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// Copyright (C) 2003--2004 Ronan Collobert (collober@idiap.ch)
//
// This file is part of Torch 3.1.
//
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
// 3. The name of the author may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
// NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
// THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include "WeightedMSECriterion.h"
namespace Torch {
WeightedMSECriterion::WeightedMSECriterion(DataSet *data_) : Criterion(data_->n_targets)
{
addBOption("average frame size", &average_frame_size, true, "divided by the frame size");
data = data_;
weights = (real *)allocator->alloc(sizeof(real)*data->n_real_examples);
for(int i = 0; i < data->n_real_examples; i++)
weights[i] = 1;
}
WeightedMSECriterion::WeightedMSECriterion(DataSet *data_, real *weights_) : Criterion(data_->n_targets)
{
data = data_;
weights = weights_;
}
void WeightedMSECriterion::setDataSet(DataSet *data_)
{
if(data_->n_real_examples != data->n_real_examples)
error("WeightedMSECriterion: trying to use a wrong DataSet");
data = data_;
}
void WeightedMSECriterion::frameForward(int t, real *f_inputs, real *f_outputs)
{
real *desired = data->targets->frames[t];
real err = 0;
for(int i = 0; i < n_inputs; i++)
{
real z = desired[i] - f_inputs[i];
err += z*z;
}
f_outputs[0] = err*weights[data->real_current_example_index];
if(average_frame_size)
f_outputs[0] /= n_inputs;
}
void WeightedMSECriterion::frameBackward(int t, real *f_inputs, real *beta_, real *f_outputs, real *alpha_)
{
real z = 2.*weights[data->real_current_example_index];
if(average_frame_size)
z /= n_inputs;
real *desired = data->targets->frames[t];
for(int i = 0; i < n_inputs; i++)
beta_[i] = z*(f_inputs[i] - desired[i]);
}
WeightedMSECriterion::~WeightedMSECriterion()
{
}
}
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