerateSparse<Scalar>::Cholesky(ASSparseMatrix* A, SymbolicFactorization* symbolic_factor) { return SparseFactor(*symbolic_factor, *A); } -template<typename Scalar> +template <typename Scalar> void AccelerateSparse<Scalar>::Cholesky(ASSparseMatrix* A, NumericFactorization* numeric_factor) { // From SparseRefactor() documentation in Solve.h - const int required_size = std::is_same<Scalar, double>::value - ? numeric_factor->symbolicFactorization.workspaceSize_Double - : numeric_factor->symbolicFactorization.workspaceSize_Float; - return SparseRefactor(*A, numeric_factor, - ResizeForAccelerateAlignment(required_size, - &factorization_workspace_)); + const int required_size = + std::is_same<Scalar, double>::value + ? numeric_factor->symbolicFactorization.workspaceSize_Double + : numeric_factor->symbolicFactorization.workspaceSize_Float; + return SparseRefactor( + *A, + numeric_factor, + ResizeForAccelerateAlignment(required_size, &factorization_workspace_)); } // Instantiate only for the specific template types required/supported s/t the @@ -166,34 +168,33 @@ void AccelerateSparse<Scalar>::Cholesky(ASSparseMatrix* A, template class AccelerateSparse<double>; template class AccelerateSparse<float>; -template<typename Scalar> -std::unique_ptr<SparseCholesky> -AppleAccelerateCholesky<Scalar>::Create(OrderingType ordering_type) { +template <typename Scalar> +std::unique_ptr<SparseCholesky> AppleAccelerateCholesky<Scalar>::Create( + OrderingType ordering_type) { return std::unique_ptr<SparseCholesky>( new AppleAccelerateCholesky<Scalar>(ordering_type)); } -template<typename Scalar> +template <typename Scalar> AppleAccelerateCholesky<Scalar>::AppleAccelerateCholesky( const OrderingType ordering_type) : ordering_type_(ordering_type) {} -template<typename Scalar> +template <typename Scalar> AppleAccelerateCholesky<Scalar>::~AppleAccelerateCholesky() { FreeSymbolicFactorization(); FreeNumericFactorization(); } -template<typename Scalar> +template <typename Scalar> CompressedRowSparseMatrix::StorageType AppleAccelerateCholesky<Scalar>::StorageType() const { return CompressedRowSparseMatrix::LOWER_TRIANGULAR; } -template<typename Scalar> -LinearSolverTerminationType -AppleAccelerateCholesky<Scalar>::Factorize(CompressedRowSparseMatrix* lhs, - std::string* message) { +template <typename Scalar> +LinearSolverTerminationType AppleAccelerateCholesky<Scalar>::Factorize( + CompressedRowSparseMatrix* lhs, std::string* message) { CHECK_EQ(lhs->storage_type(), StorageType()); if (lhs == NULL) { *message = "Failure: Input lhs is NULL."; @@ -234,11 +235,9 @@ AppleAccelerateCholesky<Scalar>::Factorize(CompressedRowSparseMatrix* lhs, return LINEAR_SOLVER_SUCCESS; } -template<typename Scalar> -LinearSolverTerminationType -AppleAccelerateCholesky<Scalar>::Solve(const double* rhs, - double* solution, - std::string* message) { +template <typename Scalar> +LinearSolverTerminationType AppleAccelerateCholesky<Scalar>::Solve( + const double* rhs, double* solution, std::string* message) { CHECK_EQ(numeric_factor_->status, SparseStatusOK) << "Solve called without a call to Factorize first (" << SparseStatusToString(numeric_factor_->status) << ")."; @@ -262,7 +261,7 @@ AppleAccelerateCholesky<Scalar>::Solve(const double* rhs, return LINEAR_SOLVER_SUCCESS; } -template<typename Scalar> +template <typename Scalar> void AppleAccelerateCholesky<Scalar>::FreeSymbolicFactorization() { if (symbolic_factor_) { SparseCleanup(*symbolic_factor_); @@ -270,7 +269,7 @@ void AppleAccelerateCholesky<Scalar>::FreeSymbolicFactorization() { } } -template<typename Scalar> +template <typename Scalar> void AppleAccelerateCholesky<Scalar>::FreeNumericFactorization() { if (numeric_factor_) { SparseCleanup(*numeric_factor_); @@ -283,7 +282,7 @@ void AppleAccelerateCholesky<Scalar>::FreeNumericFactorization() { template class AppleAccelerateCholesky<double>; template class AppleAccelerateCholesky<float>; -} -} +} // namespace internal +} // namespace ceres #endif // CERES_NO_ACCELERATE_SPARSE |