mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 08:34:37 +08:00
Sameer Agarwal
ebb66e655f
Ceres Solver was using an old forked version of FixedArray, now that we are using absl, we can use the official version that ships with it. Change-Id: Ic88d7f6e8a49b928d611f7cbb04172452b322b01
106 lines
4.1 KiB
C++
106 lines
4.1 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2023 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#ifndef CERES_INTERNAL_EIGEN_VECTOR_OPS_H_
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#define CERES_INTERNAL_EIGEN_VECTOR_OPS_H_
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#include <numeric>
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#include "absl/container/fixed_array.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/parallel_for.h"
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#include "ceres/parallel_vector_ops.h"
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namespace ceres::internal {
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// Blas1 operations on Eigen vectors. These functions are needed as an
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// abstraction layer so that we can use different versions of a vector style
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// object in the conjugate gradients linear solver.
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template <typename Derived>
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inline double Norm(const Eigen::DenseBase<Derived>& x,
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ContextImpl* context,
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int num_threads) {
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absl::FixedArray<double> norms(num_threads, 0.);
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ParallelFor(
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context,
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0,
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x.rows(),
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num_threads,
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[&x, &norms](int thread_id, std::tuple<int, int> range) {
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auto [start, end] = range;
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norms[thread_id] += x.segment(start, end - start).squaredNorm();
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},
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kMinBlockSizeParallelVectorOps);
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return std::sqrt(std::accumulate(norms.begin(), norms.end(), 0.));
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}
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inline void SetZero(Vector& x, ContextImpl* context, int num_threads) {
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ParallelSetZero(context, num_threads, x);
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}
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inline void Axpby(double a,
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const Vector& x,
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double b,
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const Vector& y,
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Vector& z,
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ContextImpl* context,
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int num_threads) {
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ParallelAssign(context, num_threads, z, a * x + b * y);
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}
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template <typename VectorLikeX, typename VectorLikeY>
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inline double Dot(const VectorLikeX& x,
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const VectorLikeY& y,
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ContextImpl* context,
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int num_threads) {
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absl::FixedArray<double> dots(num_threads, 0.);
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ParallelFor(
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context,
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0,
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x.rows(),
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num_threads,
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[&x, &y, &dots](int thread_id, std::tuple<int, int> range) {
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auto [start, end] = range;
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const int block_size = end - start;
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const auto& x_block = x.segment(start, block_size);
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const auto& y_block = y.segment(start, block_size);
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dots[thread_id] += x_block.dot(y_block);
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},
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kMinBlockSizeParallelVectorOps);
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return std::accumulate(dots.begin(), dots.end(), 0.);
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}
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inline void Copy(const Vector& from,
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Vector& to,
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ContextImpl* context,
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int num_threads) {
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ParallelAssign(context, num_threads, to, from);
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}
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} // namespace ceres::internal
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#endif // CERES_INTERNAL_EIGEN_VECTOR_OPS_H_
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