| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2023 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. |
| // |
| // Authors: vitus@google.com (Michael Vitus), |
| // dmitriy.korchemkin@gmail.com (Dmitriy Korchemkin) |
| |
| #ifndef CERES_INTERNAL_PARTITION_RANGE_FOR_PARALLEL_FOR_H_ |
| #define CERES_INTERNAL_PARTITION_RANGE_FOR_PARALLEL_FOR_H_ |
| |
| #include <algorithm> |
| #include <vector> |
| |
| namespace ceres::internal { |
| // Check if it is possible to split range [start; end) into at most |
| // max_num_partitions contiguous partitions of cost not greater than |
| // max_partition_cost. Inclusive integer cumulative costs are provided by |
| // cumulative_cost_data objects, with cumulative_cost_offset being a total cost |
| // of all indices (starting from zero) preceding start element. Cumulative costs |
| // are returned by cumulative_cost_fun called with a reference to |
| // cumulative_cost_data element with index from range[start; end), and should be |
| // non-decreasing. Partition of the range is returned via partition argument |
| template <typename CumulativeCostData, typename CumulativeCostFun> |
| bool MaxPartitionCostIsFeasible(int start, |
| int end, |
| int max_num_partitions, |
| int max_partition_cost, |
| int cumulative_cost_offset, |
| const CumulativeCostData* cumulative_cost_data, |
| CumulativeCostFun&& cumulative_cost_fun, |
| std::vector<int>* partition) { |
| partition->clear(); |
| partition->push_back(start); |
| int partition_start = start; |
| int cost_offset = cumulative_cost_offset; |
| |
| while (partition_start < end) { |
| // Already have max_num_partitions |
| if (partition->size() > max_num_partitions) { |
| return false; |
| } |
| const int target = max_partition_cost + cost_offset; |
| const int partition_end = |
| std::partition_point( |
| cumulative_cost_data + partition_start, |
| cumulative_cost_data + end, |
| [&cumulative_cost_fun, target](const CumulativeCostData& item) { |
| return cumulative_cost_fun(item) <= target; |
| }) - |
| cumulative_cost_data; |
| // Unable to make a partition from a single element |
| if (partition_end == partition_start) { |
| return false; |
| } |
| |
| const int cost_last = |
| cumulative_cost_fun(cumulative_cost_data[partition_end - 1]); |
| partition->push_back(partition_end); |
| partition_start = partition_end; |
| cost_offset = cost_last; |
| } |
| return true; |
| } |
| |
| // Split integer interval [start, end) into at most max_num_partitions |
| // contiguous intervals, minimizing maximal total cost of a single interval. |
| // Inclusive integer cumulative costs for each (zero-based) index are provided |
| // by cumulative_cost_data objects, and are returned by cumulative_cost_fun call |
| // with a reference to one of the objects from range [start, end) |
| template <typename CumulativeCostData, typename CumulativeCostFun> |
| std::vector<int> PartitionRangeForParallelFor( |
| int start, |
| int end, |
| int max_num_partitions, |
| const CumulativeCostData* cumulative_cost_data, |
| CumulativeCostFun&& cumulative_cost_fun) { |
| // Given maximal partition cost, it is possible to verify if it is admissible |
| // and obtain corresponding partition using MaxPartitionCostIsFeasible |
| // function. In order to find the lowest admissible value, a binary search |
| // over all potentially optimal cost values is being performed |
| const int cumulative_cost_last = |
| cumulative_cost_fun(cumulative_cost_data[end - 1]); |
| const int cumulative_cost_offset = |
| start ? cumulative_cost_fun(cumulative_cost_data[start - 1]) : 0; |
| const int total_cost = cumulative_cost_last - cumulative_cost_offset; |
| |
| // Minimal maximal partition cost is not smaller than the average |
| // We will use non-inclusive lower bound |
| int partition_cost_lower_bound = total_cost / max_num_partitions - 1; |
| // Minimal maximal partition cost is not larger than the total cost |
| // Upper bound is inclusive |
| int partition_cost_upper_bound = total_cost; |
| |
| std::vector<int> partition; |
| // Range partition corresponding to the latest evaluated upper bound. |
| // A single segment covering the whole input interval [start, end) corresponds |
| // to minimal maximal partition cost of total_cost. |
| std::vector<int> partition_upper_bound = {start, end}; |
| // Binary search over partition cost, returning the lowest admissible cost |
| while (partition_cost_upper_bound - partition_cost_lower_bound > 1) { |
| partition.reserve(max_num_partitions + 1); |
| const int partition_cost = |
| partition_cost_lower_bound + |
| (partition_cost_upper_bound - partition_cost_lower_bound) / 2; |
| bool admissible = MaxPartitionCostIsFeasible( |
| start, |
| end, |
| max_num_partitions, |
| partition_cost, |
| cumulative_cost_offset, |
| cumulative_cost_data, |
| std::forward<CumulativeCostFun>(cumulative_cost_fun), |
| &partition); |
| if (admissible) { |
| partition_cost_upper_bound = partition_cost; |
| std::swap(partition, partition_upper_bound); |
| } else { |
| partition_cost_lower_bound = partition_cost; |
| } |
| } |
| |
| return partition_upper_bound; |
| } |
| } // namespace ceres::internal |
| |
| #endif |