| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193 | // Ceres Solver - A fast non-linear least squares minimizer// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.// http://code.google.com/p/ceres-solver///// 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: wjr@google.com (William Rucklidge)//// This file contains tests for the GradientChecker class.#include "ceres/gradient_checker.h"#include <cmath>#include <cstdlib>#include <vector>#include "ceres/cost_function.h"#include "ceres/random.h"#include "glog/logging.h"#include "gtest/gtest.h"namespace ceres {namespace internal {// We pick a (non-quadratic) function whose derivative are easy:////    f = exp(- a' x).//   df = - f a.//// where 'a' is a vector of the same size as 'x'. In the block// version, they are both block vectors, of course.class GoodTestTerm : public CostFunction { public:  GoodTestTerm(int arity, int const *dim) : arity_(arity) {    // Make 'arity' random vectors.    a_.resize(arity_);    for (int j = 0; j < arity_; ++j) {      a_[j].resize(dim[j]);      for (int u = 0; u < dim[j]; ++u) {        a_[j][u] = 2.0 * RandDouble() - 1.0;      }    }    for (int i = 0; i < arity_; i++) {      mutable_parameter_block_sizes()->push_back(dim[i]);    }    set_num_residuals(1);  }  bool Evaluate(double const* const* parameters,                double* residuals,                double** jacobians) const {    // Compute a . x.    double ax = 0;    for (int j = 0; j < arity_; ++j) {      for (int u = 0; u < parameter_block_sizes()[j]; ++u) {        ax += a_[j][u] * parameters[j][u];      }    }    // This is the cost, but also appears as a factor    // in the derivatives.    double f = *residuals = exp(-ax);    // Accumulate 1st order derivatives.    if (jacobians) {      for (int j = 0; j < arity_; ++j) {        if (jacobians[j]) {          for (int u = 0; u < parameter_block_sizes()[j]; ++u) {            // See comments before class.            jacobians[j][u] = - f * a_[j][u];          }        }      }    }    return true;  } private:  int arity_;  vector<vector<double> > a_;  // our vectors.};class BadTestTerm : public CostFunction { public:  BadTestTerm(int arity, int const *dim) : arity_(arity) {    // Make 'arity' random vectors.    a_.resize(arity_);    for (int j = 0; j < arity_; ++j) {      a_[j].resize(dim[j]);      for (int u = 0; u < dim[j]; ++u) {        a_[j][u] = 2.0 * RandDouble() - 1.0;      }    }    for (int i = 0; i < arity_; i++) {      mutable_parameter_block_sizes()->push_back(dim[i]);    }    set_num_residuals(1);  }  bool Evaluate(double const* const* parameters,                double* residuals,                double** jacobians) const {    // Compute a . x.    double ax = 0;    for (int j = 0; j < arity_; ++j) {      for (int u = 0; u < parameter_block_sizes()[j]; ++u) {        ax += a_[j][u] * parameters[j][u];      }    }    // This is the cost, but also appears as a factor    // in the derivatives.    double f = *residuals = exp(-ax);    // Accumulate 1st order derivatives.    if (jacobians) {      for (int j = 0; j < arity_; ++j) {        if (jacobians[j]) {          for (int u = 0; u < parameter_block_sizes()[j]; ++u) {            // See comments before class.            jacobians[j][u] = - f * a_[j][u] + 0.001;          }        }      }    }    return true;  } private:  int arity_;  vector<vector<double> > a_;  // our vectors.};TEST(GradientChecker, SmokeTest) {  srand(5);  // Test with 3 blocks of size 2, 3 and 4.  int const arity = 3;  int const dim[arity] = { 2, 3, 4 };  // Make a random set of blocks.  FixedArray<double*> parameters(arity);  for (int j = 0; j < arity; ++j) {    parameters[j] = new double[dim[j]];    for (int u = 0; u < dim[j]; ++u) {      parameters[j][u] = 2.0 * RandDouble() - 1.0;    }  }  // Make a term and probe it.  GoodTestTerm good_term(arity, dim);  typedef GradientChecker<GoodTestTerm, 1, 2, 3, 4> GoodTermGradientChecker;  EXPECT_TRUE(GoodTermGradientChecker::Probe(      parameters.get(), 1e-6, &good_term, NULL));  BadTestTerm bad_term(arity, dim);  typedef GradientChecker<BadTestTerm, 1, 2, 3, 4> BadTermGradientChecker;  EXPECT_FALSE(BadTermGradientChecker::Probe(      parameters.get(), 1e-6, &bad_term, NULL));  for (int j = 0; j < arity; j++) {    delete[] parameters[j];  }}}  // namespace internal}  // namespace ceres
 |