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Austin Schuh70cc9552019-01-21 19:46:48 -08001// Ceres Solver - A fast non-linear least squares minimizer
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29// Author: keir@google.com (Keir Mierle)
30
31#include "ceres/compressed_row_jacobian_writer.h"
32
33#include <iterator>
34#include <utility>
35#include <vector>
36
37#include "ceres/casts.h"
38#include "ceres/compressed_row_sparse_matrix.h"
39#include "ceres/parameter_block.h"
40#include "ceres/program.h"
41#include "ceres/residual_block.h"
42#include "ceres/scratch_evaluate_preparer.h"
43
44namespace ceres {
45namespace internal {
46
47using std::make_pair;
48using std::pair;
49using std::vector;
50using std::adjacent_find;
51
52void CompressedRowJacobianWriter::PopulateJacobianRowAndColumnBlockVectors(
53 const Program* program, CompressedRowSparseMatrix* jacobian) {
54 const vector<ParameterBlock*>& parameter_blocks =
55 program->parameter_blocks();
56 vector<int>& col_blocks = *(jacobian->mutable_col_blocks());
57 col_blocks.resize(parameter_blocks.size());
58 for (int i = 0; i < parameter_blocks.size(); ++i) {
59 col_blocks[i] = parameter_blocks[i]->LocalSize();
60 }
61
62 const vector<ResidualBlock*>& residual_blocks =
63 program->residual_blocks();
64 vector<int>& row_blocks = *(jacobian->mutable_row_blocks());
65 row_blocks.resize(residual_blocks.size());
66 for (int i = 0; i < residual_blocks.size(); ++i) {
67 row_blocks[i] = residual_blocks[i]->NumResiduals();
68 }
69}
70
71void CompressedRowJacobianWriter::GetOrderedParameterBlocks(
72 const Program* program,
73 int residual_id,
74 vector<pair<int, int>>* evaluated_jacobian_blocks) {
75 const ResidualBlock* residual_block =
76 program->residual_blocks()[residual_id];
77 const int num_parameter_blocks = residual_block->NumParameterBlocks();
78
79 for (int j = 0; j < num_parameter_blocks; ++j) {
80 const ParameterBlock* parameter_block =
81 residual_block->parameter_blocks()[j];
82 if (!parameter_block->IsConstant()) {
83 evaluated_jacobian_blocks->push_back(
84 make_pair(parameter_block->index(), j));
85 }
86 }
87 sort(evaluated_jacobian_blocks->begin(), evaluated_jacobian_blocks->end());
88}
89
90SparseMatrix* CompressedRowJacobianWriter::CreateJacobian() const {
91 const vector<ResidualBlock*>& residual_blocks =
92 program_->residual_blocks();
93
94 int total_num_residuals = program_->NumResiduals();
95 int total_num_effective_parameters = program_->NumEffectiveParameters();
96
97 // Count the number of jacobian nonzeros.
98 int num_jacobian_nonzeros = 0;
99 for (int i = 0; i < residual_blocks.size(); ++i) {
100 ResidualBlock* residual_block = residual_blocks[i];
101 const int num_residuals = residual_block->NumResiduals();
102 const int num_parameter_blocks = residual_block->NumParameterBlocks();
103 for (int j = 0; j < num_parameter_blocks; ++j) {
104 ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
105 if (!parameter_block->IsConstant()) {
106 num_jacobian_nonzeros += num_residuals * parameter_block->LocalSize();
107 }
108 }
109 }
110
111 // Allocate storage for the jacobian with some extra space at the end.
112 // Allocate more space than needed to store the jacobian so that when the LM
113 // algorithm adds the diagonal, no reallocation is necessary. This reduces
114 // peak memory usage significantly.
115 CompressedRowSparseMatrix* jacobian =
116 new CompressedRowSparseMatrix(
117 total_num_residuals,
118 total_num_effective_parameters,
119 num_jacobian_nonzeros + total_num_effective_parameters);
120
121 // At this stage, the CompressedRowSparseMatrix is an invalid state. But this
122 // seems to be the only way to construct it without doing a memory copy.
123 int* rows = jacobian->mutable_rows();
124 int* cols = jacobian->mutable_cols();
125
126 int row_pos = 0;
127 rows[0] = 0;
128 for (int i = 0; i < residual_blocks.size(); ++i) {
129 const ResidualBlock* residual_block = residual_blocks[i];
130 const int num_parameter_blocks = residual_block->NumParameterBlocks();
131
132 // Count the number of derivatives for a row of this residual block and
133 // build a list of active parameter block indices.
134 int num_derivatives = 0;
135 vector<int> parameter_indices;
136 for (int j = 0; j < num_parameter_blocks; ++j) {
137 ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
138 if (!parameter_block->IsConstant()) {
139 parameter_indices.push_back(parameter_block->index());
140 num_derivatives += parameter_block->LocalSize();
141 }
142 }
143
144 // Sort the parameters by their position in the state vector.
145 sort(parameter_indices.begin(), parameter_indices.end());
146 if (adjacent_find(parameter_indices.begin(), parameter_indices.end()) !=
147 parameter_indices.end()) {
148 std::string parameter_block_description;
149 for (int j = 0; j < num_parameter_blocks; ++j) {
150 ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
151 parameter_block_description +=
152 parameter_block->ToString() + "\n";
153 }
154 LOG(FATAL) << "Ceres internal error: "
155 << "Duplicate parameter blocks detected in a cost function. "
156 << "This should never happen. Please report this to "
157 << "the Ceres developers.\n"
158 << "Residual Block: " << residual_block->ToString() << "\n"
159 << "Parameter Blocks: " << parameter_block_description;
160 }
161
162 // Update the row indices.
163 const int num_residuals = residual_block->NumResiduals();
164 for (int j = 0; j < num_residuals; ++j) {
165 rows[row_pos + j + 1] = rows[row_pos + j] + num_derivatives;
166 }
167
168 // Iterate over parameter blocks in the order which they occur in the
169 // parameter vector. This code mirrors that in Write(), where jacobian
170 // values are updated.
171 int col_pos = 0;
172 for (int j = 0; j < parameter_indices.size(); ++j) {
173 ParameterBlock* parameter_block =
174 program_->parameter_blocks()[parameter_indices[j]];
175 const int parameter_block_size = parameter_block->LocalSize();
176
177 for (int r = 0; r < num_residuals; ++r) {
178 // This is the position in the values array of the jacobian where this
179 // row of the jacobian block should go.
180 const int column_block_begin = rows[row_pos + r] + col_pos;
181
182 for (int c = 0; c < parameter_block_size; ++c) {
183 cols[column_block_begin + c] = parameter_block->delta_offset() + c;
184 }
185 }
186 col_pos += parameter_block_size;
187 }
188 row_pos += num_residuals;
189 }
190 CHECK_EQ(num_jacobian_nonzeros, rows[total_num_residuals]);
191
192 PopulateJacobianRowAndColumnBlockVectors(program_, jacobian);
193
194 return jacobian;
195}
196
197void CompressedRowJacobianWriter::Write(int residual_id,
198 int residual_offset,
199 double **jacobians,
200 SparseMatrix* base_jacobian) {
201 CompressedRowSparseMatrix* jacobian =
202 down_cast<CompressedRowSparseMatrix*>(base_jacobian);
203
204 double* jacobian_values = jacobian->mutable_values();
205 const int* jacobian_rows = jacobian->rows();
206
207 const ResidualBlock* residual_block =
208 program_->residual_blocks()[residual_id];
209 const int num_residuals = residual_block->NumResiduals();
210
211 vector<pair<int, int>> evaluated_jacobian_blocks;
212 GetOrderedParameterBlocks(program_, residual_id, &evaluated_jacobian_blocks);
213
214 // Where in the current row does the jacobian for a parameter block begin.
215 int col_pos = 0;
216
217 // Iterate over the jacobian blocks in increasing order of their
218 // positions in the reduced parameter vector.
219 for (int i = 0; i < evaluated_jacobian_blocks.size(); ++i) {
220 const ParameterBlock* parameter_block =
221 program_->parameter_blocks()[evaluated_jacobian_blocks[i].first];
222 const int argument = evaluated_jacobian_blocks[i].second;
223 const int parameter_block_size = parameter_block->LocalSize();
224
225 // Copy one row of the jacobian block at a time.
226 for (int r = 0; r < num_residuals; ++r) {
227 // Position of the r^th row of the current jacobian block.
228 const double* block_row_begin =
229 jacobians[argument] + r * parameter_block_size;
230
231 // Position in the values array of the jacobian where this
232 // row of the jacobian block should go.
233 double* column_block_begin =
234 jacobian_values + jacobian_rows[residual_offset + r] + col_pos;
235
236 std::copy(block_row_begin,
237 block_row_begin + parameter_block_size,
238 column_block_begin);
239 }
240 col_pos += parameter_block_size;
241 }
242}
243
244} // namespace internal
245} // namespace ceres