| /external/ceres-solver/internal/ceres/ |
| coordinate_descent_minimizer.cc | 181 Solve(&inner_program,
202 // Solve the optimization problem for one parameter block.
203 void CoordinateDescentMinimizer::Solve(Program* program,
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| unsymmetric_linear_solver_test.cc | 91 solver->Solve(transformed_A.get(),
101 solver->Solve(transformed_A.get(),
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| conjugate_gradients_solver.cc | 66 LinearSolver::Summary ConjugateGradientsSolver::Solve(
197 // solve the Newton step. This particular convergence test comes
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| sparse_normal_cholesky_solver.cc | 143 EventLogger event_logger("SparseNormalCholeskySolver::Eigen::Solve");
150 // Compute the normal equations. J'J delta = J'f and solve them
207 simplicial_ldlt_->solve(b);
211 "Eigen failure. Unable to do triangular solve.";
215 event_logger.AddEvent("Solve");
240 EventLogger event_logger("SparseNormalCholeskySolver::CXSparse::Solve");
247 // Compute the normal equations. J'J delta = J'f and solve them
298 event_logger.AddEvent("Solve");
321 EventLogger event_logger("SparseNormalCholeskySolver::SuiteSparse::Solve");
363 cholmod_dense* solution = ss_.Solve(factor_, rhs, &summary.message)
[all...] |
| suitesparse.cc | 312 cholmod_dense* SuiteSparse::Solve(cholmod_factor* L,
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| trust_region_minimizer_test.cc | 391 Solve(options, &problem, &summary);
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| dogleg_strategy.cc | 116 // regularize the Gauss-Newton solve and that defines the
377 // For any given y, we can solve (2) for x as
448 return -B_i.partialPivLu().solve(subspace_g_);
457 // This function attempts to solve the boundary-constrained subspace problem
530 // If the solve fails, the multiplier to the diagonal is increased
536 // multiplier starts out from the last successful solve.
544 // that we need to solve the normal equations more or less
561 // As in the LevenbergMarquardtStrategy, solve Jy = r instead
565 linear_solver_summary = linear_solver_->Solve(jacobian,
626 // to doing a pure Gauss-Newton solve
[all...] |
| schur_complement_solver.cc | 65 EventLogger event_logger("SchurComplementSolver::Solve");
114 // Solve the system Sx = r, assuming that the matrix S is stored in a
148 VectorRef(solution, num_rows) = llt.solve(ConstVectorRef(rhs(), num_rows));
268 // Solve the system Sx = r, assuming that the matrix S is stored in a
356 cholmod_dense* cholmod_solution = ss_.Solve(factor_,
363 "SuiteSparse failure. Unable to perform triangular solve.";
375 // Solve the system Sx = r, assuming that the matrix S is stored in a
431 // Solve the system Sx = r, assuming that the matrix S is stored in a
506 simplicial_ldlt_->solve(ConstVectorRef(rhs(), num_rows));
507 event_logger.AddEvent("Solve");
[all...] |
| system_test.cc | 152 Solve(options,
169 // SPARSE_NORMAL_CHOLESKY as the golden solve. We compare
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| visibility_based_preconditioner.cc | 469 CHECK_NOTNULL(ss->Solve(factor_, tmp_rhs_, &status));
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| solver_impl.cc | 184 void SolverImpl::Solve(const Solver::Options& options,
423 "LinearSolver::Solve",
[all...] |
| /external/ceres-solver/examples/ |
| denoising.cc | 157 ceres::Solve(options, problem, &summary);
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| simple_bundle_adjuster.cc | 215 ceres::Solve(options, &problem, &summary);
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| more_garbow_hillstrom.cc | 290 Solve(options, &problem, &summary);
321 Solve(options, &problem, &summary);
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| bundle_adjuster.cc | 101 "accuracy of each linear solve of the truncated newton step. "
102 "Changing this parameter can affect solve performance.");
106 DEFINE_double(max_solver_time, 1e32, "Maximum solve time in seconds.");
325 Solve(options, &problem, &summary);
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| libmv_homography.cc | 53 // perspectively projected into two images. The first step is to solve a
237 // Solve Lx=B
238 const Vec h = L.fullPivLu().solve(b);
352 // Configure the solve.
362 // Run the solve.
364 ceres::Solve(solver_options, &problem, &summary);
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| ellipse_approximation.cc | 365 ceres::Solve(options, problem, &summary);
440 // First, solve `X` and `t` jointly with dynamic_sparsity = true.
445 // Second, solve with dynamic_sparsity = false.
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| libmv_bundle_adjuster.cc | 766 // Solve!
768 ceres::Solve(options, &problem, &summary);
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| nist.cc | 420 // construct the problem from scratch for each case and solve it.
436 Solve(options, &problem, &summary);
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| /external/llvm/lib/Analysis/ |
| SparsePropagation.cpp | 293 void SparseSolver::Solve(Function &F) {
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| /external/llvm/lib/Transforms/Scalar/ |
| SCCP.cpp | 255 /// Solve - Solve for constants and executable blocks.
257 void Solve();
261 /// However, this is not a safe assumption. After we solve dataflow, this
[all...] |
| LoopStrengthReduce.cpp | 85 /// conceivably solve, so it should not affect generated code, but catches the
[all...] |
| /cts/suite/cts/deviceTests/browserbench/assets/octane/ |
| box2d.js | [all...] |
