| # Ceres Solver - A fast non-linear least squares minimizer |
| # Copyright 2018 Google Inc. All rights reserved. |
| # http://ceres-solver.org/ |
| # |
| # 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) |
| # |
| # Generate bundle adjustment tests as separate binaries. Since the bundle |
| # adjustment tests are fairly processing intensive, serializing them makes the |
| # tests take forever to run. Splitting them into separate binaries makes it |
| # easier to parallelize in continuous integration systems, and makes local |
| # processing on multi-core workstations much faster. |
| |
| # Product of ORDERINGS, THREAD_CONFIGS, and SOLVER_CONFIGS is the full set of |
| # tests to generate. |
| ORDERINGS = ["kAutomaticOrdering", "kUserOrdering"] |
| SINGLE_THREADED = "1" |
| MULTI_THREADED = "4" |
| THREAD_CONFIGS = [SINGLE_THREADED, MULTI_THREADED] |
| |
| SOLVER_CONFIGS = [ |
| # Linear solver Sparse backend Preconditioner |
| ('DENSE_SCHUR', 'NO_SPARSE', 'IDENTITY'), |
| ('ITERATIVE_SCHUR', 'NO_SPARSE', 'JACOBI'), |
| ('ITERATIVE_SCHUR', 'NO_SPARSE', 'SCHUR_JACOBI'), |
| ('ITERATIVE_SCHUR', 'SUITE_SPARSE', 'CLUSTER_JACOBI'), |
| ('ITERATIVE_SCHUR', 'EIGEN_SPARSE', 'CLUSTER_JACOBI'), |
| ('ITERATIVE_SCHUR', 'CX_SPARSE', 'CLUSTER_JACOBI'), |
| ('ITERATIVE_SCHUR', 'ACCELERATE_SPARSE','CLUSTER_JACOBI'), |
| ('ITERATIVE_SCHUR', 'SUITE_SPARSE', 'CLUSTER_TRIDIAGONAL'), |
| ('ITERATIVE_SCHUR', 'EIGEN_SPARSE', 'CLUSTER_TRIDIAGONAL'), |
| ('ITERATIVE_SCHUR', 'CX_SPARSE', 'CLUSTER_TRIDIAGONAL'), |
| ('ITERATIVE_SCHUR', 'ACCELERATE_SPARSE','CLUSTER_TRIDIAGONAL'), |
| ('SPARSE_NORMAL_CHOLESKY', 'SUITE_SPARSE', 'IDENTITY'), |
| ('SPARSE_NORMAL_CHOLESKY', 'EIGEN_SPARSE', 'IDENTITY'), |
| ('SPARSE_NORMAL_CHOLESKY', 'CX_SPARSE', 'IDENTITY'), |
| ('SPARSE_NORMAL_CHOLESKY', 'ACCELERATE_SPARSE','IDENTITY'), |
| ('SPARSE_SCHUR', 'SUITE_SPARSE', 'IDENTITY'), |
| ('SPARSE_SCHUR', 'EIGEN_SPARSE', 'IDENTITY'), |
| ('SPARSE_SCHUR', 'CX_SPARSE', 'IDENTITY'), |
| ('SPARSE_SCHUR', 'ACCELERATE_SPARSE','IDENTITY'), |
| ] |
| |
| FILENAME_SHORTENING_MAP = dict( |
| DENSE_SCHUR='denseschur', |
| ITERATIVE_SCHUR='iterschur', |
| SPARSE_NORMAL_CHOLESKY='sparsecholesky', |
| SPARSE_SCHUR='sparseschur', |
| NO_SPARSE='', # Omit sparse reference entirely for dense tests. |
| SUITE_SPARSE='suitesparse', |
| EIGEN_SPARSE='eigensparse', |
| CX_SPARSE='cxsparse', |
| ACCELERATE_SPARSE='acceleratesparse', |
| IDENTITY='identity', |
| JACOBI='jacobi', |
| SCHUR_JACOBI='schurjacobi', |
| CLUSTER_JACOBI='clustjacobi', |
| CLUSTER_TRIDIAGONAL='clusttri', |
| kAutomaticOrdering='auto', |
| kUserOrdering='user', |
| ) |
| |
| COPYRIGHT_HEADER = ( |
| """// Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2018 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
| // 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. |
| // |
| // ======================================== |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| // THIS FILE IS AUTOGENERATED. DO NOT EDIT. |
| // ======================================== |
| // |
| // This file is generated using generate_bundle_adjustment_tests.py.""") |
| |
| BUNDLE_ADJUSTMENT_TEST_TEMPLATE = (COPYRIGHT_HEADER + """ |
| |
| #include "bundle_adjustment_test_util.h" |
| %(preprocessor_conditions_begin)s |
| namespace ceres { |
| namespace internal { |
| |
| TEST_F(BundleAdjustmentTest, |
| %(test_class_name)s) { // NOLINT |
| BundleAdjustmentProblem bundle_adjustment_problem; |
| Solver::Options* options = bundle_adjustment_problem.mutable_solver_options(); |
| options->num_threads = %(num_threads)s; |
| options->linear_solver_type = %(linear_solver)s; |
| options->sparse_linear_algebra_library_type = %(sparse_backend)s; |
| options->preconditioner_type = %(preconditioner)s; |
| if (%(ordering)s) { |
| options->linear_solver_ordering.reset(); |
| } |
| Problem* problem = bundle_adjustment_problem.mutable_problem(); |
| RunSolverForConfigAndExpectResidualsMatch(*options, problem); |
| } |
| |
| } // namespace internal |
| } // namespace ceres |
| %(preprocessor_conditions_end)s""") |
| |
| def camelcasify(token): |
| """Convert capitalized underscore tokens to camel case""" |
| return ''.join([x.lower().capitalize() for x in token.split('_')]) |
| |
| |
| def generate_bundle_test(linear_solver, |
| sparse_backend, |
| preconditioner, |
| ordering, |
| thread_config): |
| """Generate a bundle adjustment test executable configured appropriately""" |
| |
| # Preconditioner only makes sense for iterative schur; drop it otherwise. |
| preconditioner_tag = preconditioner |
| if linear_solver != 'ITERATIVE_SCHUR': |
| preconditioner_tag = '' |
| |
| # Omit references to the sparse backend when one is not in use. |
| sparse_backend_tag = sparse_backend |
| if sparse_backend == 'NO_SPARSE': |
| sparse_backend_tag = '' |
| |
| # Use a double underscore; otherwise the names are harder to understand. |
| test_class_name = '_'.join(filter(lambda x: x, [ |
| camelcasify(linear_solver), |
| camelcasify(sparse_backend_tag), |
| camelcasify(preconditioner_tag), |
| ordering[1:], # Strip 'k' |
| 'Threads' if thread_config == MULTI_THREADED else ''])) |
| |
| # Initial template parameters (augmented more below). |
| template_parameters = dict( |
| linear_solver=linear_solver, |
| sparse_backend=sparse_backend, |
| preconditioner=preconditioner, |
| ordering=ordering, |
| num_threads=thread_config, |
| test_class_name=test_class_name) |
| |
| # Accumulate appropriate #ifdef/#ifndefs for the solver's sparse backend. |
| preprocessor_conditions_begin = [] |
| preprocessor_conditions_end = [] |
| if sparse_backend == 'SUITE_SPARSE': |
| preprocessor_conditions_begin.append('#ifndef CERES_NO_SUITESPARSE') |
| preprocessor_conditions_end.insert(0, '#endif // CERES_NO_SUITESPARSE') |
| elif sparse_backend == 'CX_SPARSE': |
| preprocessor_conditions_begin.append('#ifndef CERES_NO_CXSPARSE') |
| preprocessor_conditions_end.insert(0, '#endif // CERES_NO_CXSPARSE') |
| elif sparse_backend == 'ACCELERATE_SPARSE': |
| preprocessor_conditions_begin.append('#ifndef CERES_NO_ACCELERATE_SPARSE') |
| preprocessor_conditions_end.insert(0, '#endif // CERES_NO_ACCELERATE_SPARSE') |
| elif sparse_backend == 'EIGEN_SPARSE': |
| preprocessor_conditions_begin.append('#ifdef CERES_USE_EIGEN_SPARSE') |
| preprocessor_conditions_end.insert(0, '#endif // CERES_USE_EIGEN_SPARSE') |
| |
| # Accumulate appropriate #ifdef/#ifndefs for threading conditions. |
| if thread_config == MULTI_THREADED: |
| preprocessor_conditions_begin.append('#ifndef CERES_NO_THREADS') |
| preprocessor_conditions_end.insert(0, '#endif // CERES_NO_THREADS') |
| |
| # If there are #ifdefs, put newlines around them. |
| if preprocessor_conditions_begin: |
| preprocessor_conditions_begin.insert(0, '') |
| preprocessor_conditions_begin.append('') |
| preprocessor_conditions_end.insert(0, '') |
| preprocessor_conditions_end.append('') |
| |
| # Put #ifdef/#ifndef stacks into the template parameters. |
| template_parameters['preprocessor_conditions_begin'] = '\n'.join( |
| preprocessor_conditions_begin) |
| template_parameters['preprocessor_conditions_end'] = '\n'.join( |
| preprocessor_conditions_end) |
| |
| # Substitute variables into the test template, and write the result to a file. |
| filename_tag = '_'.join(FILENAME_SHORTENING_MAP.get(x) for x in [ |
| linear_solver, |
| sparse_backend_tag, |
| preconditioner_tag, |
| ordering] |
| if FILENAME_SHORTENING_MAP.get(x)) |
| if (thread_config == MULTI_THREADED): |
| filename_tag += '_threads' |
| |
| filename = ('generated_bundle_adjustment_tests/ba_%s_test.cc' % |
| filename_tag.lower()) |
| with open(filename, 'w') as fd: |
| fd.write(BUNDLE_ADJUSTMENT_TEST_TEMPLATE % template_parameters) |
| |
| # All done. |
| print 'Generated', filename |
| |
| return filename |
| |
| |
| if __name__ == '__main__': |
| # Iterate over all the possible configurations and generate the tests. |
| generated_files = [] |
| for linear_solver, sparse_backend, preconditioner in SOLVER_CONFIGS: |
| for ordering in ORDERINGS: |
| for thread_config in THREAD_CONFIGS: |
| generated_files.append( |
| generate_bundle_test(linear_solver, |
| sparse_backend, |
| preconditioner, |
| ordering, |
| thread_config)) |
| |
| # Generate the CMakeLists.txt as well. |
| with open('generated_bundle_adjustment_tests/CMakeLists.txt', 'w') as fd: |
| fd.write(COPYRIGHT_HEADER.replace('//', '#').replace('http:#', 'http://')) |
| fd.write('\n') |
| fd.write('\n') |
| for generated_file in generated_files: |
| fd.write('ceres_test(%s)\n' % |
| generated_file.split('/')[1].replace('_test.cc', '')) |