Remove Protocol Buffers support.
Change-Id: I451c543c82cdfb566736aab94d836abcfb5c689d
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 33fbefd..7431c0f 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -514,23 +514,6 @@
ADD_DEFINITIONS(-DCERES_WORK_AROUND_ANDROID_NDK_COMPILER_BUG)
ENDIF (BUILD_ANDROID)
-# Protocol buffers
-OPTION(PROTOBUF
- "Enable protocol buffers support."
- ON)
-
-IF (PROTOBUF)
- FIND_PACKAGE(Protobuf)
- IF (PROTOBUF_FOUND)
- INCLUDE_DIRECTORIES(${PROTOBUF_INCLUDE_DIRS})
- INCLUDE_DIRECTORIES(${CMAKE_CURRENT_BINARY_DIR}/internal)
- ELSE (PROTOBUF_FOUND)
- ADD_DEFINITIONS(-DCERES_NO_PROTOCOL_BUFFERS)
- ENDIF (PROTOBUF_FOUND)
-ELSE (PROTOBUF)
- ADD_DEFINITIONS(-DCERES_NO_PROTOCOL_BUFFERS)
-ENDIF (PROTOBUF)
-
OPTION(DISABLE_TR1
"Don't use TR1. This replaces some hash tables with sets. Slower."
OFF)
diff --git a/android/build_android.sh b/android/build_android.sh
index 5cb4383..053b828 100644
--- a/android/build_android.sh
+++ b/android/build_android.sh
@@ -151,5 +151,4 @@
-DBUILD_ANDROID=ON \
-DSUITESPARSE=OFF \
-DGFLAGS=OFF \
- -DCXSPARSE=OFF \
- -DPROTOBUF=OFF
+ -DCXSPARSE=OFF
diff --git a/data/problem-6-1384-000.lsqp b/data/problem-6-1384-000.lsqp
deleted file mode 100644
index ea78dfd..0000000
--- a/data/problem-6-1384-000.lsqp
+++ /dev/null
Binary files differ
diff --git a/docs/source/building.rst b/docs/source/building.rst
index b91027b..7bc09e7 100644
--- a/docs/source/building.rst
+++ b/docs/source/building.rst
@@ -57,11 +57,6 @@
atlas.sourceforge.net/>`_, both of which ship with BLAS and LAPACK
routines.
-8. `protobuf <http://code.google.com/p/protobuf/>`_ is used for
-serializing and deserializing linear least squares problems to
-disk. This is useful for debugging and testing. It is an optional
-dependency and without it some of the tests will be disabled.
-
.. _section-linux:
Building on Linux
@@ -91,8 +86,6 @@
sudo apt-get install libeigen3-dev
# SuiteSparse and CXSparse
sudo apt-get install libsuitesparse-dev
- # protobuf
- sudo apt-get install libprotobuf-dev
We are now ready to build and test Ceres.
@@ -189,8 +182,6 @@
brew install eigen
# SuiteSparse and CXSparse
brew install suite-sparse
- # protobuf
- brew install protobuf
We are now ready to build and test Ceres.
@@ -296,11 +287,6 @@
customize the build process by passing appropriate flags to
``CMake``. Use these flags only if you really know what you are doing.
-#. ``-DPROTOBUF=OFF``: ``protobuf`` is a large and complicated
- dependency. If you do not care for the tests that depend on it and
- the logging support it enables, you can use this flag to turn it
- off.
-
#. ``-DSUITESPARSE=OFF``: By default, Ceres will link to
``SuiteSparse`` if all its dependencies are present. Use this flag
to build Ceres without ``SuiteSparse``. This will also disable
diff --git a/docs/source/solving.rst b/docs/source/solving.rst
index d3f2d0f..254c120 100644
--- a/docs/source/solving.rst
+++ b/docs/source/solving.rst
@@ -1205,15 +1205,6 @@
printed as dense vectors. This should only be used for small
problems.
- * ``PROTOBUF`` Write out the linear least squares problem to the
- directory pointed to by
- :member:`Solver::Options::trust_region_problem_dump_directory` as
- a protocol buffer. ``linear_least_squares_problems.h/cc``
- contains routines for loading these problems. For details on the
- on disk format used, see ``matrix.proto``. The files are named
- ``ceres_solver_iteration_???.bin``. This requires that ``protobuf`` be
- linked into Ceres Solver.
-
* ``TEXTFILE`` Write out the linear least squares problem to the
directory pointed to by
:member:`Solver::Options::trust_region_problem_dump_directory` as
diff --git a/include/ceres/types.h b/include/ceres/types.h
index 5512340..5edd128 100644
--- a/include/ceres/types.h
+++ b/include/ceres/types.h
@@ -310,13 +310,6 @@
CONSOLE,
// Write out the linear least squares problem to the directory
- // pointed to by Solver::Options::lsqp_dump_directory as a protocol
- // buffer. linear_least_squares_problems.h/cc contains routines for
- // loading these problems. For details on the on disk format used,
- // see matrix.proto. The files are named lm_iteration_???.lsqp.
- PROTOBUF,
-
- // Write out the linear least squares problem to the directory
// pointed to by Solver::Options::lsqp_dump_directory as text files
// which can be read into MATLAB/Octave. The Jacobian is dumped as a
// text file containing (i,j,s) triplets, the vectors D, x and f are
diff --git a/internal/ceres/CMakeLists.txt b/internal/ceres/CMakeLists.txt
index f77c066..3b8b2f0 100644
--- a/internal/ceres/CMakeLists.txt
+++ b/internal/ceres/CMakeLists.txt
@@ -118,10 +118,6 @@
SET(LIB_SUFFIX "64")
ENDIF ()
-If (PROTOBUF_FOUND)
- PROTOBUF_GENERATE_CPP(PROTO_SRCS PROTO_HDRS matrix.proto)
-ENDIF (PROTOBUF_FOUND)
-
# Also depend on the header files so that they appear in IDEs.
FILE(GLOB CERES_INTERNAL_HDRS *.h)
@@ -186,13 +182,7 @@
ENDIF (NOT MSVC)
ENDIF (OPENMP_FOUND)
-IF (PROTOBUF_FOUND)
- LIST(APPEND CERES_LIBRARY_DEPENDENCIES ${PROTOBUF_LIBRARY})
-ENDIF (PROTOBUF_FOUND)
-
SET(CERES_LIBRARY_SOURCE
- ${PROTO_SRCS}
- ${PROTO_HDRS}
${CERES_INTERNAL_SRC}
${CERES_INTERNAL_HDRS}
${CERES_INTERNAL_SCHUR_FILES})
diff --git a/internal/ceres/block_sparse_matrix.cc b/internal/ceres/block_sparse_matrix.cc
index ae36d60..fdd762c 100644
--- a/internal/ceres/block_sparse_matrix.cc
+++ b/internal/ceres/block_sparse_matrix.cc
@@ -36,7 +36,6 @@
#include "ceres/blas.h"
#include "ceres/block_structure.h"
#include "ceres/internal/eigen.h"
-#include "ceres/matrix_proto.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
@@ -82,31 +81,6 @@
CHECK_NOTNULL(values_.get());
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-BlockSparseMatrix::BlockSparseMatrix(const SparseMatrixProto& outer_proto) {
- CHECK(outer_proto.has_block_matrix());
-
- const BlockSparseMatrixProto& proto = outer_proto.block_matrix();
- CHECK(proto.has_num_rows());
- CHECK(proto.has_num_cols());
- CHECK_EQ(proto.num_nonzeros(), proto.values_size());
-
- num_rows_ = proto.num_rows();
- num_cols_ = proto.num_cols();
- num_nonzeros_ = proto.num_nonzeros();
-
- // Copy out the values into *this.
- values_.reset(new double[num_nonzeros_]);
- for (int i = 0; i < proto.num_nonzeros(); ++i) {
- values_[i] = proto.values(i);
- }
-
- // Create the block structure according to the proto.
- block_structure_.reset(new CompressedRowBlockStructure);
- ProtoToBlockStructure(proto.block_structure(), block_structure_.get());
-}
-#endif
-
void BlockSparseMatrix::SetZero() {
fill(values_.get(), values_.get() + num_nonzeros_, 0.0);
}
@@ -243,21 +217,6 @@
return block_structure_.get();
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-void BlockSparseMatrix::ToProto(SparseMatrixProto* outer_proto) const {
- outer_proto->Clear();
-
- BlockSparseMatrixProto* proto = outer_proto->mutable_block_matrix();
- proto->set_num_rows(num_rows_);
- proto->set_num_cols(num_cols_);
- proto->set_num_nonzeros(num_nonzeros_);
- for (int i = 0; i < num_nonzeros_; ++i) {
- proto->add_values(values_[i]);
- }
- BlockStructureToProto(*block_structure_, proto->mutable_block_structure());
-}
-#endif
-
void BlockSparseMatrix::ToTextFile(FILE* file) const {
CHECK_NOTNULL(file);
for (int i = 0; i < block_structure_->rows.size(); ++i) {
diff --git a/internal/ceres/block_sparse_matrix.h b/internal/ceres/block_sparse_matrix.h
index e03c56f..e17d12a 100644
--- a/internal/ceres/block_sparse_matrix.h
+++ b/internal/ceres/block_sparse_matrix.h
@@ -43,7 +43,6 @@
namespace ceres {
namespace internal {
-class SparseMatrixProto;
class TripletSparseMatrix;
// This class implements the SparseMatrix interface for storing and
@@ -64,11 +63,6 @@
// CompressedRowBlockStructure objects.
explicit BlockSparseMatrix(CompressedRowBlockStructure* block_structure);
- // Construct a block sparse matrix from a protocol buffer.
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- explicit BlockSparseMatrix(const SparseMatrixProto& proto);
-#endif
-
BlockSparseMatrix();
virtual ~BlockSparseMatrix();
@@ -79,9 +73,6 @@
virtual void SquaredColumnNorm(double* x) const;
virtual void ScaleColumns(const double* scale);
virtual void ToDenseMatrix(Matrix* dense_matrix) const;
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- virtual void ToProto(SparseMatrixProto* proto) const;
-#endif
virtual void ToTextFile(FILE* file) const;
virtual int num_rows() const { return num_rows_; }
diff --git a/internal/ceres/block_sparse_matrix_test.cc b/internal/ceres/block_sparse_matrix_test.cc
index 457a2fb..36b7385 100644
--- a/internal/ceres/block_sparse_matrix_test.cc
+++ b/internal/ceres/block_sparse_matrix_test.cc
@@ -35,7 +35,6 @@
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/linear_least_squares_problems.h"
-#include "ceres/matrix_proto.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
@@ -109,27 +108,5 @@
EXPECT_LT((m_a - m_b).norm(), 1e-12);
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-TEST_F(BlockSparseMatrixTest, Serialization) {
- // Roundtrip through serialization and check for equality.
- SparseMatrixProto proto;
- A_->ToProto(&proto);
-
- LOG(INFO) << proto.DebugString();
-
- BlockSparseMatrix A2(proto);
-
- Matrix m_a;
- Matrix m_b;
- A_->ToDenseMatrix(&m_a);
- A2.ToDenseMatrix(&m_b);
-
- LOG(INFO) << "\n" << m_a;
- LOG(INFO) << "\n" << m_b;
-
- EXPECT_LT((m_a - m_b).norm(), 1e-12);
-}
-#endif
-
} // namespace internal
} // namespace ceres
diff --git a/internal/ceres/block_structure.cc b/internal/ceres/block_structure.cc
index e611311..5a1a5e1 100644
--- a/internal/ceres/block_structure.cc
+++ b/internal/ceres/block_structure.cc
@@ -29,7 +29,6 @@
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/block_structure.h"
-#include "ceres/matrix_proto.h"
namespace ceres {
namespace internal {
@@ -38,55 +37,5 @@
return (lhs.block_id < rhs.block_id);
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-void ProtoToBlockStructure(const BlockStructureProto &proto,
- CompressedRowBlockStructure *block_structure) {
- // Decode the column blocks.
- block_structure->cols.resize(proto.cols_size());
- for (int i = 0; i < proto.cols_size(); ++i) {
- block_structure->cols[i].size = proto.cols(i).size();
- block_structure->cols[i].position =
- proto.cols(i).position();
- }
- // Decode the row structure.
- block_structure->rows.resize(proto.rows_size());
- for (int i = 0; i < proto.rows_size(); ++i) {
- const CompressedRowProto &row = proto.rows(i);
- block_structure->rows[i].block.size = row.block().size();
- block_structure->rows[i].block.position = row.block().position();
-
- // Copy the cells within the row.
- block_structure->rows[i].cells.resize(row.cells_size());
- for (int j = 0; j < row.cells_size(); ++j) {
- const CellProto &cell = row.cells(j);
- block_structure->rows[i].cells[j].block_id = cell.block_id();
- block_structure->rows[i].cells[j].position = cell.position();
- }
- }
-}
-
-void BlockStructureToProto(const CompressedRowBlockStructure &block_structure,
- BlockStructureProto *proto) {
- // Encode the column blocks.
- for (int i = 0; i < block_structure.cols.size(); ++i) {
- BlockProto *block = proto->add_cols();
- block->set_size(block_structure.cols[i].size);
- block->set_position(block_structure.cols[i].position);
- }
- // Encode the row structure.
- for (int i = 0; i < block_structure.rows.size(); ++i) {
- CompressedRowProto *row = proto->add_rows();
- BlockProto *block = row->mutable_block();
- block->set_size(block_structure.rows[i].block.size);
- block->set_position(block_structure.rows[i].block.position);
- for (int j = 0; j < block_structure.rows[i].cells.size(); ++j) {
- CellProto *cell = row->add_cells();
- cell->set_block_id(block_structure.rows[i].cells[j].block_id);
- cell->set_position(block_structure.rows[i].cells[j].position);
- }
- }
-}
-#endif
-
} // namespace internal
} // namespace ceres
diff --git a/internal/ceres/compressed_row_sparse_matrix.h b/internal/ceres/compressed_row_sparse_matrix.h
index d60b580..7da723c 100644
--- a/internal/ceres/compressed_row_sparse_matrix.h
+++ b/internal/ceres/compressed_row_sparse_matrix.h
@@ -92,13 +92,6 @@
virtual const double* values() const { return &values_[0]; }
virtual double* mutable_values() { return &values_[0]; }
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- // Dump the sparse matrix to a proto. Destroys the contents of proto.
- virtual void ToProto(SparseMatrixProto* proto) const {
- LOG(FATAL) << "Broken.;";
- }
-#endif
-
// Delete the bottom delta_rows.
// num_rows -= delta_rows
void DeleteRows(int delta_rows);
diff --git a/internal/ceres/dense_sparse_matrix.cc b/internal/ceres/dense_sparse_matrix.cc
index f94b888..d67474f 100644
--- a/internal/ceres/dense_sparse_matrix.cc
+++ b/internal/ceres/dense_sparse_matrix.cc
@@ -31,7 +31,6 @@
#include "ceres/dense_sparse_matrix.h"
#include <algorithm>
-#include "ceres/matrix_proto.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/port.h"
@@ -81,22 +80,6 @@
has_diagonal_reserved_(false) {
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-DenseSparseMatrix::DenseSparseMatrix(const SparseMatrixProto& outer_proto)
- : m_(Eigen::MatrixXd::Zero(
- outer_proto.dense_matrix().num_rows(),
- outer_proto.dense_matrix().num_cols())),
- has_diagonal_appended_(false),
- has_diagonal_reserved_(false) {
- const DenseSparseMatrixProto& proto = outer_proto.dense_matrix();
- for (int i = 0; i < m_.rows(); ++i) {
- for (int j = 0; j < m_.cols(); ++j) {
- m_(i, j) = proto.values(m_.cols() * i + j);
- }
- }
-}
-#endif
-
void DenseSparseMatrix::SetZero() {
m_.setZero();
}
@@ -122,22 +105,6 @@
*dense_matrix = m_.block(0, 0, num_rows(), num_cols());
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-void DenseSparseMatrix::ToProto(SparseMatrixProto* outer_proto) const {
- CHECK(!has_diagonal_appended_) << "Not supported.";
- outer_proto->Clear();
- DenseSparseMatrixProto* proto = outer_proto->mutable_dense_matrix();
-
- proto->set_num_rows(num_rows());
- proto->set_num_cols(num_cols());
-
- int num_nnz = num_nonzeros();
- for (int i = 0; i < num_nnz; ++i) {
- proto->add_values(m_.data()[i]);
- }
-}
-#endif
-
void DenseSparseMatrix::AppendDiagonal(double *d) {
CHECK(!has_diagonal_appended_);
if (!has_diagonal_reserved_) {
diff --git a/internal/ceres/dense_sparse_matrix.h b/internal/ceres/dense_sparse_matrix.h
index 96a715d..981e2d1 100644
--- a/internal/ceres/dense_sparse_matrix.h
+++ b/internal/ceres/dense_sparse_matrix.h
@@ -42,7 +42,6 @@
namespace ceres {
namespace internal {
-class SparseMatrixProto;
class TripletSparseMatrix;
class DenseSparseMatrix : public SparseMatrix {
@@ -51,9 +50,6 @@
// m. This assumes that m does not have any repeated entries.
explicit DenseSparseMatrix(const TripletSparseMatrix& m);
explicit DenseSparseMatrix(const ColMajorMatrix& m);
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- explicit DenseSparseMatrix(const SparseMatrixProto& proto);
-#endif
DenseSparseMatrix(int num_rows, int num_cols);
DenseSparseMatrix(int num_rows, int num_cols, bool reserve_diagonal);
@@ -67,9 +63,6 @@
virtual void SquaredColumnNorm(double* x) const;
virtual void ScaleColumns(const double* scale);
virtual void ToDenseMatrix(Matrix* dense_matrix) const;
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- virtual void ToProto(SparseMatrixProto* proto) const;
-#endif
virtual void ToTextFile(FILE* file) const;
virtual int num_rows() const;
virtual int num_cols() const;
diff --git a/internal/ceres/dense_sparse_matrix_test.cc b/internal/ceres/dense_sparse_matrix_test.cc
index 3f8215d..e8bff2b 100644
--- a/internal/ceres/dense_sparse_matrix_test.cc
+++ b/internal/ceres/dense_sparse_matrix_test.cc
@@ -36,7 +36,6 @@
#include "ceres/casts.h"
#include "ceres/linear_least_squares_problems.h"
-#include "ceres/matrix_proto.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.h"
@@ -156,22 +155,6 @@
CompareMatrices(tsm.get(), dsm.get());
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-TEST_F(DenseSparseMatrixTest, Serialization) {
- SparseMatrixProto proto;
- dsm->ToProto(&proto);
-
- DenseSparseMatrix n(proto);
- ASSERT_EQ(dsm->num_rows(), n.num_rows());
- ASSERT_EQ(dsm->num_cols(), n.num_cols());
- ASSERT_EQ(dsm->num_nonzeros(), n.num_nonzeros());
-
- for (int i = 0; i < n.num_rows() + 1; ++i) {
- ASSERT_EQ(dsm->values()[i], proto.dense_matrix().values(i));
- }
-}
-#endif
-
TEST_F(DenseSparseMatrixTest, ToDenseMatrix) {
Matrix tsm_dense;
Matrix dsm_dense;
@@ -182,54 +165,5 @@
EXPECT_EQ((tsm_dense - dsm_dense).norm(), 0.0);
}
-// TODO(keir): Make this work without protocol buffers.
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-TEST_F(DenseSparseMatrixTest, AppendDiagonal) {
- DenseSparseMatrixProto proto;
- proto.set_num_rows(3);
- proto.set_num_cols(3);
- for (int i = 0; i < 9; ++i) {
- proto.add_values(i);
- }
- SparseMatrixProto outer_proto;
- *outer_proto.mutable_dense_matrix() = proto;
-
- DenseSparseMatrix dsm(outer_proto);
-
- double diagonal[] = { 10, 11, 12 };
- dsm.AppendDiagonal(diagonal);
-
- // Verify the diagonal got added.
- Matrix m = dsm.matrix();
-
- EXPECT_EQ(6, m.rows());
- EXPECT_EQ(3, m.cols());
- for (int i = 0; i < 3; ++i) {
- for (int j = 0; j < 3; ++j) {
- EXPECT_EQ(3 * i + j, m(i, j));
- if (i == j) {
- EXPECT_EQ(10 + i, m(i + 3, j));
- } else {
- EXPECT_EQ(0, m(i + 3, j));
- }
- }
- }
-
- // Verify the diagonal gets removed.
- dsm.RemoveDiagonal();
-
- m = dsm.matrix();
-
- EXPECT_EQ(3, m.rows());
- EXPECT_EQ(3, m.cols());
-
- for (int i = 0; i < 3; ++i) {
- for (int j = 0; j < 3; ++j) {
- EXPECT_EQ(3 * i + j, m(i, j));
- }
- }
-}
-#endif
-
} // namespace internal
} // namespace ceres
diff --git a/internal/ceres/linear_least_squares_problems.cc b/internal/ceres/linear_least_squares_problems.cc
index df6d03f..24ba565 100644
--- a/internal/ceres/linear_least_squares_problems.cc
+++ b/internal/ceres/linear_least_squares_problems.cc
@@ -38,7 +38,6 @@
#include "ceres/casts.h"
#include "ceres/file.h"
#include "ceres/internal/scoped_ptr.h"
-#include "ceres/matrix_proto.h"
#include "ceres/stringprintf.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/types.h"
@@ -63,74 +62,6 @@
return NULL;
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromFile(
- const string& filename) {
- LinearLeastSquaresProblemProto problem_proto;
- {
- string serialized_proto;
- ReadFileToStringOrDie(filename, &serialized_proto);
- CHECK(problem_proto.ParseFromString(serialized_proto));
- }
-
- LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem;
- const SparseMatrixProto& A = problem_proto.a();
-
- if (A.has_block_matrix()) {
- problem->A.reset(new BlockSparseMatrix(A));
- } else if (A.has_triplet_matrix()) {
- problem->A.reset(new TripletSparseMatrix(A));
- } else {
- LOG(FATAL) << "Broken.";
- }
-
- if (problem_proto.b_size() > 0) {
- problem->b.reset(new double[problem_proto.b_size()]);
- for (int i = 0; i < problem_proto.b_size(); ++i) {
- problem->b[i] = problem_proto.b(i);
- }
- }
-
- if (problem_proto.d_size() > 0) {
- problem->D.reset(new double[problem_proto.d_size()]);
- for (int i = 0; i < problem_proto.d_size(); ++i) {
- problem->D[i] = problem_proto.d(i);
- }
- }
-
- if (problem_proto.d_size() > 0) {
- if (problem_proto.x_size() > 0) {
- problem->x_D.reset(new double[problem_proto.x_size()]);
- for (int i = 0; i < problem_proto.x_size(); ++i) {
- problem->x_D[i] = problem_proto.x(i);
- }
- }
- } else {
- if (problem_proto.x_size() > 0) {
- problem->x.reset(new double[problem_proto.x_size()]);
- for (int i = 0; i < problem_proto.x_size(); ++i) {
- problem->x[i] = problem_proto.x(i);
- }
- }
- }
-
- problem->num_eliminate_blocks = 0;
- if (problem_proto.has_num_eliminate_blocks()) {
- problem->num_eliminate_blocks = problem_proto.num_eliminate_blocks();
- }
-
- return problem;
-}
-#else
-LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromFile(
- const string& filename) {
- LOG(FATAL)
- << "Loading a least squares problem from disk requires "
- << "Ceres to be built with Protocol Buffers support.";
- return NULL;
-}
-#endif // CERES_NO_PROTOCOL_BUFFERS
-
/*
A = [1 2]
[3 4]
@@ -598,56 +529,6 @@
return true;
};
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& filename_base,
- const SparseMatrix* A,
- const double* D,
- const double* b,
- const double* x,
- int num_eliminate_blocks) {
- CHECK_NOTNULL(A);
- LinearLeastSquaresProblemProto lsqp;
- A->ToProto(lsqp.mutable_a());
-
- if (D != NULL) {
- for (int i = 0; i < A->num_cols(); ++i) {
- lsqp.add_d(D[i]);
- }
- }
-
- if (b != NULL) {
- for (int i = 0; i < A->num_rows(); ++i) {
- lsqp.add_b(b[i]);
- }
- }
-
- if (x != NULL) {
- for (int i = 0; i < A->num_cols(); ++i) {
- lsqp.add_x(x[i]);
- }
- }
-
- lsqp.set_num_eliminate_blocks(num_eliminate_blocks);
-
- const string filename = filename_base + ".bin";
- LOG(INFO) << "Dumping least squares problem to disk. File: " << filename;
- WriteStringToFileOrDie(lsqp.SerializeAsString(), filename);
- return true;
-}
-#else
-bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& filename_base,
- const SparseMatrix* A,
- const double* D,
- const double* b,
- const double* x,
- int num_eliminate_blocks) {
- LOG(ERROR) << "Dumping least squares problems is only "
- << "supported when Ceres is compiled with "
- << "protocol buffer support.";
- return false;
-}
-#endif
-
void WriteArrayToFileOrDie(const string& filename,
const double* x,
const int size) {
@@ -732,12 +613,6 @@
case CONSOLE:
return DumpLinearLeastSquaresProblemToConsole(A, D, b, x,
num_eliminate_blocks);
- case PROTOBUF:
- return DumpLinearLeastSquaresProblemToProtocolBuffer(
- filename_base,
- A, D, b, x,
- num_eliminate_blocks);
-
case TEXTFILE:
return DumpLinearLeastSquaresProblemToTextFile(filename_base,
A, D, b, x,
diff --git a/internal/ceres/matrix.proto b/internal/ceres/matrix.proto
deleted file mode 100644
index 55a01d2..0000000
--- a/internal/ceres/matrix.proto
+++ /dev/null
@@ -1,143 +0,0 @@
-// Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
-// http://code.google.com/p/ceres-solver/
-//
-// Redistribution and use in source and binary forms, with or without
-// modification, are permitted provided that the following conditions are met:
-//
-// * Redistributions of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-// * Redistributions in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-// * Neither the name of Google Inc. nor the names of its contributors may be
-// used to endorse or promote products derived from this software without
-// specific prior written permission.
-//
-// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
-// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
-// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
-// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
-// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
-// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
-// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
-// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
-// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
-// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-// POSSIBILITY OF SUCH DAMAGE.
-//
-// Author: keir@google.com (Keir Mierle)
-
-syntax = "proto2";
-
-package ceres.internal;
-
-message BlockProto {
- // The span of the block.
- optional int32 size = 1;
-
- // Position along the row or column (depending on storage orientation).
- optional int32 position = 2;
-}
-
-message CellProto {
- // Column or row block id as appropriate.
- optional int32 block_id = 1;
-
- // Position in the values array the cell is located. Each cell is stored as a
- // row-major chunk inside the values array.
- optional int32 position = 2;
-}
-
-// A single row or column, depending on the matrix type.
-message CompressedRowProto {
- optional BlockProto block = 2;
- repeated CellProto cells = 1;
-}
-
-message BlockStructureProto {
- repeated BlockProto cols = 1;
- repeated CompressedRowProto rows = 2;
-}
-
-// A block sparse matrix, either in column major or row major format.
-message BlockSparseMatrixProto {
- optional int64 num_rows = 2;
- optional int64 num_cols = 3;
- optional int64 num_nonzeros = 4;
- repeated double values = 1 [packed=true];
-
- optional BlockStructureProto block_structure = 5;
-}
-
-message TripletSparseMatrixProto {
- optional int64 num_rows = 4;
- optional int64 num_cols = 5;
- optional int64 num_nonzeros = 6;
-
- // The data is stored as three arrays. For each i, values(i) is stored at the
- // location (rows(i), cols(i)). If the there are multiple entries with the
- // same (rows(i), cols(i)), the values entries corresponding to them are
- // summed up.
- repeated int64 rows = 1 [packed=true];
- repeated int64 cols = 2 [packed=true];
- repeated double values = 3 [packed=true];
-}
-
-message CompressedRowSparseMatrixProto {
- optional int64 num_rows = 4;
- optional int64 num_cols = 5;
-
- repeated int64 rows = 1 [packed=true];
- repeated int64 cols = 2 [packed=true];
- repeated double values = 3 [packed=true];
-}
-
-message DenseSparseMatrixProto {
- optional int64 num_rows = 1;
- optional int64 num_cols = 2;
-
- // Entries are stored in row-major order.
- repeated double values = 3 [packed=true];
-}
-
-// A sparse matrix. It is a union; only one field is permitted. If new sparse
-// implementations are added, update this proto accordingly.
-message SparseMatrixProto {
- optional TripletSparseMatrixProto triplet_matrix = 1;
- optional BlockSparseMatrixProto block_matrix = 2;
- optional CompressedRowSparseMatrixProto compressed_row_matrix = 3;
- optional DenseSparseMatrixProto dense_matrix = 4;
-}
-
-// A linear least squares problem.
-//
-// Given a matrix A, an optional diagonal matrix D as a vector, and a vector b,
-// the proto represents the following linear least squares problem.
-//
-// | A | x = | b |
-// | D | | 0 |
-//
-// If D is empty, then the problem is considered to be
-//
-// A x = b
-//
-// The desired solution for the problem is the vector x that solves the
-// following optimization problem:
-//
-// arg min_x ||Ax - b||^2 + ||Dx||^2
-//
-// If x is present, then it is the expected solution to the
-// problem. The dimensions of A, b, x, and D should be consistent.
-message LinearLeastSquaresProblemProto {
- optional SparseMatrixProto a = 1;
- repeated double b = 2 [packed=true];
- repeated double d = 3 [packed=true];
- repeated double x = 4 [packed=true];
- // If the problem is of SfM type, i.e it has a generalized
- // bi-partite structure, then num_eliminate_blocks is the number of
- // column blocks that are to eliminated in the formation of the
- // Schur complement. For more details see
- // explicit_schur_complement_solver.h.
- optional int32 num_eliminate_blocks = 5;
-}
diff --git a/internal/ceres/matrix_proto.h b/internal/ceres/matrix_proto.h
deleted file mode 100644
index 94b3076..0000000
--- a/internal/ceres/matrix_proto.h
+++ /dev/null
@@ -1,40 +0,0 @@
-// Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
-// http://code.google.com/p/ceres-solver/
-//
-// Redistribution and use in source and binary forms, with or without
-// modification, are permitted provided that the following conditions are met:
-//
-// * Redistributions of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-// * Redistributions in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-// * Neither the name of Google Inc. nor the names of its contributors may be
-// used to endorse or promote products derived from this software without
-// specific prior written permission.
-//
-// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
-// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
-// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
-// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
-// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
-// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
-// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
-// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
-// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
-// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-// POSSIBILITY OF SUCH DAMAGE.
-//
-// Author: keir@google.com (Keir Mierle)
-//
-// A portability header to make optional protocol buffer support less intrusive.
-
-#ifndef CERES_INTERNAL_MATRIX_PROTO_H_
-#define CERES_INTERNAL_MATRIX_PROTO_H_
-
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-#include "ceres/matrix.pb.h"
-#endif
-
-#endif // CERES_INTERNAL_MATRIX_PROTO_H_
diff --git a/internal/ceres/schur_eliminator_test.cc b/internal/ceres/schur_eliminator_test.cc
index 56db598..503a931 100644
--- a/internal/ceres/schur_eliminator_test.cc
+++ b/internal/ceres/schur_eliminator_test.cc
@@ -214,16 +214,5 @@
EliminateSolveAndCompare(VectorRef(D.get(), A->num_cols()), false, 1e-14);
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-TEST_F(SchurEliminatorTest, BlockProblem) {
- const string input_file = TestFileAbsolutePath("problem-6-1384-000.lsqp");
-
- SetUpFromFilename(input_file);
- ComputeReferenceSolution(VectorRef(D.get(), A->num_cols()));
- EliminateSolveAndCompare(VectorRef(D.get(), A->num_cols()), true, 1e-10);
- EliminateSolveAndCompare(VectorRef(D.get(), A->num_cols()), false, 1e-10);
-}
-#endif // CERES_NO_PROTOCOL_BUFFERS
-
} // namespace internal
} // namespace ceres
diff --git a/internal/ceres/sparse_matrix.h b/internal/ceres/sparse_matrix.h
index 1b19f88..f3b9671 100644
--- a/internal/ceres/sparse_matrix.h
+++ b/internal/ceres/sparse_matrix.h
@@ -41,8 +41,6 @@
namespace ceres {
namespace internal {
-class SparseMatrixProto;
-
// This class defines the interface for storing and manipulating
// sparse matrices. The key property that differentiates different
// sparse matrices is how they are organized in memory and how the
@@ -86,11 +84,6 @@
// sparse matrix.
virtual void ToDenseMatrix(Matrix* dense_matrix) const = 0;
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- // Dump the sparse matrix to a proto. Destroys the contents of proto.
- virtual void ToProto(SparseMatrixProto* proto) const = 0;
-#endif
-
// Write out the matrix as a sequence of (i,j,s) triplets. This
// format is useful for loading the matrix into MATLAB/octave as a
// sparse matrix.
diff --git a/internal/ceres/triplet_sparse_matrix.cc b/internal/ceres/triplet_sparse_matrix.cc
index a09f38e..824b123 100644
--- a/internal/ceres/triplet_sparse_matrix.cc
+++ b/internal/ceres/triplet_sparse_matrix.cc
@@ -35,7 +35,6 @@
#include "ceres/internal/eigen.h"
#include "ceres/internal/port.h"
#include "ceres/internal/scoped_ptr.h"
-#include "ceres/matrix_proto.h"
#include "ceres/types.h"
#include "glog/logging.h"
@@ -83,32 +82,6 @@
CopyData(orig);
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-TripletSparseMatrix::TripletSparseMatrix(const SparseMatrixProto& outer_proto) {
- CHECK(outer_proto.has_triplet_matrix());
-
- const TripletSparseMatrixProto& proto = outer_proto.triplet_matrix();
- CHECK(proto.has_num_rows());
- CHECK(proto.has_num_cols());
- CHECK_EQ(proto.rows_size(), proto.cols_size());
- CHECK_EQ(proto.cols_size(), proto.values_size());
-
- // Initialize the matrix with the appropriate size and capacity.
- max_num_nonzeros_ = 0;
- set_num_nonzeros(0);
- Reserve(proto.num_nonzeros());
- Resize(proto.num_rows(), proto.num_cols());
- set_num_nonzeros(proto.num_nonzeros());
-
- // Copy the entries in.
- for (int i = 0; i < proto.num_nonzeros(); ++i) {
- rows_[i] = proto.rows(i);
- cols_[i] = proto.cols(i);
- values_[i] = proto.values(i);
- }
-}
-#endif
-
TripletSparseMatrix& TripletSparseMatrix::operator=(
const TripletSparseMatrix& rhs) {
num_rows_ = rhs.num_rows_;
@@ -215,22 +188,6 @@
}
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-void TripletSparseMatrix::ToProto(SparseMatrixProto *proto) const {
- proto->Clear();
-
- TripletSparseMatrixProto* tsm_proto = proto->mutable_triplet_matrix();
- tsm_proto->set_num_rows(num_rows_);
- tsm_proto->set_num_cols(num_cols_);
- tsm_proto->set_num_nonzeros(num_nonzeros_);
- for (int i = 0; i < num_nonzeros_; ++i) {
- tsm_proto->add_rows(rows_[i]);
- tsm_proto->add_cols(cols_[i]);
- tsm_proto->add_values(values_[i]);
- }
-}
-#endif
-
void TripletSparseMatrix::AppendRows(const TripletSparseMatrix& B) {
CHECK_EQ(B.num_cols(), num_cols_);
Reserve(num_nonzeros_ + B.num_nonzeros_);
diff --git a/internal/ceres/triplet_sparse_matrix.h b/internal/ceres/triplet_sparse_matrix.h
index 89a645b..4d7cde7 100644
--- a/internal/ceres/triplet_sparse_matrix.h
+++ b/internal/ceres/triplet_sparse_matrix.h
@@ -39,8 +39,6 @@
namespace ceres {
namespace internal {
-class SparseMatrixProto;
-
// An implementation of the SparseMatrix interface to store and
// manipulate sparse matrices in triplet (i,j,s) form. This object is
// inspired by the design of the cholmod_triplet struct used in the
@@ -50,9 +48,6 @@
TripletSparseMatrix();
TripletSparseMatrix(int num_rows, int num_cols, int max_num_nonzeros);
explicit TripletSparseMatrix(const TripletSparseMatrix& orig);
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- explicit TripletSparseMatrix(const SparseMatrixProto& proto);
-#endif
TripletSparseMatrix& operator=(const TripletSparseMatrix& rhs);
@@ -65,9 +60,6 @@
virtual void SquaredColumnNorm(double* x) const;
virtual void ScaleColumns(const double* scale);
virtual void ToDenseMatrix(Matrix* dense_matrix) const;
-#ifndef CERES_NO_PROTOCOL_BUFFERS
- virtual void ToProto(SparseMatrixProto *proto) const;
-#endif
virtual void ToTextFile(FILE* file) const;
virtual int num_rows() const { return num_rows_; }
virtual int num_cols() const { return num_cols_; }
diff --git a/internal/ceres/triplet_sparse_matrix_test.cc b/internal/ceres/triplet_sparse_matrix_test.cc
index d16682e..b93d72e 100644
--- a/internal/ceres/triplet_sparse_matrix_test.cc
+++ b/internal/ceres/triplet_sparse_matrix_test.cc
@@ -31,7 +31,6 @@
#include "ceres/triplet_sparse_matrix.h"
#include "gtest/gtest.h"
-#include "ceres/matrix_proto.h"
#include "ceres/internal/scoped_ptr.h"
namespace ceres {
@@ -316,39 +315,5 @@
}
}
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-TEST(TripletSparseMatrix, Serialization) {
- TripletSparseMatrix m(2, 5, 4);
-
- m.mutable_rows()[0] = 0;
- m.mutable_cols()[0] = 1;
- m.mutable_values()[0] = 2.5;
-
- m.mutable_rows()[1] = 1;
- m.mutable_cols()[1] = 4;
- m.mutable_values()[1] = 5.2;
- m.set_num_nonzeros(2);
-
- // Roundtrip through serialization and check for equality.
- SparseMatrixProto proto;
- m.ToProto(&proto);
-
- TripletSparseMatrix n(proto);
-
- ASSERT_EQ(n.num_rows(), 2);
- ASSERT_EQ(n.num_cols(), 5);
-
- // Note that max_num_nonzeros gets truncated; the serialization
- ASSERT_EQ(n.num_nonzeros(), 2);
- ASSERT_EQ(n.max_num_nonzeros(), 2);
-
- for (int i = 0; i < m.num_nonzeros(); ++i) {
- EXPECT_EQ(m.rows()[i], n.rows()[i]);
- EXPECT_EQ(m.cols()[i], n.cols()[i]);
- EXPECT_EQ(m.values()[i], n.values()[i]);
- }
-}
-#endif
-
} // namespace internal
} // namespace ceres
diff --git a/internal/ceres/visibility_based_preconditioner_test.cc b/internal/ceres/visibility_based_preconditioner_test.cc
index 999024a..82aaac6 100644
--- a/internal/ceres/visibility_based_preconditioner_test.cc
+++ b/internal/ceres/visibility_based_preconditioner_test.cc
@@ -52,292 +52,293 @@
namespace ceres {
namespace internal {
-using testing::AssertionResult;
-using testing::AssertionSuccess;
-using testing::AssertionFailure;
+// TODO(sameeragarwal): Re-enable this test once serialization is
+// working again.
-static const double kTolerance = 1e-12;
+// using testing::AssertionResult;
+// using testing::AssertionSuccess;
+// using testing::AssertionFailure;
-class VisibilityBasedPreconditionerTest : public ::testing::Test {
- public:
- static const int kCameraSize = 9;
+// static const double kTolerance = 1e-12;
- protected:
- void SetUp() {
- string input_file = TestFileAbsolutePath("problem-6-1384-000.lsqp");
+// class VisibilityBasedPreconditionerTest : public ::testing::Test {
+// public:
+// static const int kCameraSize = 9;
- scoped_ptr<LinearLeastSquaresProblem> problem(
- CHECK_NOTNULL(CreateLinearLeastSquaresProblemFromFile(input_file)));
- A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
- b_.reset(problem->b.release());
- D_.reset(problem->D.release());
+// protected:
+// void SetUp() {
+// string input_file = TestFileAbsolutePath("problem-6-1384-000.lsqp");
- const CompressedRowBlockStructure* bs =
- CHECK_NOTNULL(A_->block_structure());
- const int num_col_blocks = bs->cols.size();
+// scoped_ptr<LinearLeastSquaresProblem> problem(
+// CHECK_NOTNULL(CreateLinearLeastSquaresProblemFromFile(input_file)));
+// A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
+// b_.reset(problem->b.release());
+// D_.reset(problem->D.release());
- num_cols_ = A_->num_cols();
- num_rows_ = A_->num_rows();
- num_eliminate_blocks_ = problem->num_eliminate_blocks;
- num_camera_blocks_ = num_col_blocks - num_eliminate_blocks_;
- options_.elimination_groups.push_back(num_eliminate_blocks_);
- options_.elimination_groups.push_back(
- A_->block_structure()->cols.size() - num_eliminate_blocks_);
+// const CompressedRowBlockStructure* bs =
+// CHECK_NOTNULL(A_->block_structure());
+// const int num_col_blocks = bs->cols.size();
- vector<int> blocks(num_col_blocks - num_eliminate_blocks_, 0);
- for (int i = num_eliminate_blocks_; i < num_col_blocks; ++i) {
- blocks[i - num_eliminate_blocks_] = bs->cols[i].size;
- }
+// num_cols_ = A_->num_cols();
+// num_rows_ = A_->num_rows();
+// num_eliminate_blocks_ = problem->num_eliminate_blocks;
+// num_camera_blocks_ = num_col_blocks - num_eliminate_blocks_;
+// options_.elimination_groups.push_back(num_eliminate_blocks_);
+// options_.elimination_groups.push_back(
+// A_->block_structure()->cols.size() - num_eliminate_blocks_);
- // The input matrix is a real jacobian and fairly poorly
- // conditioned. Setting D to a large constant makes the normal
- // equations better conditioned and makes the tests below better
- // conditioned.
- VectorRef(D_.get(), num_cols_).setConstant(10.0);
+// vector<int> blocks(num_col_blocks - num_eliminate_blocks_, 0);
+// for (int i = num_eliminate_blocks_; i < num_col_blocks; ++i) {
+// blocks[i - num_eliminate_blocks_] = bs->cols[i].size;
+// }
- schur_complement_.reset(new BlockRandomAccessDenseMatrix(blocks));
- Vector rhs(schur_complement_->num_rows());
+// // The input matrix is a real jacobian and fairly poorly
+// // conditioned. Setting D to a large constant makes the normal
+// // equations better conditioned and makes the tests below better
+// // conditioned.
+// VectorRef(D_.get(), num_cols_).setConstant(10.0);
- scoped_ptr<SchurEliminatorBase> eliminator;
- LinearSolver::Options eliminator_options;
- eliminator_options.elimination_groups = options_.elimination_groups;
- eliminator_options.num_threads = options_.num_threads;
+// schur_complement_.reset(new BlockRandomAccessDenseMatrix(blocks));
+// Vector rhs(schur_complement_->num_rows());
- eliminator.reset(SchurEliminatorBase::Create(eliminator_options));
- eliminator->Init(num_eliminate_blocks_, bs);
- eliminator->Eliminate(A_.get(), b_.get(), D_.get(),
- schur_complement_.get(), rhs.data());
- }
+// scoped_ptr<SchurEliminatorBase> eliminator;
+// LinearSolver::Options eliminator_options;
+// eliminator_options.elimination_groups = options_.elimination_groups;
+// eliminator_options.num_threads = options_.num_threads;
+
+// eliminator.reset(SchurEliminatorBase::Create(eliminator_options));
+// eliminator->Init(num_eliminate_blocks_, bs);
+// eliminator->Eliminate(A_.get(), b_.get(), D_.get(),
+// schur_complement_.get(), rhs.data());
+// }
- AssertionResult IsSparsityStructureValid() {
- preconditioner_->InitStorage(*A_->block_structure());
- const HashSet<pair<int, int> >& cluster_pairs = get_cluster_pairs();
- const vector<int>& cluster_membership = get_cluster_membership();
+// AssertionResult IsSparsityStructureValid() {
+// preconditioner_->InitStorage(*A_->block_structure());
+// const HashSet<pair<int, int> >& cluster_pairs = get_cluster_pairs();
+// const vector<int>& cluster_membership = get_cluster_membership();
- for (int i = 0; i < num_camera_blocks_; ++i) {
- for (int j = i; j < num_camera_blocks_; ++j) {
- if (cluster_pairs.count(make_pair(cluster_membership[i],
- cluster_membership[j]))) {
- if (!IsBlockPairInPreconditioner(i, j)) {
- return AssertionFailure()
- << "block pair (" << i << "," << j << "missing";
- }
- } else {
- if (IsBlockPairInPreconditioner(i, j)) {
- return AssertionFailure()
- << "block pair (" << i << "," << j << "should not be present";
- }
- }
- }
- }
- return AssertionSuccess();
- }
+// for (int i = 0; i < num_camera_blocks_; ++i) {
+// for (int j = i; j < num_camera_blocks_; ++j) {
+// if (cluster_pairs.count(make_pair(cluster_membership[i],
+// cluster_membership[j]))) {
+// if (!IsBlockPairInPreconditioner(i, j)) {
+// return AssertionFailure()
+// << "block pair (" << i << "," << j << "missing";
+// }
+// } else {
+// if (IsBlockPairInPreconditioner(i, j)) {
+// return AssertionFailure()
+// << "block pair (" << i << "," << j << "should not be present";
+// }
+// }
+// }
+// }
+// return AssertionSuccess();
+// }
- AssertionResult PreconditionerValuesMatch() {
- preconditioner_->Update(*A_, D_.get());
- const HashSet<pair<int, int> >& cluster_pairs = get_cluster_pairs();
- const BlockRandomAccessSparseMatrix* m = get_m();
- Matrix preconditioner_matrix;
- m->matrix()->ToDenseMatrix(&preconditioner_matrix);
- ConstMatrixRef full_schur_complement(schur_complement_->values(),
- m->num_rows(),
- m->num_rows());
- const int num_clusters = get_num_clusters();
- const int kDiagonalBlockSize =
- kCameraSize * num_camera_blocks_ / num_clusters;
+// AssertionResult PreconditionerValuesMatch() {
+// preconditioner_->Update(*A_, D_.get());
+// const HashSet<pair<int, int> >& cluster_pairs = get_cluster_pairs();
+// const BlockRandomAccessSparseMatrix* m = get_m();
+// Matrix preconditioner_matrix;
+// m->matrix()->ToDenseMatrix(&preconditioner_matrix);
+// ConstMatrixRef full_schur_complement(schur_complement_->values(),
+// m->num_rows(),
+// m->num_rows());
+// const int num_clusters = get_num_clusters();
+// const int kDiagonalBlockSize =
+// kCameraSize * num_camera_blocks_ / num_clusters;
- for (int i = 0; i < num_clusters; ++i) {
- for (int j = i; j < num_clusters; ++j) {
- double diff = 0.0;
- if (cluster_pairs.count(make_pair(i, j))) {
- diff =
- (preconditioner_matrix.block(kDiagonalBlockSize * i,
- kDiagonalBlockSize * j,
- kDiagonalBlockSize,
- kDiagonalBlockSize) -
- full_schur_complement.block(kDiagonalBlockSize * i,
- kDiagonalBlockSize * j,
- kDiagonalBlockSize,
- kDiagonalBlockSize)).norm();
- } else {
- diff = preconditioner_matrix.block(kDiagonalBlockSize * i,
- kDiagonalBlockSize * j,
- kDiagonalBlockSize,
- kDiagonalBlockSize).norm();
- }
- if (diff > kTolerance) {
- return AssertionFailure()
- << "Preconditioner block " << i << " " << j << " differs "
- << "from expected value by " << diff;
- }
- }
- }
- return AssertionSuccess();
- }
+// for (int i = 0; i < num_clusters; ++i) {
+// for (int j = i; j < num_clusters; ++j) {
+// double diff = 0.0;
+// if (cluster_pairs.count(make_pair(i, j))) {
+// diff =
+// (preconditioner_matrix.block(kDiagonalBlockSize * i,
+// kDiagonalBlockSize * j,
+// kDiagonalBlockSize,
+// kDiagonalBlockSize) -
+// full_schur_complement.block(kDiagonalBlockSize * i,
+// kDiagonalBlockSize * j,
+// kDiagonalBlockSize,
+// kDiagonalBlockSize)).norm();
+// } else {
+// diff = preconditioner_matrix.block(kDiagonalBlockSize * i,
+// kDiagonalBlockSize * j,
+// kDiagonalBlockSize,
+// kDiagonalBlockSize).norm();
+// }
+// if (diff > kTolerance) {
+// return AssertionFailure()
+// << "Preconditioner block " << i << " " << j << " differs "
+// << "from expected value by " << diff;
+// }
+// }
+// }
+// return AssertionSuccess();
+// }
- // Accessors
- int get_num_blocks() { return preconditioner_->num_blocks_; }
+// // Accessors
+// int get_num_blocks() { return preconditioner_->num_blocks_; }
- int get_num_clusters() { return preconditioner_->num_clusters_; }
- int* get_mutable_num_clusters() { return &preconditioner_->num_clusters_; }
+// int get_num_clusters() { return preconditioner_->num_clusters_; }
+// int* get_mutable_num_clusters() { return &preconditioner_->num_clusters_; }
- const vector<int>& get_block_size() {
- return preconditioner_->block_size_; }
+// const vector<int>& get_block_size() {
+// return preconditioner_->block_size_; }
- vector<int>* get_mutable_block_size() {
- return &preconditioner_->block_size_; }
+// vector<int>* get_mutable_block_size() {
+// return &preconditioner_->block_size_; }
- const vector<int>& get_cluster_membership() {
- return preconditioner_->cluster_membership_;
- }
+// const vector<int>& get_cluster_membership() {
+// return preconditioner_->cluster_membership_;
+// }
- vector<int>* get_mutable_cluster_membership() {
- return &preconditioner_->cluster_membership_;
- }
+// vector<int>* get_mutable_cluster_membership() {
+// return &preconditioner_->cluster_membership_;
+// }
- const set<pair<int, int> >& get_block_pairs() {
- return preconditioner_->block_pairs_;
- }
+// const set<pair<int, int> >& get_block_pairs() {
+// return preconditioner_->block_pairs_;
+// }
- set<pair<int, int> >* get_mutable_block_pairs() {
- return &preconditioner_->block_pairs_;
- }
+// set<pair<int, int> >* get_mutable_block_pairs() {
+// return &preconditioner_->block_pairs_;
+// }
- const HashSet<pair<int, int> >& get_cluster_pairs() {
- return preconditioner_->cluster_pairs_;
- }
+// const HashSet<pair<int, int> >& get_cluster_pairs() {
+// return preconditioner_->cluster_pairs_;
+// }
- HashSet<pair<int, int> >* get_mutable_cluster_pairs() {
- return &preconditioner_->cluster_pairs_;
- }
+// HashSet<pair<int, int> >* get_mutable_cluster_pairs() {
+// return &preconditioner_->cluster_pairs_;
+// }
- bool IsBlockPairInPreconditioner(const int block1, const int block2) {
- return preconditioner_->IsBlockPairInPreconditioner(block1, block2);
- }
+// bool IsBlockPairInPreconditioner(const int block1, const int block2) {
+// return preconditioner_->IsBlockPairInPreconditioner(block1, block2);
+// }
- bool IsBlockPairOffDiagonal(const int block1, const int block2) {
- return preconditioner_->IsBlockPairOffDiagonal(block1, block2);
- }
+// bool IsBlockPairOffDiagonal(const int block1, const int block2) {
+// return preconditioner_->IsBlockPairOffDiagonal(block1, block2);
+// }
- const BlockRandomAccessSparseMatrix* get_m() {
- return preconditioner_->m_.get();
- }
+// const BlockRandomAccessSparseMatrix* get_m() {
+// return preconditioner_->m_.get();
+// }
- int num_rows_;
- int num_cols_;
- int num_eliminate_blocks_;
- int num_camera_blocks_;
+// int num_rows_;
+// int num_cols_;
+// int num_eliminate_blocks_;
+// int num_camera_blocks_;
- scoped_ptr<BlockSparseMatrix> A_;
- scoped_array<double> b_;
- scoped_array<double> D_;
+// scoped_ptr<BlockSparseMatrix> A_;
+// scoped_array<double> b_;
+// scoped_array<double> D_;
- Preconditioner::Options options_;
- scoped_ptr<VisibilityBasedPreconditioner> preconditioner_;
- scoped_ptr<BlockRandomAccessDenseMatrix> schur_complement_;
-};
+// Preconditioner::Options options_;
+// scoped_ptr<VisibilityBasedPreconditioner> preconditioner_;
+// scoped_ptr<BlockRandomAccessDenseMatrix> schur_complement_;
+// };
-#ifndef CERES_NO_PROTOCOL_BUFFERS
-TEST_F(VisibilityBasedPreconditionerTest, OneClusterClusterJacobi) {
- options_.type = CLUSTER_JACOBI;
- preconditioner_.reset(
- new VisibilityBasedPreconditioner(*A_->block_structure(), options_));
+// TEST_F(VisibilityBasedPreconditionerTest, OneClusterClusterJacobi) {
+// options_.type = CLUSTER_JACOBI;
+// preconditioner_.reset(
+// new VisibilityBasedPreconditioner(*A_->block_structure(), options_));
- // Override the clustering to be a single clustering containing all
- // the cameras.
- vector<int>& cluster_membership = *get_mutable_cluster_membership();
- for (int i = 0; i < num_camera_blocks_; ++i) {
- cluster_membership[i] = 0;
- }
+// // Override the clustering to be a single clustering containing all
+// // the cameras.
+// vector<int>& cluster_membership = *get_mutable_cluster_membership();
+// for (int i = 0; i < num_camera_blocks_; ++i) {
+// cluster_membership[i] = 0;
+// }
- *get_mutable_num_clusters() = 1;
+// *get_mutable_num_clusters() = 1;
- HashSet<pair<int, int> >& cluster_pairs = *get_mutable_cluster_pairs();
- cluster_pairs.clear();
- cluster_pairs.insert(make_pair(0, 0));
+// HashSet<pair<int, int> >& cluster_pairs = *get_mutable_cluster_pairs();
+// cluster_pairs.clear();
+// cluster_pairs.insert(make_pair(0, 0));
- EXPECT_TRUE(IsSparsityStructureValid());
- EXPECT_TRUE(PreconditionerValuesMatch());
+// EXPECT_TRUE(IsSparsityStructureValid());
+// EXPECT_TRUE(PreconditionerValuesMatch());
- // Multiplication by the inverse of the preconditioner.
- const int num_rows = schur_complement_->num_rows();
- ConstMatrixRef full_schur_complement(schur_complement_->values(),
- num_rows,
- num_rows);
- Vector x(num_rows);
- Vector y(num_rows);
- Vector z(num_rows);
+// // Multiplication by the inverse of the preconditioner.
+// const int num_rows = schur_complement_->num_rows();
+// ConstMatrixRef full_schur_complement(schur_complement_->values(),
+// num_rows,
+// num_rows);
+// Vector x(num_rows);
+// Vector y(num_rows);
+// Vector z(num_rows);
- for (int i = 0; i < num_rows; ++i) {
- x.setZero();
- y.setZero();
- z.setZero();
- x[i] = 1.0;
- preconditioner_->RightMultiply(x.data(), y.data());
- z = full_schur_complement
- .selfadjointView<Eigen::Upper>()
- .ldlt().solve(x);
- double max_relative_difference =
- ((y - z).array() / z.array()).matrix().lpNorm<Eigen::Infinity>();
- EXPECT_NEAR(max_relative_difference, 0.0, kTolerance);
- }
-}
+// for (int i = 0; i < num_rows; ++i) {
+// x.setZero();
+// y.setZero();
+// z.setZero();
+// x[i] = 1.0;
+// preconditioner_->RightMultiply(x.data(), y.data());
+// z = full_schur_complement
+// .selfadjointView<Eigen::Upper>()
+// .ldlt().solve(x);
+// double max_relative_difference =
+// ((y - z).array() / z.array()).matrix().lpNorm<Eigen::Infinity>();
+// EXPECT_NEAR(max_relative_difference, 0.0, kTolerance);
+// }
+// }
-TEST_F(VisibilityBasedPreconditionerTest, ClusterJacobi) {
- options_.type = CLUSTER_JACOBI;
- preconditioner_.reset(
- new VisibilityBasedPreconditioner(*A_->block_structure(), options_));
+// TEST_F(VisibilityBasedPreconditionerTest, ClusterJacobi) {
+// options_.type = CLUSTER_JACOBI;
+// preconditioner_.reset(
+// new VisibilityBasedPreconditioner(*A_->block_structure(), options_));
- // Override the clustering to be equal number of cameras.
- vector<int>& cluster_membership = *get_mutable_cluster_membership();
- cluster_membership.resize(num_camera_blocks_);
- static const int kNumClusters = 3;
+// // Override the clustering to be equal number of cameras.
+// vector<int>& cluster_membership = *get_mutable_cluster_membership();
+// cluster_membership.resize(num_camera_blocks_);
+// static const int kNumClusters = 3;
- for (int i = 0; i < num_camera_blocks_; ++i) {
- cluster_membership[i] = (i * kNumClusters) / num_camera_blocks_;
- }
- *get_mutable_num_clusters() = kNumClusters;
+// for (int i = 0; i < num_camera_blocks_; ++i) {
+// cluster_membership[i] = (i * kNumClusters) / num_camera_blocks_;
+// }
+// *get_mutable_num_clusters() = kNumClusters;
- HashSet<pair<int, int> >& cluster_pairs = *get_mutable_cluster_pairs();
- cluster_pairs.clear();
- for (int i = 0; i < kNumClusters; ++i) {
- cluster_pairs.insert(make_pair(i, i));
- }
+// HashSet<pair<int, int> >& cluster_pairs = *get_mutable_cluster_pairs();
+// cluster_pairs.clear();
+// for (int i = 0; i < kNumClusters; ++i) {
+// cluster_pairs.insert(make_pair(i, i));
+// }
- EXPECT_TRUE(IsSparsityStructureValid());
- EXPECT_TRUE(PreconditionerValuesMatch());
-}
+// EXPECT_TRUE(IsSparsityStructureValid());
+// EXPECT_TRUE(PreconditionerValuesMatch());
+// }
-TEST_F(VisibilityBasedPreconditionerTest, ClusterTridiagonal) {
- options_.type = CLUSTER_TRIDIAGONAL;
- preconditioner_.reset(
- new VisibilityBasedPreconditioner(*A_->block_structure(), options_));
- static const int kNumClusters = 3;
+// TEST_F(VisibilityBasedPreconditionerTest, ClusterTridiagonal) {
+// options_.type = CLUSTER_TRIDIAGONAL;
+// preconditioner_.reset(
+// new VisibilityBasedPreconditioner(*A_->block_structure(), options_));
+// static const int kNumClusters = 3;
- // Override the clustering to be 3 clusters.
- vector<int>& cluster_membership = *get_mutable_cluster_membership();
- cluster_membership.resize(num_camera_blocks_);
- for (int i = 0; i < num_camera_blocks_; ++i) {
- cluster_membership[i] = (i * kNumClusters) / num_camera_blocks_;
- }
- *get_mutable_num_clusters() = kNumClusters;
+// // Override the clustering to be 3 clusters.
+// vector<int>& cluster_membership = *get_mutable_cluster_membership();
+// cluster_membership.resize(num_camera_blocks_);
+// for (int i = 0; i < num_camera_blocks_; ++i) {
+// cluster_membership[i] = (i * kNumClusters) / num_camera_blocks_;
+// }
+// *get_mutable_num_clusters() = kNumClusters;
- // Spanning forest has structure 0-1 2
- HashSet<pair<int, int> >& cluster_pairs = *get_mutable_cluster_pairs();
- cluster_pairs.clear();
- for (int i = 0; i < kNumClusters; ++i) {
- cluster_pairs.insert(make_pair(i, i));
- }
- cluster_pairs.insert(make_pair(0, 1));
+// // Spanning forest has structure 0-1 2
+// HashSet<pair<int, int> >& cluster_pairs = *get_mutable_cluster_pairs();
+// cluster_pairs.clear();
+// for (int i = 0; i < kNumClusters; ++i) {
+// cluster_pairs.insert(make_pair(i, i));
+// }
+// cluster_pairs.insert(make_pair(0, 1));
- EXPECT_TRUE(IsSparsityStructureValid());
- EXPECT_TRUE(PreconditionerValuesMatch());
-}
-#endif // CERES_NO_PROTOCOL_BUFFERS
+// EXPECT_TRUE(IsSparsityStructureValid());
+// EXPECT_TRUE(PreconditionerValuesMatch());
+// }
} // namespace internal
} // namespace ceres
diff --git a/jni/Android.mk b/jni/Android.mk
index a2caf7c..b881d88 100644
--- a/jni/Android.mk
+++ b/jni/Android.mk
@@ -99,7 +99,6 @@
LOCAL_CPP_EXTENSION := .cc
LOCAL_CFLAGS := $(CERES_EXTRA_DEFINES) \
- -DCERES_NO_PROTOCOL_BUFFERS \
-DCERES_NO_SUITESPARSE \
-DCERES_NO_GFLAGS \
-DCERES_NO_THREADS \
