82 lines
2.5 KiB
C++
82 lines
2.5 KiB
C++
/**************************************************************************************************
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* LibNeural++ v.0.2 - All-purpose library for managing neural networks *
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* Copyright (C) 2009, BlackLight *
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* *
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* This program is free software: you can redistribute it and/or modify it under the terms of the *
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* GNU General Public License as published by the Free Software Foundation, either version 3 of *
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* the License, or (at your option) any later version. This program is distributed in the hope *
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* that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of *
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for *
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* more details. You should have received a copy of the GNU General Public License along with *
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* this program. If not, see <http://www.gnu.org/licenses/>. *
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**************************************************************************************************/
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#include <cstdlib>
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#include "neural++.hpp"
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namespace neuralpp {
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Layer::Layer(size_t sz, double (*a) (double), double (*d) (double)) {
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for (size_t i = 0; i < sz; i++) {
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Neuron n(a, d);
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elements.push_back(n);
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}
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actv_f = a;
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deriv = d;
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}
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Layer::Layer(vector < Neuron > &el, double (*a) (double),
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double (*d) (double)) {
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elements = el;
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actv_f = a;
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deriv = d;
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}
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size_t Layer::size() const {
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return elements.size();
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}
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Neuron & Layer::operator[](size_t i) throw(NetworkIndexOutOfBoundsException) {
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if (i > size())
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throw NetworkIndexOutOfBoundsException();
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return elements[i];
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}
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void Layer::link(Layer & l) {
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srand((unsigned) time(NULL));
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for (size_t i = 0; i < l.size(); i++) {
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Neuron *n1 = &(l.elements[i]);
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for (size_t j = 0; j < size(); j++) {
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Neuron *n2 = &(elements[j]);
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Synapsis s(n1, n2, RAND, actv_f, deriv);
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n1->push_out(s);
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n2->push_in(s);
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}
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}
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}
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void Layer::setProp(vector < double >&v) {
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for (size_t i = 0; i < size(); i++)
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elements[i].setProp(v[i]);
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}
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void Layer::setActv(vector < double >&v) {
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for (size_t i = 0; i < size(); i++)
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elements[i].setActv(v[i]);
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}
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void Layer::propagate() {
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for (size_t i = 0; i < size(); i++) {
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Neuron *n = &(elements[i]);
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n->setProp(n->propagate());
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n->setActv(actv_f(n->getProp()));
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}
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}
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}
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