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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
#include "WeightedSumMachine.h"
#include "random.h"
namespace Torch {
WeightedSumMachine::WeightedSumMachine(Trainer **trainers_, int n_trainers_, List** trainers_measurers_, real *weights_)
{
// Boaf
trainers = trainers_;
trainers_measurers = trainers_measurers_;
n_trainers = n_trainers_;
n_outputs = trainers[0]->machine->n_outputs;
addToList(&outputs, n_outputs, (real *)xalloc(sizeof(real)*n_outputs));
if(weights_)
{
weights = weights_;
weights_is_allocated = false;
}
else
{
weights = (real *)xalloc(n_trainers*sizeof(real));
for(int i = 0; i < n_trainers; i++)
weights[i] = 0;
weights_is_allocated = true;
}
n_trainers_trained = 0;
}
void WeightedSumMachine::reset()
{
for (int i=0;i<n_trainers;i++)
trainers[i]->machine->reset();
n_trainers_trained = 0;
}
void WeightedSumMachine::forward(List *inputs)
{
real* pout = (real*)outputs->ptr;
for(int j = 0; j < n_outputs; j++)
*pout++ = 0;
for(int i = 0; i < n_trainers_trained; i++)
{
trainers[i]->machine->forward(inputs);
real z = weights[i];
pout = (real*)outputs->ptr;
List *out = trainers[i]->machine->outputs;
while(out)
{
real *ptr_out = (real *)out->ptr;
for(int j = 0; j < out->n; j++)
*pout++ += z * *ptr_out++;
out = out->next;
}
}
}
void WeightedSumMachine::loadFILE(FILE *file)
{
xfread(&n_trainers_trained, sizeof(int), 1, file);
xfread(weights, sizeof(real), n_trainers, file);
for (int i = 0; i < n_trainers; i++)
trainers[i]->loadFILE(file);
}
void WeightedSumMachine::saveFILE(FILE *file)
{
xfwrite(&n_trainers_trained, sizeof(int), 1, file);
xfwrite(weights, sizeof(real), n_trainers, file);
for (int i = 0; i < n_trainers; i++)
trainers[i]->saveFILE(file);
}
WeightedSumMachine::~WeightedSumMachine()
{
freeList(&outputs, true);
if(weights_is_allocated)
free(weights);
}
}
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