This was an ill-advised and complicated to interpret option
which offers nothing particularly useful.
Change-Id: Ia7741ed62ef977c96fa52299a884e404bee659ac
1. Fix a stupid error in types.cc
2. Update documentation for Solver::Options::dense_linear_algebra_library_type
3. Add a note to installation.rst to update the installation docs.
4. Mention GPU acceleration in features.rst
Change-Id: Id63202ff090e23bbb211d2ee458559fb8046281d
Add [[deprecate]] notices to everything LocalParameterization
related.
Make sure that Ceres can be compiled without triggering
deprecation warnings.
Update the documentation:
a. Add deprecation notices.
b. Document interaction between LocalParameterization and Manifold
coexisting in the Problem.
c. Add documentation for Manifold(s)
Change-Id: Ie4ad48963c83fded86e533c8c60561af402fbaff
- Also adds documentation of mixed precision solves to Sphinx docs.
- Fix reference to Sphinx theme used (RTD not better).
- Fix NOTE syntax in use_explicit_schur_complement Sphinx docs.
Change-Id: I7bdac0f07eb737f49b05e3fcaa3eebd087355d2d
- Removes all workarounds for pre-C++14 versions
- Removes '11' qualifier from C++ threading option and associated
defines.
- Fix missing inclusion of 'Multithreading' in reported Ceres components
when C++ threading model is enabled.
- Update Sphinx documentation to specify C++14 as minimum requirement.
Change-Id: I706c8b367b3221e3c4d1a0aaf669a8f9c911e438
Re-organize the section, add some more references and details for
existing preconditioners and add documentation for the SUBSET
precondition.
https://github.com/ceres-solver/ceres-solver/issues/490
Change-Id: I93d0af819c160f5e4ce48b18202f629ddb92ca7b
In the docs, `Solver::Options::gradient_check_relative_precision` is
documented to have a default precision of 1e08. That is incorrect, it
should be 1e-8.
Change-Id: Ib6b29e356738de4b555c77f7ffd1224d0cae4b6a
https://github.com/ceres-solver/ceres-solver/issues/270
Detailed list of changes:
1. Add SUBSET to the PreconditionerType enum.
2. Add Solver::Options::residual_blocks_for_subset_preconditioner
3. Integrate SubsetPreconditioner into the CGNR solver.
4. Add the reordering logic needed for this to TrustRegionPreprocessor.
5. Expect CreateJacobianBlockTranspose to take the starting row block
so that we can work with subparts of the Jacobian matrix.
6. Extend the denoising example to use this preconditioner.
As an illustration of its performance, we consider the performance of
denoising -input ../data/ceres_noisy.pgm --foe_file ../data/5x5.foe
tl;dr
For the same cost,
SPARSE_NORMAL_CHOLESKY - 81s
CGNR + JACOBI - 718s
CGNR + SUBSET - 57s
SPARSE_NORMAL_CHOLESKY
======================
Cost:
Initial 2.317806e+05
Final 2.232323e+04
Change 2.094574e+05
Minimizer iterations 10
Successful steps 10
Unsuccessful steps 0
Time (in seconds):
Preprocessor 2.999746
Residual only evaluation 2.306811 (10)
Jacobian & residual evaluation 7.421727 (10)
Linear solver 65.517273 (10)
Minimizer 78.731011
Postprocessor 0.026079
Total 81.756836
Termination: CONVERGENCE (Function tolerance reached. |cost_change|/cost: 8.573046e-04 <= 1.000000e-03)
CGNR + JACOBI
=============
Cost:
Initial 2.317806e+05
Final 2.232344e+04
Change 2.094572e+05
Minimizer iterations 10
Successful steps 10
Unsuccessful steps 0
Time (in seconds):
Preprocessor 0.648814
Residual only evaluation 2.297607 (10)
Jacobian & residual evaluation 7.327886 (10)
Linear solver 699.601248 (10)
Minimizer 712.419493
Postprocessor 0.024014
Total 713.092321
Termination: CONVERGENCE (Function tolerance reached. |cost_change|/cost: 8.528538e-04 <= 1.000000e-03)
CGNR + SUBSET (random 20% residuals used for the preconditioner)
===============================================================
Cost:
Initial 2.317806e+05
Final 2.232327e+04
Change 2.094574e+05
Minimizer iterations 10
Successful steps 10
Unsuccessful steps 0
Time (in seconds):
Preprocessor 1.472743
Residual only evaluation 2.428315 (10)
Jacobian & residual evaluation 7.367796 (10)
Linear solver 42.585999 (10)
Minimizer 55.664459
Postprocessor 0.024098
Total 57.161301
Termination: CONVERGENCE (Function tolerance reached. |cost_change|/cost: 8.538277e-04 <= 1.000000e-03)
Change-Id: Ifb011408bd53edbb9439b0b7345649a38f999e18
- In light of the C++11 threads threading option this is no longer
necessary for cross-platform threading support and did not offer a
noticeable performance gain over either the C++11 threads
implementation or OpenMP.
Change-Id: Icb588d520888c19a1775171795b55bcaffb3d256
Also removed Solver::Summary::num_linear_solver_threads_given
and Solver::Summary::num_linear_solver_threads_used.
Change-Id: I559145ae2e7af597ea06ec03d386645a3a892e9f
This adds a callback mechanism to for users to get notified just
before jacobian and residual evaluations. This will enable
aggressive caching and sharing of compute between cost functions.
Change-Id: I67993726920218edf71ab9ae70c34c204756c71a
1. Solver::Options::num_threads now controls parallelism in Ceres
Solver. The user specified value of
Solver::Options::num_linear_solver_threads is ignored.
2. If the user specifies Solver::Options::num_linear_solver_threads
and it is different from Solver::Options::num_threads,
a warning is printed.
3. Solver::Summary:num_linear_solver_threads_given and
Solver::Summary::num_linear_solver_threads_used are also
deprecated and are always set to Solver::Summary::num_threads_given
and Solver::Summary::num_threads_used.
Change-Id: I20b9336d9336e400e6f0a15b63857c0c43eb271c
1. Replace two maps by 1.
2. Update number of calls and the time for the call at the cost
of a single map lookup.
3. Add Solver::Summary::num_linear_solves.
Fixes https://github.com/ceres-solver/ceres-solver/issues/340
Change-Id: I71eb9be7fb363a8cb066591c4c1761f256c81677
1. Fix a typo in auto_diff_cost_function.h
2. Fix and update Solver::Summary::FullReport() text labels.
3. Add logging of the number of residual and jacobian evaluations
to the full report. The GradientProblemSolver already does this.
Change-Id: I41059af5f0ebe0417accbbc30b0808a4b04b9edb
There are platforms where OpenMP is not available. This
patch adds support for Intel Threading Building Blocks (TBB)
as an alternative threading backend.
Change-Id: I94497d7cba0c3cfaccfc992169236f17fe948ae9
THIS IS AN API BREAKING CHANGE.
Decouple the algorithm from the sparse linear algebra
library being used to perform the computation.
Before this change
Covariance::AlgorithmType had values
DENSE_SVD
EIGEN_SPARSE_QR
SUITE_SPARSE_QR
This has been replaced by two enums now.
Covariance::Options::sparse_linear_algebra_library_type
which can take values EIGEN_SPARSE, SUITE_SPARSE or CX_SPARSE.
The last one is currently not supported.
And Covariance::Options::algorithm_type takes values
DENSE_SVD
SPARSE_QR
This sets the stage for future extensions of the covariance
computation algorithm.
Also as part of this change, the covariance computation chapter
has been made a top level chapter on its own instead of being
buried deep inside the Solving Non-linear Least Squares problem.
Change-Id: Ibfbf60902d8d17694d9ff585047a5a57d329ab22
1. Refactor the python code that generates the template specializations
to remove code duplication.
2. Improved the logic for template specialization selection where
Eigen::Dynamic now serves as a wildcard.
3. Added schur_templates.h/cc which allows querying the set of available
template specializations without instantiating a linear solver.
4. Added Solver::Summary::schur_structre_given and
Solver::Summary::schur_structure_used and expose them in
Solver::Summary::FullReport for better performance debugging.
5. Updated the templates with newer dates and some minor comments cleanup
which lead to the the template specializations to be re-generated.
Change-Id: Iaf3c6f714353597899916c300465da01f151c3de
Solver::Options::numeric_derivative_relative_step_size to
Solver::Options::gradient_check_numeric_derivative_relative_step_size
Change-Id: Ib89ae3f87e588d4aba2a75361770d2cec26f07aa
Change the Ceres gradient checking API to make is useful for
unit testing, clean up code duplication and fix interaction between
gradient checking and local parameterizations.
There were two gradient checking implementations, one being used
when using the check_gradients flag in the Solver, the other
being a standalone class. The standalone version was restricted
to cost functions with fixed parameter sizes at compile time, which
is being lifted here. This enables it to be used inside the
GradientCheckingCostFunction as well.
In addition, this installs new hooks in the Solver to ensure
that Solve will fail if any incorrect gradients are detected. This
way, you can set the check_gradient flags to true and detect
errors in an automated way, instead of just printing error information
to the log. The error log is now also returned in the Solver summary
instead of being printed directly. The user can then decide what to
do with it. The existing hooks for user callbacks are used for
this purpose to keep the internal API changes minimal and non-invasive.
The last and biggest change is the way the the interaction between
local parameterizations and the gradient checker works. Before,
local parameterizations would be ignored by the checker. However,
if a cost function does not compute its Jacobian along the null
space of the local parameterization, this wil not have any effect
on the solver, but would result in a gradient checker error.
With this change, the Jacobians are multiplied by the Jacobians
of the respective local parameterization and thus being compared
in the tangent space only.
The typical use case for this are quaternion parameters, where
a cost function will typically assume that the quaternion is
always normalized, skipping the correct computation of the Jacobian
along the normal to save computation cost.
Change-Id: I5e1bb97b8a899436cea25101efe5011b0bb13282
Accumulate the number of steps of the line search algorithm
and report it as part of Summary::FullReport.
Change-Id: I1de12784009a3e08f2a2c2aff5085d57a3c73828
1. Add answers to a number of FAQs.
2. Add a note to the documentation for NumericDiffCostFunction that
NumericDiffOptions needs to be documented and mentioned.
3. Update the docs for Solver::Options::numeric_derivative_relative_step_size
to indicate that this setting only applies to the gradient checker.
4. Remove deprecated constructors from NumericDiffCostFunction and
DynamicNumericDiffCostFunction.
Change-Id: If8fc011b2a5996dbc2c51268aa477550ed014a1c
1. Fix a typo in the Trust Region algorithm.
2. Add ARL in the list of users.
3. Update the version history.
Change-Id: Ic286e8ef1a71af07f3890b7592dd3aed9c5f87ce
This CL is required to build Tango.
Inspired by this commit in RedwoodInternal repository:
commit 09dde53c248e04f432b5eccceea5daeedb706aea
Author: Mike Vitus <mike@hidof.com>
Date: Wed Apr 23 11:05:17 2014 -0700
Change-Id: I328b6634969de4ccdd71947945aa67a49ee9073f
- Previously we had no defined default value for
sparse_linear_algebra_library_type in Solver::Options if Ceres
was compiled with no sparse library available. Thus in that case,
the default value (dependent upon the compiler) would indicate that
one was available.
- Now we have an explicit option that means no sparse library is
available, which is now the default value in Solver::Options in this
case.
- Add a warning in CMake when the user disables all sparse libraries.
- Fix typos in trust_region_preprocessor_test:
(SUITE/CX)_SPARSE -> (SUITE/CX)SPARSE that induced failures when
no sparse libraries were available.
Change-Id: I869c399a12d42bfc44220cbb25ce6d6dd80236bd
1. Fix the release script to ignore the version.h checking.
2. Fix some ceres documentation formatting errors.
Change-Id: I3fd6b85e771b242f463d6a36c3efd8d691f9242f
1. Complete restructuring of the documentation to account for
GradientProblemSolver.
2. Update the version history to account for changes since 1.9.0.
3. Add links and document the various examples that ship with ceres.
4. Documentation for GradientProblem GradientProblemSolver.
Change-Id: If3a18f2850cbc98be1bc34435e9ea468785b8b27
Sameer Agarwal