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cross_entropy_criterion.cc
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// Copyright 2008 Google Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
#include "cross_entropy_criterion.h"
namespace Torch {
CrossEntropyCriterion::CrossEntropyCriterion(int n_inputs_)
: Criterion(n_inputs_)
{
addBOption("average frame size", &average_frame_size, true, "divided by the frame size");
warning("CrossEntropyCriterion -> numerical issues here?");
}
void CrossEntropyCriterion::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++) {
err -= desired[i] * log(f_inputs[i]) + (1.-desired[i]) * log(1.-f_inputs[i]);
}
if(average_frame_size) {
err /= n_inputs;
}
f_outputs[0] = err;
//if(isnan(err) || isinf(err)) {
// warning("CrossEntropyCriterion::frameForward : isnan or isinf is true!");
//}
}
void CrossEntropyCriterion::frameBackward(int t, real *f_inputs, real *beta_, real *f_outputs, real *alpha_)
{
real *desired = data->targets->frames[t];
if(average_frame_size) {
real norm = 1./n_inputs;
for(int i = 0; i < n_inputs; i++) {
beta_[i] = norm * (f_inputs[i]-desired[i]) / (f_inputs[i]*(1.-f_inputs[i]));
//if(isnan(beta_[i]) || isinf(beta_[i])) {
// warning("CrossEntropyCriterion::frameBackward : isnan or isinf is true!");
//}
}
} else {
for(int i = 0; i < n_inputs; i++) {
beta_[i] = (f_inputs[i]-desired[i]) / (f_inputs[i]*(1.-f_inputs[i]));
}
}
}
CrossEntropyCriterion::~CrossEntropyCriterion()
{
}
}