PLearn 0.1
DoubleProductVariable.cc
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00001 // -*- C++ -*-
00002 
00003 // DoubleProductVariable.cc
00004 //
00005 // Copyright (C) 2007 Simon Lemieux, Pascal Vincent
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: Simon Lemieux, Pascal Vincent
00036 
00040 #include "DoubleProductVariable.h"
00041 
00042 namespace PLearn {
00043 using namespace std;
00044 
00047 PLEARN_IMPLEMENT_OBJECT(
00048     DoubleProductVariable,
00049     "ONE LINE USER DESCRIPTION",
00050     "Let X,W and M be the inputs, nw the length of W and d their width (they all have the same width)"
00051     " \nThen output(n,i+j*nw) = sum_k{X(n,k)*W(i,k)*M(j,k)}");
00052 
00053 DoubleProductVariable::DoubleProductVariable(Var& x, Var& w, Var& m)
00054     : inherited(x & w & m, x.length(), w.length()*m.length())
00055 {
00056     build_();
00057 }
00058 
00059 
00060 void DoubleProductVariable::recomputeSize(int& l, int& w) const
00061 {   
00062         if (varray.size() > 0) {
00063             l = varray[0].length() ; // the computed length of this Var
00064             w = varray[1].length()*varray[2].length(); // the computed width
00065         } else
00066             l = w = 0;    
00067 }
00068 
00069 // ### computes value from varray values
00070 void DoubleProductVariable::fprop()
00071 {
00072     Mat x = varray[0]->matValue,
00073         w = varray[1]->matValue,
00074         m = varray[2]->matValue;
00075 
00076     int nx = x.length(),
00077         nw = w.length(),
00078         nm = m.length(),
00079         d = x.width();// ( = w.width() = m.width() )
00080 
00081 
00082     /*
00083     for(int n=0; n<nx; n++)
00084         for(int i=0; i<nw; i++)        
00085             for(int j=0; j<nm; j++)
00086             {
00087                 matValue(n,i+j*nw) = 0.;
00088                 for(int k=0; k<d; k++)
00089                     matValue(n,i+j*nw) += x(n,k)*w(i,k)*m(j,k);
00090             }
00091     */
00092 
00093     for(int n=0; n<nx; n++)
00094     {
00095         real* matValue_n = matValue[n];
00096         const real* x_n = x[n];
00097         for(int j=0; j<nm; j++)
00098         {
00099             const real* m_j = m[j];
00100             for(int i=0; i<nw; i++)
00101             {
00102                 const real* w_i = w[i];
00103                 real val = 0;
00104                 for(int k=0; k<d; k++)
00105                     val += x_n[k]*w_i[k]*m_j[k];
00106                 matValue_n[i+j*nw] = val;
00107             }
00108         }
00109     }
00110 }
00111 // ### computes varray gradients from gradient
00112 void DoubleProductVariable::bprop()
00113 {
00114     Mat x = varray[0]->matValue,
00115         w = varray[1]->matValue,
00116         m = varray[2]->matValue,
00117         x_grad = varray[0]->matGradient,
00118         w_grad = varray[1]->matGradient,
00119         m_grad = varray[2]->matGradient,
00120         s_grad = matGradient;
00121 
00122     int nx = x.length(),
00123         nw = w.length(),
00124         nm = m.length(),
00125         d = x.width();// ( = w.width()= m.width() )
00126 
00127     /*
00128      for(int n=0; n<nx; n++)
00129         for(int i=0 ;i<nw; i++)
00130             for(int j=0; j<nm; j++)
00131             {
00132                 for(int k=0; k<d; k++)
00133                 {
00134                     x_grad(n,k) += s_grad(n,i+j*nw)*w(i,k)*m(j,k);
00135                     w_grad(i,k) += s_grad(n,i+j*nw)*x(n,k)*m(j,k);
00136                     m_grad(j,k) += s_grad(n,i+j*nw)*x(n,k)*w(i,k);
00137                 }
00138             }
00139     */
00140 
00141     for(int n=0; n<nx; n++)
00142     {
00143         const real* s_grad_n = s_grad[n];
00144         const real* x_n = x[n];
00145         real* x_grad_n = x_grad[n];
00146         for(int j=0; j<nm; j++)
00147         {
00148             const real* m_j = m[j];
00149             real* m_grad_j = m_grad[j];
00150             for(int i=0 ;i<nw; i++)
00151             {
00152                 const real* w_i = w[i];
00153                 real* w_grad_i = w_grad[i];
00154                 real s_grad_n_val = s_grad_n[i+j*nw];
00155                 for(int k=0; k<d; k++)
00156                 {             
00157                     x_grad_n[k] += s_grad_n_val*w_i[k]*m_j[k];
00158                     w_grad_i[k] += s_grad_n_val*x_n[k]*m_j[k];
00159                     m_grad_j[k] += s_grad_n_val*x_n[k]*w_i[k];
00160                 }                
00161             }
00162         }
00163     }
00164 }
00165 // ### You can implement these methods:
00166 // void DoubleProductVariable::bbprop() {}
00167 // void DoubleProductVariable::symbolicBprop() {}
00168 // void DoubleProductVariable::rfprop() {}
00169 
00170 
00171 // ### Nothing to add here, simply calls build_
00172 void DoubleProductVariable::build()
00173 {
00174     inherited::build();
00175     build_();
00176 }
00177 
00178 void DoubleProductVariable::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00179 {
00180     inherited::makeDeepCopyFromShallowCopy(copies);
00181 
00182     // ### Call deepCopyField on all "pointer-like" fields
00183     // ### that you wish to be deepCopied rather than
00184     // ### shallow-copied.
00185     // ### ex:
00186     // deepCopyField(trainvec, copies);
00187 
00188     // ### If you want to deepCopy a Var field:
00189     // varDeepCopyField(somevariable, copies);
00190 }
00191 
00192 void DoubleProductVariable::declareOptions(OptionList& ol)
00193 {
00194     // ### Declare all of this object's options here.
00195     // ### For the "flags" of each option, you should typically specify
00196     // ### one of OptionBase::buildoption, OptionBase::learntoption or
00197     // ### OptionBase::tuningoption. If you don't provide one of these three,
00198     // ### this option will be ignored when loading values from a script.
00199     // ### You can also combine flags, for example with OptionBase::nosave:
00200     // ### (OptionBase::buildoption | OptionBase::nosave)
00201 
00202     // ### ex:
00203     // declareOption(ol, "myoption", &DoubleProductVariable::myoption,
00204     //               OptionBase::buildoption,
00205     //               "Help text describing this option");
00206     // ...
00207 
00208     // Now call the parent class' declareOptions
00209     inherited::declareOptions(ol);
00210 }
00211 
00212 void DoubleProductVariable::build_()
00213 {
00214     // ### This method should do the real buildincg of the object,
00215     // ### according to set 'options', in *any* situation.
00216     // ### Typical situations include:
00217     // ###  - Initial building of an object from a few user-specified options
00218     // ###  - Building of a "reloaded" object: i.e. from the complete set of
00219     // ###    all serialised options.
00220     // ###  - Updating or "re-building" of an object after a few "tuning"
00221     // ###    options have been modified.
00222     // ### You should assume that the parent class' build_() has already been
00223     // ### called.
00224    
00225     if (varW().width() != varX().width() || varW().width() != varM().width())
00226         PLERROR("All input matrix widths must be equal in DoubleProductVariable");
00227 }
00228 
00229 
00230 } // end of namespace PLearn
00231 
00232 
00233 
00234 /*
00235   Local Variables:
00236   mode:c++
00237   c-basic-offset:4
00238   c-file-style:"stroustrup"
00239   c-file-offsets:((innamespace . 0)(inline-open . 0))
00240   indent-tabs-mode:nil
00241   fill-column:79
00242   End:
00243 */
00244 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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