covariance.h was using SUITE_SPARSE even when SUITESPARSE
was disabled because it did not have config.h included in it
so it did not see that CERES_NO_SUITESPARSE was defined.
Add more config.h includes to files that are using these
configuration macros.
Change-Id: I6b1d2c2bd9e559de40a6332cd6be85ad4da3377b
Overriding export gflags export macros breaks glog in shared Ceres
solver builds. Threfore, always compile gtest as a static library to
avoid the need of overriding the export macros.
Change-Id: Ibc9a04a771085caa8f02c81745ce626643df8450
These changes allow the use of a SuiteSparse CMake package from
https://github.com/sergiud/SuiteSparse that allows native compilation of
SuiteSparse using CMake on a variety of platforms Packages generated
using official SuiteSparse makefiles can still be used without
modifications. The find module remains agnostic to specific CMake
package implementation.
CMake packages have the advantage that they are self-contained and
relocatable. The latter is particularly useful in cross-compilation
scenarios.
Fixes#728
Change-Id: I089d5c6f87c05b1530a5ab9a36dff2fcbe82d13d
In many cases, manifolds stored in ProductManifold have a default
constructor which can simplify ProductManifold initialization even
further. Allow default construction of ProductManifold in this case.
Change-Id: I29b2612870c02232556688019a77049709684a55
* Fix workspace type in CUDADenseQR and CUDADenseCholesky --
Workspace sizes are in terms of number of elements, not bytes.
* Add cuda-memcheck tests to catch such CUDA memory errors in
the future.
Change-Id: I3dd0f0947daba9e4c6cd0216bef81d694547d505
Since the number of manifolds used to initialize ProductManifold and
their types are known at compile-time, it is possible to avoid storing
pointers to the base class as required by a homogeneous, currently
dynamically sized container. Instead, we can use std::tuple<> as a
heterogenous container with the number of elements fixed at compile-time
that allows us to store the concrete manifold realizations.
The advantage of this approach is that we can bypass the vtable when
iterating over each manifold within ProductManifold. The indirection is
invoked only once while accessing the ProductManifoldImpl members.
Additionally, potential dynamic memory allocations by a std::vector can
be completely avoided. This makes the ProductManifold implementation
more efficient both in memory and runtime.
Change-Id: Ic71b0c175ab726f8992e9703f7666bca477baf19
Previously they were defined in manifold.h but their implementations
were in the internal directory and to prevent circular dependencies
the implementation headers were pushed to the bottom of manifold.h
This started out as one header and has become progressively worse
as more manifolds are templated.
This change moves the two manifolds into their own headers which
also contain their implementations.
Change-Id: I671da0279a47cd2ff1f52c69a1d159426f55bd80
This brings it in line with other manifolds like SphereManifold
and LineManifold, where the user has the choice to specify the size
of the manifold at compile time or runtime.
Most of the time the size is known at compile time so this will
speed up the common case.
Change-Id: I0c7ff8b7a9a64a81203eb11afc074874e208815a
Disable the definition of `min`/`max` macros by defining `NOMINMAX`
and prevent macro substitution in the public interface.
Also, quiet floating-point comparisons are defined as template functions
by the MSVC STL which causes compilation errors due to ambiguities in
resolving the template parameter types.
Fixes#668Fixes#716Fixes#718
Change-Id: I5fe7832a6a3a7ad0421a2557527528c34b88e9c7
Also refactor the logic for generating ba tests a bit
breaking it into dense, sparse and iterative tests.
Change-Id: I6b33e3b047ef900b12907bd150febe4744779b7a
Current language standard selection mechanism is quite convoluted and
the logic for propagating a specific C++ language standard (which cannot
be fully enforced anyway) is unnecessarily complicated. Instead
communicate the minimum required C++ standard and let CMake handle the
requirement. This allows the compiler and consumers to use newer
language revisions if available. The language standard used to compile
Ceres solver can still be set via `CMAKE_CXX_STANDARD`.
Move to CMake 3.10 which is supported by Ubuntu 18.04 LTS and simplify
the corresponding language features request.
Change-Id: Ib1f95e2bc5f06bf1275a62565d303eb0f114d127
1. Add CUDA initialization and cleanup management to the
ContextImpl object. The ContextImpl is now solely responsible
for managing CUDA-related resources.
2. All CUDA dense solvers now use lazy CUDA initialization
via the ContextImpl object.
Change-Id: Ief456860c72e462367ee997d389c19e2bff50baf
Current language standard selection mechanism is quite convoluted and
the logic for propagating a specific C++ language standard (which cannot
be fully enforced anyway) is unnecessarily complicated. Instead
communicate the minimum required C++ standard and let CMake handle the
requirement. This allows the compiler and consumers to use newer
language revisions if available. The language standard used to compile
Ceres solver can still be set via `CMAKE_CXX_STANDARD`.
Move to CMake 3.10 which is supported by Ubuntu 18.04 LTS and simplify
the corresponding language features request.
Change-Id: Id3526c69990315289e7ea0fbcdeaa6af79d24d03
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 logic for checking for availability of CUDA as the
dense linear algebra library before allowing the user
to use it.
Change-Id: I0ceafa1052632504b33685bc731366ef6933e518
1. Add CUDADenseQR & tests.
CUDADenseQR uses the cuSolverDN LAPACK implementation
of QR factorization. A key limitation, however, is that
this solver does not perform singularity checking --
this is because cuSolverDN does not have a trtrs
implementation; we instead use cuBLAS' trsv for
backsubstitution.
2. All CPU -> GPU memory transfers are now async, and both
CUDADenseQR and CUDADenseCholesky explicitly manage their
own streams for async operations.
3. Simplified CUDADenseCholesky to only use the legacy 32-bit
cuSolverDN API.
Change-Id: I2a9b7b65469658ddfe33b5b2a3892c8744d6e437
Currently, the logic for exporting symbols is rather complicated: when
tests are enabled internal symbols are exported in addition to the
public symbols. Such logic causes several problems. (1) Test binaries
link against a Ceres build that is different from the final release
since fewer optimizations are applied if more symbols are exported. (2)
Also, some toolchains hide symbols by default breaking the existing
logic eventually causing linker errors.
Since internal symbols are not intended to be used outside of the
project, we can compile them into object files and use exactly the same
binary code both for the final build and the tests without relying on
conditionals.
By default, all symbols are now hidden unless annotated as public.
Internal symbols are explicitly marked as not being exported in case
users chose not to hide symbols by default.
Change-Id: I589dd10be2f6f438508783cf99d141af0120057b
Enabling the AVX2 instruction set causes a segmentation fault in mocked
manifold tests. This is due to Eigen vectors stored in a std::shared_ptr
for which the memory allocated by gmock is not aligned even though it is
expected to be by Eigen for correct use of packet math.
The problem does not occur if Ceres is compiled with C++17 (or later)
enabled due to the support for aligned new allocations.
Change-Id: I711abe9439cc411bd7a8b4936f3b93af07b7fbd6
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
This MR ports the LineParameterization of manifolds. The unit test are
rewritten to use the manifold test facilities.
The LineManifold is extended so that it can also handle dynamic size
ambient space dimensions.
Change-Id: I1fe3cd34b56f74b72ca028c34f5368e9df9fe4d7
Do not define trivial constructors or destructors unless necessary
(e.g., for implementing pimpl) following the rule of zero. Define
virtual base class destructors out-of-line to avoid emitting vtables in
every translation unit.
Change-Id: Iea2d8978e62a8ee5a97b86cbb4e858d56e0fb274
Applied changes correspond to clang-tidy fixes
stemming from the modernize-use-equals-default check.
Change-Id: I254b0908a76d464131564b637cd0e42a6b03fb5a
virtual can be ambiguous. Applied changes correspond to clang-tidy fixes
stemming from the modernize-use-override check.
Change-Id: I973afd4680a5df587419777504aeb94467196b89
1. Add CUDADenseCholesky64Bit, CUDADenseCholesky32Bit, & tests.
CUDADenseCholesky32Bit uses the legacy versions of potrf/potrs
in cuSolverDN, while CUDADenseCholesky64Bit uses the new 64-bit
versions available since Cuda 11.1. The legacy versions are
provided since some platforms such as the Nvidia Jetsons only
support Cuda 10.2.
2. Expose CUDA as a new option under DenseLinearAlgebraLibraryType.
The relevant option to string and string to option helper functions
are modified accordingly.
3. Add cuda as a dense_linear_algebra_library option in bundle_adjuster
to demonstrate the use of the new CUDA option.
Change-Id: I23615e1d301df5185ed646b3e33ee802508dae86
This MR adds SphereManifold ported from
HomogeneousVectorParameterization. Additionally the minus operator
and jacobian evaluation was implemented.
The unit tests were almost completly reimplemented and uses the
test facilities provided for manifolds.
Change-Id: Iccf72a2333bc921ff24c4d831db35020c653ee86
Sameer Agarwal