ceres-solver / ceres-solver / e4577dd6d99207493c13579da0bfd7da58904d8e / . / internal / ceres / trust_region_step_evaluator.cc

// Ceres Solver - A fast non-linear least squares minimizer | |

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// Author: sameeragarwal@google.com (Sameer Agarwal) | |

#include <algorithm> | |

#include <limits> | |

#include "ceres/trust_region_step_evaluator.h" | |

#include "glog/logging.h" | |

namespace ceres { | |

namespace internal { | |

TrustRegionStepEvaluator::TrustRegionStepEvaluator( | |

const double initial_cost, | |

const int max_consecutive_nonmonotonic_steps) | |

: max_consecutive_nonmonotonic_steps_(max_consecutive_nonmonotonic_steps), | |

minimum_cost_(initial_cost), | |

current_cost_(initial_cost), | |

reference_cost_(initial_cost), | |

candidate_cost_(initial_cost), | |

accumulated_reference_model_cost_change_(0.0), | |

accumulated_candidate_model_cost_change_(0.0), | |

num_consecutive_nonmonotonic_steps_(0){ | |

} | |

double TrustRegionStepEvaluator::StepQuality( | |

const double cost, | |

const double model_cost_change) const { | |

// If the function evaluation for this step was a failure, in which | |

// case the TrustRegionMinimizer would have set the cost to | |

// std::numeric_limits<double>::max(). In this case, the division by | |

// model_cost_change can result in an overflow. To prevent that from | |

// happening, we will deal with this case explicitly. | |

if (cost >= std::numeric_limits<double>::max()) { | |

return std::numeric_limits<double>::lowest(); | |

} | |

const double relative_decrease = (current_cost_ - cost) / model_cost_change; | |

const double historical_relative_decrease = | |

(reference_cost_ - cost) / | |

(accumulated_reference_model_cost_change_ + model_cost_change); | |

return std::max(relative_decrease, historical_relative_decrease); | |

} | |

void TrustRegionStepEvaluator::StepAccepted( | |

const double cost, | |

const double model_cost_change) { | |

// Algorithm 10.1.2 from Trust Region Methods by Conn, Gould & | |

// Toint. | |

// | |

// Step 3a | |

current_cost_ = cost; | |

accumulated_candidate_model_cost_change_ += model_cost_change; | |

accumulated_reference_model_cost_change_ += model_cost_change; | |

// Step 3b. | |

if (current_cost_ < minimum_cost_) { | |

minimum_cost_ = current_cost_; | |

num_consecutive_nonmonotonic_steps_ = 0; | |

candidate_cost_ = current_cost_; | |

accumulated_candidate_model_cost_change_ = 0.0; | |

} else { | |

// Step 3c. | |

++num_consecutive_nonmonotonic_steps_; | |

if (current_cost_ > candidate_cost_) { | |

candidate_cost_ = current_cost_; | |

accumulated_candidate_model_cost_change_ = 0.0; | |

} | |

} | |

// Step 3d. | |

// | |

// At this point we have made too many non-monotonic steps and | |

// we are going to reset the value of the reference iterate so | |

// as to force the algorithm to descend. | |

// | |

// Note: In the original algorithm by Toint, this step was only | |

// executed if the step was non-monotonic, but that would not handle | |

// the case of max_consecutive_nonmonotonic_steps = 0. The small | |

// modification of doing this always handles that corner case | |

// correctly. | |

if (num_consecutive_nonmonotonic_steps_ == | |

max_consecutive_nonmonotonic_steps_) { | |

reference_cost_ = candidate_cost_; | |

accumulated_reference_model_cost_change_ = | |

accumulated_candidate_model_cost_change_; | |

} | |

} | |

} // namespace internal | |

} // namespace ceres |