Overview
Request 863726 accepted
I have no clue why build fail for others, why cc1plus was killed.
- Update to version 2.0.0.
* C++ threading based multi-threading support.
* Problem::AddResidualBlock(), SizedFunction, AutoDiffCostFunction,
NumericDiffCostFunction support an arbitrary number of parameter
blocks using variadic templates
* Significantly faster AutoDiff
* Mixed precision solves when using SPARSE_NORMAL_CHOLESKY.
* LocalParameterization objects can have a zero sized tangent
size, which effectively makes the parameter block constant.
In particular, this allows for a SubsetParameterization that
holds all the coordinates of a parameter block constant.
* Visibility based preconditioning now works with Eigen and CXSparse.
* Added Problem::EvaluateResidualBlock() and
Problem::EvaluateResidualBlockAssumingParametersUnchanged().
* GradientChecker now uses RIDDERS method for more accurate
numerical derivatives.
* Covariance computation uses a faster SVD algorithm
* A new local parameterization for lines
* A new (SUBSET) preconditioner for problems with general sparsity.
* Faster Schur elimination using faster custom BLAS routines for
small matrices.
* Automatic differentiation for FirstOrderFunction in the form of
AutoDiffFirstOrderFunction.
* TinySolverAutoDiffFunction now supports dynamic number of
residuals just like AutoDiffCostFunction.
* Backward Incompatible API Changes
* EvaluationCallback has been moved from Solver::Options to
Problem::Options for a more correct API.
* Removed Android.mk based build.
* Solver::Options::num_linear_solver_threads is no more.
* Several other moinor fixes and changes
- Created by andythe_great
- In state accepted
Request History
andythe_great created request
I have no clue why build fail for others, why cc1plus was killed.
- Update to version 2.0.0.
* C++ threading based multi-threading support.
* Problem::AddResidualBlock(), SizedFunction, AutoDiffCostFunction,
NumericDiffCostFunction support an arbitrary number of parameter
blocks using variadic templates
* Significantly faster AutoDiff
* Mixed precision solves when using SPARSE_NORMAL_CHOLESKY.
* LocalParameterization objects can have a zero sized tangent
size, which effectively makes the parameter block constant.
In particular, this allows for a SubsetParameterization that
holds all the coordinates of a parameter block constant.
* Visibility based preconditioning now works with Eigen and CXSparse.
* Added Problem::EvaluateResidualBlock() and
Problem::EvaluateResidualBlockAssumingParametersUnchanged().
* GradientChecker now uses RIDDERS method for more accurate
numerical derivatives.
* Covariance computation uses a faster SVD algorithm
* A new local parameterization for lines
* A new (SUBSET) preconditioner for problems with general sparsity.
* Faster Schur elimination using faster custom BLAS routines for
small matrices.
* Automatic differentiation for FirstOrderFunction in the form of
AutoDiffFirstOrderFunction.
* TinySolverAutoDiffFunction now supports dynamic number of
residuals just like AutoDiffCostFunction.
* Backward Incompatible API Changes
* EvaluationCallback has been moved from Solver::Options to
Problem::Options for a more correct API.
* Removed Android.mk based build.
* Solver::Options::num_linear_solver_threads is no more.
* Several other moinor fixes and changes
dstoecker accepted request
@Dmitry_R, @Mailaender, @StefanBruens, @TheBlackCat, @adrianSuSE, @anag, @badshah400, @cjunghans, @dstoecker, @eeich, @kwk, @mslacken, @openfoam, @psmt: review reminder