ConcatColumnsVariable.cc

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// -*- C++ -*-

// PLearn (A C++ Machine Learning Library)
// Copyright (C) 1998 Pascal Vincent
// Copyright (C) 1999-2002 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal
// Copyright (C) 2001-2002 Nicolas Chapados, Ichiro Takeuchi, Jean-Sebastien Senecal
// Copyright (C) 2002 Xiangdong Wang, Christian Dorion

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// modification, are permitted provided that the following conditions are met:
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//  1. Redistributions of source code must retain the above copyright
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/* *******************************************************      
   * $Id: ConcatColumnsVariable.cc,v 1.4 2004/04/27 15:58:16 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "ConcatColumnsVariable.h"
#include "SubMatVariable.h"

namespace PLearn {
using namespace std;


PLEARN_IMPLEMENT_OBJECT(ConcatColumnsVariable,
                        "Concatenation of the columns of several variables",
                        "NO HELP");

ConcatColumnsVariable::ConcatColumnsVariable(const VarArray& vararray)
    : inherited(vararray.nonNull(), vararray.maxLength(), vararray.sumOfWidths())
{
    build_();
}

void
ConcatColumnsVariable::build()
{
    inherited::build();
    build_();
}

void
ConcatColumnsVariable::build_()
{
    if (varray->length()) {
        int l = varray[0]->length();
        for (int i = 1; i < varray.size(); i++)
            if (l != varray[i]->length())
                PLERROR("ConcatColumnsVariable: all non-null variables must have the same length");
    }
}

void ConcatColumnsVariable::recomputeSize(int& l, int& w) const
{
    if (varray) {
        l = varray.maxLength();
        w = varray.sumOfWidths();
    } else
        l = w = 0;
}

void ConcatColumnsVariable::fprop()
{
  int n_rows = matValue.length();
  int m_start = 0;
  int mod = matValue.mod();
  for (int m=0;m<varray.size();m++)
    {
      real* mp = varray[m]->valuedata;
      int n_cols = varray[m]->matValue.width();
      real* p = &valuedata[m_start];
      for (int i=0;i<n_rows;i++,p+=mod)
        for (int j=0;j<n_cols;j++,mp++)
          p[j] = *mp;
      m_start+=n_cols;
    }
}


void ConcatColumnsVariable::bprop()
{
  int n_rows = matValue.length();
  int m_start = 0;
  int mod = matValue.mod();
  for (int m=0;m<varray.size();m++)
    {
      real* mp = varray[m]->gradientdata;
      int n_cols = varray[m]->matGradient.width();
      real* p = &gradientdata[m_start];
      for (int i=0;i<n_rows;i++,p+=mod)
        for (int j=0;j<n_cols;j++,mp++)
          *mp += p[j];
      m_start+=n_cols;
    }
}


void ConcatColumnsVariable::symbolicBprop()
{
  int k=0;
  for (int n=0; n<varray.size(); n++) {
    Var vn = varray[n];
    vn->accg(new SubMatVariable(g, 0, k, length(), vn->width()));
    k += vn->width();
  }
}



} // end of namespace PLearn

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