Update Ceres to latest upstream version 2.1.0temp-ceres_update

This release deprecated the Parameterization API and the new Manifolds
API is to be used instead. This is what was done in the Libmv as part
of this change.

Additionally, remove the bundling scripts. Nowadays those are only
leading to a duplicated work to maintain.

1 files changed, 21 insertions, 19 deletions

diff --git a/extern/ceres/include/ceres/solver.h b/extern/ceres/include/ceres/solver.h
index 61b8dd53eb3..026fc1c0830 100644
--- a/extern/ceres/include/ceres/solver.h
+++ b/extern/ceres/include/ceres/solver.h
@@ -38,8 +38,9 @@
 #include <vector>
 
 #include "ceres/crs_matrix.h"
+#include "ceres/internal/config.h"
 #include "ceres/internal/disable_warnings.h"
-#include "ceres/internal/port.h"
+#include "ceres/internal/export.h"
 #include "ceres/iteration_callback.h"
 #include "ceres/ordered_groups.h"
 #include "ceres/problem.h"
@@ -363,23 +364,23 @@ class CERES_EXPORT Solver {
     std::unordered_set<ResidualBlockId>
         residual_blocks_for_subset_preconditioner;
 
-    // Ceres supports using multiple dense linear algebra libraries
-    // for dense matrix factorizations. Currently EIGEN and LAPACK are
-    // the valid choices. EIGEN is always available, LAPACK refers to
-    // the system BLAS + LAPACK library which may or may not be
+    // Ceres supports using multiple dense linear algebra libraries for dense
+    // matrix factorizations. Currently EIGEN, LAPACK and CUDA are the valid
+    // choices. EIGEN is always available, LAPACK refers to the system BLAS +
+    // LAPACK library which may or may not be available. CUDA refers to Nvidia's
+    // GPU based dense linear algebra library, which may or may not be
     // available.
     //
-    // This setting affects the DENSE_QR, DENSE_NORMAL_CHOLESKY and
-    // DENSE_SCHUR solvers. For small to moderate sized problem EIGEN
-    // is a fine choice but for large problems, an optimized LAPACK +
-    // BLAS implementation can make a substantial difference in
-    // performance.
+    // This setting affects the DENSE_QR, DENSE_NORMAL_CHOLESKY and DENSE_SCHUR
+    // solvers. For small to moderate sized problem EIGEN is a fine choice but
+    // for large problems, an optimized LAPACK + BLAS or CUDA implementation can
+    // make a substantial difference in performance.
     DenseLinearAlgebraLibraryType dense_linear_algebra_library_type = EIGEN;
 
-    // Ceres supports using multiple sparse linear algebra libraries
-    // for sparse matrix ordering and factorizations. Currently,
-    // SUITE_SPARSE and CX_SPARSE are the valid choices, depending on
-    // whether they are linked into Ceres at build time.
+    // Ceres supports using multiple sparse linear algebra libraries for sparse
+    // matrix ordering and factorizations. Currently, SUITE_SPARSE and CX_SPARSE
+    // are the valid choices, depending on whether they are linked into Ceres at
+    // build time.
     SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type =
 #if !defined(CERES_NO_SUITESPARSE)
         SUITE_SPARSE;
@@ -423,7 +424,7 @@ class CERES_EXPORT Solver {
     // each group, Ceres is free to order the parameter blocks as it
     // chooses.
     //
-    // If NULL, then all parameter blocks are assumed to be in the
+    // If nullptr, then all parameter blocks are assumed to be in the
     // same group and the solver is free to decide the best
     // ordering.
     //
@@ -536,8 +537,9 @@ class CERES_EXPORT Solver {
     // max_num_refinement_iterations to 2-3.
     //
     // NOTE2: The following two options are currently only applicable
-    // if sparse_linear_algebra_library_type is EIGEN_SPARSE and
-    // linear_solver_type is SPARSE_NORMAL_CHOLESKY, or SPARSE_SCHUR.
+    // if sparse_linear_algebra_library_type is EIGEN_SPARSE or
+    // ACCELERATE_SPARSE, and linear_solver_type is SPARSE_NORMAL_CHOLESKY
+    // or SPARSE_SCHUR.
     bool use_mixed_precision_solves = false;
 
     // Number steps of the iterative refinement process to run when
@@ -882,7 +884,7 @@ class CERES_EXPORT Solver {
     // Dimension of the tangent space of the problem (or the number of
     // columns in the Jacobian for the problem). This is different
     // from num_parameters if a parameter block is associated with a
-    // LocalParameterization
+    // LocalParameterization/Manifold.
     int num_effective_parameters = -1;
 
     // Number of residual blocks in the problem.
@@ -903,7 +905,7 @@ class CERES_EXPORT Solver {
     // number of columns in the Jacobian for the reduced
     // problem). This is different from num_parameters_reduced if a
     // parameter block in the reduced problem is associated with a
-    // LocalParameterization.
+    // LocalParameterization/Manifold.
     int num_effective_parameters_reduced = -1;
 
     // Number of residual blocks in the reduced problem.