163 lines
5.2 KiB
C++
163 lines
5.2 KiB
C++
/********************************************************
|
|
* ██████╗ ██████╗████████╗██╗
|
|
* ██╔════╝ ██╔════╝╚══██╔══╝██║
|
|
* ██║ ███╗██║ ██║ ██║
|
|
* ██║ ██║██║ ██║ ██║
|
|
* ╚██████╔╝╚██████╗ ██║ ███████╗
|
|
* ╚═════╝ ╚═════╝ ╚═╝ ╚══════╝
|
|
* Geophysical Computational Tools & Library (GCTL)
|
|
*
|
|
* Copyright (c) 2022 Yi Zhang (yizhang-geo@zju.edu.cn)
|
|
*
|
|
* GCTL is distributed under a dual licensing scheme. You can redistribute
|
|
* it and/or modify it under the terms of the GNU Lesser General Public
|
|
* License as published by the Free Software Foundation, either version 2
|
|
* of the License, or (at your option) any later version. You should have
|
|
* received a copy of the GNU Lesser General Public License along with this
|
|
* program. If not, see <http://www.gnu.org/licenses/>.
|
|
*
|
|
* If the terms and conditions of the LGPL v.2. would prevent you from using
|
|
* the GCTL, please consider the option to obtain a commercial license for a
|
|
* fee. These licenses are offered by the GCTL's original author. As a rule,
|
|
* licenses are provided "as-is", unlimited in time for a one time fee. Please
|
|
* send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget
|
|
* to include some description of your company and the realm of its activities.
|
|
* Also add information on how to contact you by electronic and paper mail.
|
|
******************************************************/
|
|
|
|
#include "olayer_multientropy.h"
|
|
|
|
gctl::multi_entropy::multi_entropy() {}
|
|
|
|
gctl::multi_entropy::~multi_entropy() {}
|
|
|
|
void gctl::multi_entropy::check_target_data(const matrix<double> &target)
|
|
{
|
|
int nobs = target.col_size();
|
|
int ncls = target.row_size();
|
|
|
|
int one;
|
|
for (size_t i = 0; i < nobs; i++)
|
|
{
|
|
one = 0;
|
|
for (size_t j = 0; j < ncls; j++)
|
|
{
|
|
if (fabs(target[j][i] - 1.0) < 1e-6)
|
|
{
|
|
one++;
|
|
continue;
|
|
}
|
|
|
|
if (fabs(target[j][i]) > 1e-6)
|
|
{
|
|
throw std::invalid_argument("[gctl::multi_entropy] Target data should only contain zero or one.");
|
|
}
|
|
}
|
|
|
|
if (one != 1)
|
|
{
|
|
throw std::invalid_argument("[gctl::multi_entropy] Each column of target data should only contain one \"1\".");
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
|
|
void gctl::multi_entropy::check_target_data(const array<int> &target)
|
|
{
|
|
int nobs = target.size();
|
|
for (size_t i = 0; i < nobs; i++)
|
|
{
|
|
if (target[i] < 0)
|
|
{
|
|
throw std::invalid_argument("[gctl::multi_entropy] Target data must be non-negative.");
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
|
|
void gctl::multi_entropy::evaluation(const matrix<double> &prev_layer_data, const matrix<double> &target)
|
|
{
|
|
int nobs = prev_layer_data.col_size();
|
|
int ncls = prev_layer_data.row_size();
|
|
|
|
if (target.col_size() != nobs || target.row_size() != ncls)
|
|
{
|
|
throw std::invalid_argument("[gctl::multi_entropy] Target data have incorrect dimension.");
|
|
}
|
|
|
|
// Compute the derivative of the input of this layer
|
|
// L = -sum(log(phat) * y)
|
|
// in = phat
|
|
// d(L) / d(in) = -y / phat
|
|
der_in_.resize(ncls, nobs, 0.0);
|
|
|
|
int i, j;
|
|
#pragma omp parallel for private (i, j) schedule(guided)
|
|
for (i = 0; i < ncls; i++)
|
|
{
|
|
for (j = 0; j < nobs; j++)
|
|
{
|
|
der_in_[i][j] = -1.0*target[i][j]/prev_layer_data[i][j];
|
|
}
|
|
}
|
|
|
|
// L = -sum(log(phat) * y)
|
|
// in = phat
|
|
// d(L) / d(in) = -y / phat
|
|
// m_din contains 0 if y = 0, and -1/phat if y = 1
|
|
loss_ = 0.0;
|
|
//#pragma omp parallel for private (i, j) schedule(guided)
|
|
for (i = 0; i < ncls; i++)
|
|
{
|
|
for (j = 0; j < nobs; j++)
|
|
{
|
|
loss_ -= std::log(prev_layer_data[i][j])*target[i][j];
|
|
}
|
|
}
|
|
|
|
loss_ /= der_in_.col_size();
|
|
return;
|
|
}
|
|
|
|
void gctl::multi_entropy::evaluation(const matrix<double> &prev_layer_data, const array<int> &target)
|
|
{
|
|
// target is a vector of class labels that take values from [0, 1, ..., nclass - 1]
|
|
// The i-th element of target is the class label for observation i
|
|
int nobs = prev_layer_data.col_size();
|
|
int ncls = prev_layer_data.row_size();
|
|
|
|
if (target.size() != nobs)
|
|
{
|
|
throw std::invalid_argument("[gctl::multi_entropy] Target data have incorrect dimension.");
|
|
}
|
|
|
|
// Compute the derivative of the input of this layer
|
|
// L = -log(phat[y])
|
|
// in = phat
|
|
// d(L) / d(in) = [0, 0, ..., -1/phat[y], 0, ..., 0]
|
|
der_in_.resize(ncls, nobs);
|
|
der_in_.assign_all(0.0);
|
|
|
|
int i;
|
|
#pragma omp parallel for private (i) schedule(guided)
|
|
for (i = 0; i < nobs; i++)
|
|
{
|
|
der_in_[target[i]][i] = -1.0/prev_layer_data[target[i]][i];
|
|
}
|
|
return;
|
|
}
|
|
|
|
double gctl::multi_entropy::loss_value() const
|
|
{
|
|
return loss_;
|
|
}
|
|
|
|
std::string gctl::multi_entropy::get_output_name() const
|
|
{
|
|
return "MultiClassEntropy";
|
|
}
|
|
|
|
gctl::olayer_type_e gctl::multi_entropy::get_output_type() const
|
|
{
|
|
return MultiClassEntropy;
|
|
} |