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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2016 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: 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
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