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// Copyright (C) 2002 Ronan Collobert (collober@iro.umontreal.ca)
//
//
// This file is part of Torch. Release II.
// [The Ultimate Machine Learning Library]
//
// Torch is free software; you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation; either version 2 of the License, or
// (at your option) any later version.
//
// Torch is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with Torch; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#ifndef FILE_SPARSE_DATA_SET_INC
#define FILE_SPARSE_DATA_SET_INC
#include "SparseDataSet.h"
#include "IOTorch.h"
namespace Torch {
/** Create a #DataSet# from a \emph{sparse} disk file.
@author Ronan Collobert (collober@iro.umontreal.ca)
*/
class FileSparseDataSet : public SparseDataSet
{
public:
IOTorch melanie;
//-----
/** Load #file# in memory.
\begin{itemize}
\item #n_inputs_# is the input dimension of each example.
\item #n_targets# is the target dimension of each example.
\item #bin# is #true# if the file is in binary format.
\item if #max_load# > 0, it loads only the first #max_load# examples.
\end{itemize}
*/
FileSparseDataSet(const char *file, int n_inputs_, int n_targets, bool bin=false, int max_load=-1);
//-----
virtual ~FileSparseDataSet();
};
}
#endif
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