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-rw-r--r--extern/ceres/include/ceres/dynamic_autodiff_cost_function.h95
1 files changed, 45 insertions, 50 deletions
diff --git a/extern/ceres/include/ceres/dynamic_autodiff_cost_function.h b/extern/ceres/include/ceres/dynamic_autodiff_cost_function.h
index e6d26111f18..7b75150b5ce 100644
--- a/extern/ceres/include/ceres/dynamic_autodiff_cost_function.h
+++ b/extern/ceres/include/ceres/dynamic_autodiff_cost_function.h
@@ -1,5 +1,5 @@
// Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2015 Google Inc. All rights reserved.
+// Copyright 2019 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// Redistribution and use in source and binary forms, with or without
@@ -28,7 +28,22 @@
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
// mierle@gmail.com (Keir Mierle)
-//
+
+#ifndef CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_
+#define CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_
+
+#include <cmath>
+#include <memory>
+#include <numeric>
+#include <vector>
+
+#include "ceres/dynamic_cost_function.h"
+#include "ceres/internal/fixed_array.h"
+#include "ceres/jet.h"
+#include "glog/logging.h"
+
+namespace ceres {
+
// This autodiff implementation differs from the one found in
// autodiff_cost_function.h by supporting autodiff on cost functions
// with variable numbers of parameters with variable sizes. With the
@@ -43,7 +58,7 @@
// bool operator()(T const* const* parameters, T* residuals) const {
// // Use parameters[i] to access the i'th parameter block.
// }
-// }
+// };
//
// Since the sizing of the parameters is done at runtime, you must
// also specify the sizes after creating the dynamic autodiff cost
@@ -60,40 +75,17 @@
// default, controlled by the Stride template parameter) with each
// pass. There is a tradeoff with the size of the passes; you may want
// to experiment with the stride.
-
-#ifndef CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_
-#define CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_
-
-#include <cmath>
-#include <numeric>
-#include <vector>
-
-#include "ceres/cost_function.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "ceres/jet.h"
-#include "glog/logging.h"
-
-namespace ceres {
-
template <typename CostFunctor, int Stride = 4>
-class DynamicAutoDiffCostFunction : public CostFunction {
+class DynamicAutoDiffCostFunction : public DynamicCostFunction {
public:
explicit DynamicAutoDiffCostFunction(CostFunctor* functor)
- : functor_(functor) {}
+ : functor_(functor) {}
virtual ~DynamicAutoDiffCostFunction() {}
- void AddParameterBlock(int size) {
- mutable_parameter_block_sizes()->push_back(size);
- }
-
- void SetNumResiduals(int num_residuals) {
- set_num_residuals(num_residuals);
- }
-
- virtual bool Evaluate(double const* const* parameters,
- double* residuals,
- double** jacobians) const {
+ bool Evaluate(double const* const* parameters,
+ double* residuals,
+ double** jacobians) const override {
CHECK_GT(num_residuals(), 0)
<< "You must call DynamicAutoDiffCostFunction::SetNumResiduals() "
<< "before DynamicAutoDiffCostFunction::Evaluate().";
@@ -112,20 +104,23 @@ class DynamicAutoDiffCostFunction : public CostFunction {
// depends on.
//
// To work around this issue, the solution here is to evaluate the
- // jacobians in a series of passes, each one computing Stripe *
+ // jacobians in a series of passes, each one computing Stride *
// num_residuals() derivatives. This is done with small, fixed-size jets.
- const int num_parameter_blocks = parameter_block_sizes().size();
- const int num_parameters = std::accumulate(parameter_block_sizes().begin(),
- parameter_block_sizes().end(),
- 0);
+ const int num_parameter_blocks =
+ static_cast<int>(parameter_block_sizes().size());
+ const int num_parameters = std::accumulate(
+ parameter_block_sizes().begin(), parameter_block_sizes().end(), 0);
// Allocate scratch space for the strided evaluation.
- std::vector<Jet<double, Stride> > input_jets(num_parameters);
- std::vector<Jet<double, Stride> > output_jets(num_residuals());
+ using JetT = Jet<double, Stride>;
+ internal::FixedArray<JetT, (256 * 7) / sizeof(JetT)> input_jets(
+ num_parameters);
+ internal::FixedArray<JetT, (256 * 7) / sizeof(JetT)> output_jets(
+ num_residuals());
// Make the parameter pack that is sent to the functor (reused).
- std::vector<Jet<double, Stride>* > jet_parameters(num_parameter_blocks,
- static_cast<Jet<double, Stride>* >(NULL));
+ internal::FixedArray<Jet<double, Stride>*> jet_parameters(
+ num_parameter_blocks, nullptr);
int num_active_parameters = 0;
// To handle constant parameters between non-constant parameter blocks, the
@@ -172,8 +167,8 @@ class DynamicAutoDiffCostFunction : public CostFunction {
// Evaluate all of the strides. Each stride is a chunk of the derivative to
// evaluate, typically some size proportional to the size of the SIMD
// registers of the CPU.
- int num_strides = static_cast<int>(ceil(num_active_parameters /
- static_cast<float>(Stride)));
+ int num_strides = static_cast<int>(
+ ceil(num_active_parameters / static_cast<float>(Stride)));
int current_derivative_section = 0;
int current_derivative_section_cursor = 0;
@@ -183,7 +178,7 @@ class DynamicAutoDiffCostFunction : public CostFunction {
// non-constant #Stride parameters.
const int initial_derivative_section = current_derivative_section;
const int initial_derivative_section_cursor =
- current_derivative_section_cursor;
+ current_derivative_section_cursor;
int active_parameter_count = 0;
parameter_cursor = 0;
@@ -193,9 +188,9 @@ class DynamicAutoDiffCostFunction : public CostFunction {
++j, parameter_cursor++) {
input_jets[parameter_cursor].v.setZero();
if (active_parameter_count < Stride &&
- parameter_cursor >= (
- start_derivative_section[current_derivative_section] +
- current_derivative_section_cursor)) {
+ parameter_cursor >=
+ (start_derivative_section[current_derivative_section] +
+ current_derivative_section_cursor)) {
if (jacobians[i] != NULL) {
input_jets[parameter_cursor].v[active_parameter_count] = 1.0;
++active_parameter_count;
@@ -222,9 +217,9 @@ class DynamicAutoDiffCostFunction : public CostFunction {
for (int j = 0; j < parameter_block_sizes()[i];
++j, parameter_cursor++) {
if (active_parameter_count < Stride &&
- parameter_cursor >= (
- start_derivative_section[current_derivative_section] +
- current_derivative_section_cursor)) {
+ parameter_cursor >=
+ (start_derivative_section[current_derivative_section] +
+ current_derivative_section_cursor)) {
if (jacobians[i] != NULL) {
for (int k = 0; k < num_residuals(); ++k) {
jacobians[i][k * parameter_block_sizes()[i] + j] =
@@ -252,7 +247,7 @@ class DynamicAutoDiffCostFunction : public CostFunction {
}
private:
- internal::scoped_ptr<CostFunctor> functor_;
+ std::unique_ptr<CostFunctor> functor_;
};
} // namespace ceres
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