PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // GaussianProcessNLLVariable.h 00004 // 00005 // Copyright (C) 2006 Nicolas Chapados 00006 // 00007 // Redistribution and use in source and binary forms, with or without 00008 // modification, are permitted provided that the following conditions are met: 00009 // 00010 // 1. Redistributions of source code must retain the above copyright 00011 // notice, this list of conditions and the following disclaimer. 00012 // 00013 // 2. Redistributions in binary form must reproduce the above copyright 00014 // notice, this list of conditions and the following disclaimer in the 00015 // documentation and/or other materials provided with the distribution. 00016 // 00017 // 3. The name of the authors may not be used to endorse or promote 00018 // products derived from this software without specific prior written 00019 // permission. 00020 // 00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR 00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN 00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED 00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00031 // 00032 // This file is part of the PLearn library. For more information on the PLearn 00033 // library, go to the PLearn Web site at www.plearn.org 00034 00035 // Authors: Nicolas Chapados 00036 00040 #ifndef GaussianProcessNLLVariable_INC 00041 #define GaussianProcessNLLVariable_INC 00042 00043 #include <plearn/var/NaryVariable.h> 00044 #include <plearn/ker/Kernel.h> 00045 00046 namespace PLearn { 00047 using namespace std; 00048 00068 class GaussianProcessNLLVariable : public NaryVariable 00069 { 00070 typedef NaryVariable inherited; 00071 00072 public: 00073 //##### Public Build Options ############################################ 00074 00077 bool m_save_gram_matrix; 00078 00080 PPath m_expdir; 00081 00082 public: 00083 //##### Public Member Functions ######################################### 00084 00086 GaussianProcessNLLVariable(); 00087 00105 GaussianProcessNLLVariable(Kernel* kernel, real noise, 00106 Mat inputs, Mat targets, 00107 const TVec<string>& hyperparam_names, 00108 const VarArray& hyperparam_vars, 00109 bool allow_bprop = true, 00110 bool save_gram_matrix = false, 00111 PPath expdir = ""); 00112 00113 00114 //##### PLearn::Variable methods ######################################### 00115 00116 virtual void recomputeSize(int& l, int& w) const; 00117 virtual void fprop(); 00118 virtual void bprop(); 00119 00138 static void fbpropFragments(Kernel* kernel, real noise, const Mat& inputs, 00139 const Mat& targets, bool compute_inverse, 00140 bool save_gram_matrix, const PPath& expdir, 00141 Mat& gram, Mat& L, Mat& alpha, Mat& inv, 00142 Vec& tmpch, Mat& tmprhs); 00143 00145 const Mat& alpha() const; 00146 00148 const Mat& gram() const { return m_gram; } 00149 00151 const Mat& gramInverse() const { return m_inverse_gram; } 00152 00154 static void logVarray(const VarArray& varr, const string& title="", 00155 bool debug=false); 00156 00157 00158 //##### PLearn::Object Protocol ######################################### 00159 00160 // Declares other standard object methods. 00161 PLEARN_DECLARE_OBJECT(GaussianProcessNLLVariable); 00162 00163 // Simply calls inherited::build() then build_() 00164 virtual void build(); 00165 00167 virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies); 00168 00169 protected: 00171 Kernel* m_kernel; 00172 00174 real m_noise; 00175 00177 Mat m_inputs; 00178 00180 Mat m_targets; 00181 00184 TVec<string> m_hyperparam_names; 00185 00188 VarArray m_hyperparam_vars; 00189 00191 bool m_allow_bprop; 00192 00194 Mat m_gram; 00195 00198 Mat m_gram_derivative; 00199 00201 Mat m_cholesky_gram; 00202 00205 Mat m_alpha_t; 00206 00209 mutable Mat m_alpha_buf; 00210 00212 Mat m_inverse_gram; 00213 00215 Vec m_cholesky_tmp; 00216 00218 Mat m_rhs_tmp; 00219 00220 protected: 00222 static void declareOptions(OptionList& ol); 00223 00224 private: 00226 void build_(); 00227 }; 00228 00229 // Declares a few other classes and functions related to this class 00230 DECLARE_OBJECT_PTR(GaussianProcessNLLVariable); 00231 00232 } // end of namespace PLearn 00233 00234 #endif 00235 00236 00237 /* 00238 Local Variables: 00239 mode:c++ 00240 c-basic-offset:4 00241 c-file-style:"stroustrup" 00242 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00243 indent-tabs-mode:nil 00244 fill-column:79 00245 End: 00246 */ 00247 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :