internal/ceres/residual_block.cc - ceres-solver - Git at Google

 // 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.
 //
 // Author: keir@google.com (Keir Mierle)
 //         sameeragarwal@google.com (Sameer Agarwal)

 #include "ceres/residual_block.h"

 #include <algorithm>
 #include <cstddef>
 #include <vector>

 #include "absl/log/check.h"
 #include "absl/log/log.h"
 #include "ceres/corrector.h"
 #include "ceres/cost_function.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/fixed_array.h"
 #include "ceres/loss_function.h"
 #include "ceres/manifold.h"
 #include "ceres/parameter_block.h"
 #include "ceres/residual_block_utils.h"
 #include "ceres/small_blas.h"

 using Eigen::Dynamic;

 namespace ceres::internal {

 ResidualBlock::ResidualBlock(
     const CostFunction* cost_function,
     const LossFunction* loss_function,
     const std::vector<ParameterBlock*>& parameter_blocks,
     int index)
     : cost_function_(cost_function),
       loss_function_(loss_function),
       parameter_blocks_(
           new ParameterBlock*[cost_function->parameter_block_sizes().size()]),
       index_(index) {
   CHECK(cost_function_ != nullptr);
   std::copy(parameter_blocks.begin(),
             parameter_blocks.end(),
             parameter_blocks_.get());
 }

 bool ResidualBlock::Evaluate(const bool apply_loss_function,
                              double* cost,
                              double* residuals,
                              double** jacobians,
                              double* scratch) const {
   const int num_parameter_blocks = NumParameterBlocks();
   const int num_residuals = cost_function_->num_residuals();

   // Collect the parameters from their blocks. This will rarely allocate, since
   // residuals taking more than 8 parameter block arguments are rare.
   FixedArray<const double*, 8> parameters(num_parameter_blocks);
   for (int i = 0; i < num_parameter_blocks; ++i) {
     parameters[i] = parameter_blocks_[i]->state();
   }

   // Put pointers into the scratch space into global_jacobians as appropriate.
   FixedArray<double*, 8> global_jacobians(num_parameter_blocks);
   if (jacobians != nullptr) {
     for (int i = 0; i < num_parameter_blocks; ++i) {
       const ParameterBlock* parameter_block = parameter_blocks_[i];
       if (jacobians[i] != nullptr &&
           parameter_block->PlusJacobian() != nullptr) {
         global_jacobians[i] = scratch;
         scratch += num_residuals * parameter_block->Size();
       } else {
         global_jacobians[i] = jacobians[i];
       }
     }
   }

   // If the caller didn't request residuals, use the scratch space for them.
   bool outputting_residuals = (residuals != nullptr);
   if (!outputting_residuals) {
     residuals = scratch;
   }

   // Invalidate the evaluation buffers so that we can check them after
   // the CostFunction::Evaluate call, to see if all the return values
   // that were required were written to and that they are finite.
   double** eval_jacobians =
       (jacobians != nullptr) ? global_jacobians.data() : nullptr;

   InvalidateEvaluation(*this, cost, residuals, eval_jacobians);

   if (!cost_function_->Evaluate(parameters.data(), residuals, eval_jacobians)) {
     return false;
   }

   if (!IsEvaluationValid(*this, parameters.data(), residuals, eval_jacobians)) {
     // clang-format off
     std::string message =
         "\n\n"
         "Error in evaluating the ResidualBlock.\n\n"
         "There are two possible reasons. Either the CostFunction did not evaluate and fill all    \n"  // NOLINT
         "residual and jacobians that were requested or there was a non-finite value (nan/infinite)\n"  // NOLINT
         "generated during the or jacobian computation. \n\n" +
         EvaluationToString(
             *this, parameters.data(), cost, residuals, eval_jacobians);
     // clang-format on
     LOG(WARNING) << message;
     return false;
   }

   double squared_norm = VectorRef(residuals, num_residuals).squaredNorm();

   // Update the plus_jacobian for the manifolds.
   if (jacobians != nullptr) {
     for (int i = 0; i < num_parameter_blocks; ++i) {
       if (jacobians[i] != nullptr) {
         const ParameterBlock* parameter_block = parameter_blocks_[i];

         // Apply the Manifold::PlusJacobian to the ambient jacobians.
         if (parameter_block->PlusJacobian() != nullptr) {
           // jacobians[i] = global_jacobians[i] * global_to_local_jacobian.
           MatrixMatrixMultiply<Dynamic, Dynamic, Dynamic, Dynamic, 0>(
               global_jacobians[i],
               num_residuals,
               parameter_block->Size(),
               parameter_block->PlusJacobian(),
               parameter_block->Size(),
               parameter_block->TangentSize(),
               jacobians[i],
               0,
               0,
               num_residuals,
               parameter_block->TangentSize());
         }
       }
     }
   }

   if (loss_function_ == nullptr || !apply_loss_function) {
     *cost = 0.5 * squared_norm;
     return true;
   }

   double rho[3];
   loss_function_->Evaluate(squared_norm, rho);
   *cost = 0.5 * rho[0];

   // No jacobians and not outputting residuals? All done. Doing an early exit
   // here avoids constructing the "Corrector" object below in a common case.
   if (jacobians == nullptr && !outputting_residuals) {
     return true;
   }

   // Correct for the effects of the loss function. The jacobians need to be
   // corrected before the residuals, since they use the uncorrected residuals.
   Corrector correct(squared_norm, rho);
   if (jacobians != nullptr) {
     for (int i = 0; i < num_parameter_blocks; ++i) {
       if (jacobians[i] != nullptr) {
         const ParameterBlock* parameter_block = parameter_blocks_[i];

         // Correct the jacobians for the loss function.
         correct.CorrectJacobian(num_residuals,
                                 parameter_block->TangentSize(),
                                 residuals,
                                 jacobians[i]);
       }
     }
   }

   // Correct the residuals with the loss function.
   if (outputting_residuals) {
     correct.CorrectResiduals(num_residuals, residuals);
   }
   return true;
 }

 int ResidualBlock::NumScratchDoublesForEvaluate() const {
   // Compute the amount of scratch space needed to store the full-sized
   // jacobians. For parameters that have no manifold no storage is needed and
   // the passed-in jacobian array is used directly. Also include space to store
   // the residuals, which is needed for cost-only evaluations.  This is slightly
   // pessimistic, since both won't be needed all the time, but the amount of
   // excess should not cause problems for the caller.
   int num_parameters = NumParameterBlocks();
   int scratch_doubles = 1;
   for (int i = 0; i < num_parameters; ++i) {
     const ParameterBlock* parameter_block = parameter_blocks_[i];
     if (parameter_block->PlusJacobian() != nullptr) {
       scratch_doubles += parameter_block->Size();
     }
   }
   scratch_doubles *= NumResiduals();
   return scratch_doubles;
 }

 }  // namespace ceres::internal
	// 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.
	//
	// Author: keir@google.com (Keir Mierle)
	// sameeragarwal@google.com (Sameer Agarwal)

	#include "ceres/residual_block.h"

	#include <algorithm>
	#include <cstddef>
	#include <vector>

	#include "absl/log/check.h"
	#include "absl/log/log.h"
	#include "ceres/corrector.h"
	#include "ceres/cost_function.h"
	#include "ceres/internal/eigen.h"
	#include "ceres/internal/fixed_array.h"
	#include "ceres/loss_function.h"
	#include "ceres/manifold.h"
	#include "ceres/parameter_block.h"
	#include "ceres/residual_block_utils.h"
	#include "ceres/small_blas.h"

	using Eigen::Dynamic;

	namespace ceres::internal {

	ResidualBlock::ResidualBlock(
	const CostFunction* cost_function,
	const LossFunction* loss_function,
	const std::vector<ParameterBlock*>& parameter_blocks,
	int index)
	: cost_function_(cost_function),
	loss_function_(loss_function),
	parameter_blocks_(
	new ParameterBlock*[cost_function->parameter_block_sizes().size()]),
	index_(index) {
	CHECK(cost_function_ != nullptr);
	std::copy(parameter_blocks.begin(),
	parameter_blocks.end(),
	parameter_blocks_.get());
	}

	bool ResidualBlock::Evaluate(const bool apply_loss_function,
	double* cost,
	double* residuals,
	double** jacobians,
	double* scratch) const {
	const int num_parameter_blocks = NumParameterBlocks();
	const int num_residuals = cost_function_->num_residuals();

	// Collect the parameters from their blocks. This will rarely allocate, since
	// residuals taking more than 8 parameter block arguments are rare.
	FixedArray<const double*, 8> parameters(num_parameter_blocks);
	for (int i = 0; i < num_parameter_blocks; ++i) {
	parameters[i] = parameter_blocks_[i]->state();
	}

	// Put pointers into the scratch space into global_jacobians as appropriate.
	FixedArray<double*, 8> global_jacobians(num_parameter_blocks);
	if (jacobians != nullptr) {
	for (int i = 0; i < num_parameter_blocks; ++i) {
	const ParameterBlock* parameter_block = parameter_blocks_[i];
	if (jacobians[i] != nullptr &&
	parameter_block->PlusJacobian() != nullptr) {
	global_jacobians[i] = scratch;
	scratch += num_residuals * parameter_block->Size();
	} else {
	global_jacobians[i] = jacobians[i];
	}
	}
	}

	// If the caller didn't request residuals, use the scratch space for them.
	bool outputting_residuals = (residuals != nullptr);
	if (!outputting_residuals) {
	residuals = scratch;
	}

	// Invalidate the evaluation buffers so that we can check them after
	// the CostFunction::Evaluate call, to see if all the return values
	// that were required were written to and that they are finite.
	double** eval_jacobians =
	(jacobians != nullptr) ? global_jacobians.data() : nullptr;

	InvalidateEvaluation(*this, cost, residuals, eval_jacobians);

	if (!cost_function_->Evaluate(parameters.data(), residuals, eval_jacobians)) {
	return false;
	}

	if (!IsEvaluationValid(*this, parameters.data(), residuals, eval_jacobians)) {
	// clang-format off
	std::string message =
	"\n\n"
	"Error in evaluating the ResidualBlock.\n\n"
	"There are two possible reasons. Either the CostFunction did not evaluate and fill all \n" // NOLINT
	"residual and jacobians that were requested or there was a non-finite value (nan/infinite)\n" // NOLINT
	"generated during the or jacobian computation. \n\n" +
	EvaluationToString(
	*this, parameters.data(), cost, residuals, eval_jacobians);
	// clang-format on
	LOG(WARNING) << message;
	return false;
	}

	double squared_norm = VectorRef(residuals, num_residuals).squaredNorm();

	// Update the plus_jacobian for the manifolds.
	if (jacobians != nullptr) {
	for (int i = 0; i < num_parameter_blocks; ++i) {
	if (jacobians[i] != nullptr) {
	const ParameterBlock* parameter_block = parameter_blocks_[i];

	// Apply the Manifold::PlusJacobian to the ambient jacobians.
	if (parameter_block->PlusJacobian() != nullptr) {
	// jacobians[i] = global_jacobians[i] * global_to_local_jacobian.
	MatrixMatrixMultiply<Dynamic, Dynamic, Dynamic, Dynamic, 0>(
	global_jacobians[i],
	num_residuals,
	parameter_block->Size(),
	parameter_block->PlusJacobian(),
	parameter_block->Size(),
	parameter_block->TangentSize(),
	jacobians[i],
	0,
	0,
	num_residuals,
	parameter_block->TangentSize());
	}
	}
	}
	}

	if (loss_function_ == nullptr \|\| !apply_loss_function) {
	cost = 0.5 squared_norm;
	return true;
	}

	double rho[3];
	loss_function_->Evaluate(squared_norm, rho);
	cost = 0.5 rho[0];

	// No jacobians and not outputting residuals? All done. Doing an early exit
	// here avoids constructing the "Corrector" object below in a common case.
	if (jacobians == nullptr && !outputting_residuals) {
	return true;
	}

	// Correct for the effects of the loss function. The jacobians need to be
	// corrected before the residuals, since they use the uncorrected residuals.
	Corrector correct(squared_norm, rho);
	if (jacobians != nullptr) {
	for (int i = 0; i < num_parameter_blocks; ++i) {
	if (jacobians[i] != nullptr) {
	const ParameterBlock* parameter_block = parameter_blocks_[i];

	// Correct the jacobians for the loss function.
	correct.CorrectJacobian(num_residuals,
	parameter_block->TangentSize(),
	residuals,
	jacobians[i]);
	}
	}
	}

	// Correct the residuals with the loss function.
	if (outputting_residuals) {
	correct.CorrectResiduals(num_residuals, residuals);
	}
	return true;
	}

	int ResidualBlock::NumScratchDoublesForEvaluate() const {
	// Compute the amount of scratch space needed to store the full-sized
	// jacobians. For parameters that have no manifold no storage is needed and
	// the passed-in jacobian array is used directly. Also include space to store
	// the residuals, which is needed for cost-only evaluations. This is slightly
	// pessimistic, since both won't be needed all the time, but the amount of
	// excess should not cause problems for the caller.
	int num_parameters = NumParameterBlocks();
	int scratch_doubles = 1;
	for (int i = 0; i < num_parameters; ++i) {
	const ParameterBlock* parameter_block = parameter_blocks_[i];
	if (parameter_block->PlusJacobian() != nullptr) {
	scratch_doubles += parameter_block->Size();
	}
	}
	scratch_doubles *= NumResiduals();
	return scratch_doubles;
	}

	} // namespace ceres::internal