diff options
author | Chris Dyer <cdyer@allegro.clab.cs.cmu.edu> | 2012-11-18 13:35:42 -0500 |
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committer | Chris Dyer <cdyer@allegro.clab.cs.cmu.edu> | 2012-11-18 13:35:42 -0500 |
commit | 1b8181bf0d6e9137e6b9ccdbe414aec37377a1a9 (patch) | |
tree | 33e5f3aa5abff1f41314cf8f6afbd2c2c40e4bfd /training/utils/optimize.h | |
parent | 7c4665949fb93fb3de402e4ce1d19bef67850d05 (diff) |
major restructure of the training code
Diffstat (limited to 'training/utils/optimize.h')
-rw-r--r-- | training/utils/optimize.h | 92 |
1 files changed, 92 insertions, 0 deletions
diff --git a/training/utils/optimize.h b/training/utils/optimize.h new file mode 100644 index 00000000..07943b44 --- /dev/null +++ b/training/utils/optimize.h @@ -0,0 +1,92 @@ +#ifndef _OPTIMIZE_H_ +#define _OPTIMIZE_H_ + +#include <iostream> +#include <vector> +#include <string> +#include <cassert> + +#include "lbfgs.h" + +// abstract base class for first order optimizers +// order of invocation: new, Load(), Optimize(), Save(), delete +class BatchOptimizer { + public: + BatchOptimizer() : eval_(1), has_converged_(false) {} + virtual ~BatchOptimizer(); + virtual std::string Name() const = 0; + int EvaluationCount() const { return eval_; } + bool HasConverged() const { return has_converged_; } + + void Optimize(const double& obj, + const std::vector<double>& g, + std::vector<double>* x) { + assert(g.size() == x->size()); + ++eval_; + OptimizeImpl(obj, g, x); + scitbx::lbfgs::traditional_convergence_test<double> converged(g.size()); + has_converged_ = converged(&(*x)[0], &g[0]); + } + + void Save(std::ostream* out) const; + void Load(std::istream* in); + protected: + virtual void SaveImpl(std::ostream* out) const; + virtual void LoadImpl(std::istream* in); + virtual void OptimizeImpl(const double& obj, + const std::vector<double>& g, + std::vector<double>* x) = 0; + + int eval_; + private: + bool has_converged_; +}; + +class RPropOptimizer : public BatchOptimizer { + public: + explicit RPropOptimizer(int num_vars, + double eta_plus = 1.2, + double eta_minus = 0.5, + double delta_0 = 0.1, + double delta_max = 50.0, + double delta_min = 1e-6) : + prev_g_(num_vars, 0.0), + delta_ij_(num_vars, delta_0), + eta_plus_(eta_plus), + eta_minus_(eta_minus), + delta_max_(delta_max), + delta_min_(delta_min) { + assert(eta_plus > 1.0); + assert(eta_minus > 0.0 && eta_minus < 1.0); + assert(delta_max > 0.0); + assert(delta_min > 0.0); + } + std::string Name() const; + void OptimizeImpl(const double& obj, + const std::vector<double>& g, + std::vector<double>* x); + void SaveImpl(std::ostream* out) const; + void LoadImpl(std::istream* in); + private: + std::vector<double> prev_g_; + std::vector<double> delta_ij_; + const double eta_plus_; + const double eta_minus_; + const double delta_max_; + const double delta_min_; +}; + +class LBFGSOptimizer : public BatchOptimizer { + public: + explicit LBFGSOptimizer(int num_vars, int memory_buffers = 10); + std::string Name() const; + void SaveImpl(std::ostream* out) const; + void LoadImpl(std::istream* in); + void OptimizeImpl(const double& obj, + const std::vector<double>& g, + std::vector<double>* x); + private: + scitbx::lbfgs::minimizer<double> opt_; +}; + +#endif |