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MachSoftmaxStable.h
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/*
* This file is part of the continuous space language and translation model toolkit
* for statistical machine translation and large vocabulary speech recognition.
*
* Copyright 2015, Holger Schwenk, LIUM, University of Le Mans, France
*
* The CSLM toolkit is free software; you can redistribute it and/or modify it
* under the terms of the GNU Lesser General Public License version 3 as
* published by the Free Software Foundation
*
* This library 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 Lesser General Public License
* for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this library; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA
*
*
*
* softmax machine: a_i = exp(a_i) / sum_k a_k
* The stable version remove the max of a_i to all a_i before exp.
* This lower numerical precision problem
* with a_k is the kth output of a linear machine
*/
#ifndef _MachSoftmaxStable_h
#define _MachSoftmaxStable_h
#include "MachLin.h"
#undef BLAS_CUDA_NPPS_SUM // thsi should be faster, but I can't get it working
class MachSoftmaxStable : public MachLin
{
private:
Timer tmn; // cumulated time used for softmax normalization
#if defined(BLAS_CUDA) && defined(BLAS_CUDA_NPPS_SUM)
Npp8u *gpu_sum_buf; // temporary buffer for fast sum with nppsSum_32f()
#endif
protected:
MachSoftmaxStable(const MachSoftmaxStable &); // create a copy of the machine
public:
MachSoftmaxStable(const int=0, const int=0, const int=128, const ulong=0, const ulong=0, const int shareid=-1, const bool xdata=false);
virtual ~MachSoftmaxStable();
virtual MachSoftmaxStable *Clone() {return new MachSoftmaxStable(*this);} // create a copy of the machine
virtual int GetMType() {return file_header_mtype_softmax_stable;}; // get type of machine
virtual void Info(bool=false, char *txt=(char*)""); // display (detailed) information on machine
virtual void Forw(int=0, bool=false); // calculate outputs for current inputs
// backprop gradients from output to input and update all weights
virtual void Backw (const float lrate, const float wdecay, int=0);
};
#endif