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Commit 6d69861a authored by Martin Beseda's avatar Martin Beseda
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WIP: Removing memory leaks

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src/Network/NeuralNetwork.cpp
+ 53
− 38
View file @ 6d69861a
......@@ -19,11 +19,10 @@ namespace lib4neuro {
NeuralNetwork::NeuralNetwork() {
this->neurons = new ::std::vector<Neuron *>(0);
this->neuron_biases = new ::std::vector<double>(0);
this->neuron_potentials = new ::std::vector<double>(0);
this->neuron_bias_indices = new ::std::vector<int>(0);
this->connection_weights = new ::std::vector<double>(0);
this->connection_list = new ::std::vector<ConnectionFunctionGeneral *>(0);
this->connection_list = ::std::vector<std::shared_ptr<ConnectionFunctionGeneral>>(0);
this->inward_adjacency = new ::std::vector<std::vector<std::pair<size_t, size_t>> *>(0);
this->outward_adjacency = new ::std::vector<std::vector<std::pair<size_t, size_t>> *>(0);
......@@ -96,17 +95,27 @@ namespace lib4neuro {
this->neuron_biases = nullptr;
}
if (this->connection_list) {
// if (this->connection_list) {
//
// if (this->delete_weights) {
// for (auto& c: *this->connection_list) {
// printf("%p\n", c);
// if(c) {
// printf("Deleting %p\n", c);
// puts("c");
//// delete c;
// puts("a");
//// c = nullptr;
// puts("b");
// }
// }
// }
// }
// this->connection_list.clear();
// delete this->connection_list;
// this->connection_list = nullptr;
if (this->delete_weights) {
for (auto c: *this->connection_list) {
delete c;
c = nullptr;
}
}
}
delete this->connection_list;
this->connection_list = nullptr;
// puts("*********** 1");
if (this->inward_adjacency) {
for (auto e: *this->inward_adjacency) {
......@@ -127,10 +136,8 @@ namespace lib4neuro {
e = nullptr;
}
}
delete this->
outward_adjacency;
this->
outward_adjacency = nullptr;
delete this-> outward_adjacency;
this->outward_adjacency = nullptr;
}
if (this->neuron_layers_feedforward) {
......@@ -455,9 +462,9 @@ namespace lib4neuro {
size_t ci = c.second;
this->neuron_potentials->at(ti) +=
this->connection_list->at(ci)->eval(*this->connection_weights) * potential;
this->connection_list.at(ci)->eval(*this->connection_weights) * potential;
std::cout << " adding input to neuron " << ti << " += " << this->connection_list->at(ci)->eval(*this->connection_weights) << "*" << potential << std::endl;
std::cout << " adding input to neuron " << ti << " += " << this->connection_list.at(ci)->eval(*this->connection_weights) << "*" << potential << std::endl;
}
}
}
......@@ -480,9 +487,11 @@ namespace lib4neuro {
NeuralNetwork::add_connection_simple(size_t n1_idx, size_t n2_idx, SIMPLE_CONNECTION_TYPE sct,
size_t weight_idx) {
ConnectionFunctionIdentity *con_weight_u1u2;
std::shared_ptr<ConnectionFunctionIdentity> con_weight_u1u2;
// ConnectionFunctionIdentity* con_weight_u1u2;
if (sct == SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT) {
con_weight_u1u2 = new ConnectionFunctionIdentity();
con_weight_u1u2 = std::make_shared<ConnectionFunctionIdentity>(ConnectionFunctionIdentity());
// con_weight_u1u2 = new ConnectionFunctionIdentity();
} else {
if (sct == SIMPLE_CONNECTION_TYPE::NEXT_WEIGHT) {
weight_idx = this->connection_weights->size();
......@@ -493,25 +502,26 @@ namespace lib4neuro {
}
}
con_weight_u1u2 = new ConnectionFunctionIdentity(weight_idx);
con_weight_u1u2 = std::make_shared<ConnectionFunctionIdentity>(ConnectionFunctionIdentity(weight_idx));
// con_weight_u1u2 = new ConnectionFunctionIdentity(weight_idx);
}
size_t conn_idx = this->add_new_connection_to_list(con_weight_u1u2);
// size_t conn_idx = this->add_new_connection_to_list(con_weight_u1u2);
this->add_outward_connection(n1_idx, n2_idx, conn_idx);
this->add_inward_connection(n2_idx, n1_idx, conn_idx);
this->layers_analyzed = false;
return this->connection_list->size() - 1;
return this->connection_list.size() - 1;
}
size_t
NeuralNetwork::add_connection_constant(size_t n1_idx, size_t n2_idx, double weight) {
std::shared_ptr<ConnectionFunctionConstant> cfc = std::make_shared<ConnectionFunctionConstant>(ConnectionFunctionConstant());
ConnectionFunctionConstant *con_weight_u1u2 = new ConnectionFunctionConstant( weight );
size_t conn_idx = this->add_new_connection_to_list(con_weight_u1u2);
size_t conn_idx = this->add_new_connection_to_list(cfc);
this->add_outward_connection(n1_idx, n2_idx, conn_idx);
this->add_inward_connection(n2_idx, n1_idx, conn_idx);
......@@ -524,7 +534,7 @@ namespace lib4neuro {
void NeuralNetwork::add_existing_connection(size_t n1_idx, size_t n2_idx, size_t connection_idx,
NeuralNetwork &parent_network) {
size_t conn_idx = this->add_new_connection_to_list(parent_network.connection_list->at(connection_idx));
size_t conn_idx = this->add_new_connection_to_list(parent_network.connection_list.at(connection_idx));
this->add_outward_connection(n1_idx, n2_idx, conn_idx);
this->add_inward_connection(n2_idx, n1_idx, conn_idx);
......@@ -610,7 +620,7 @@ namespace lib4neuro {
size_t ci = c.second;
this->neuron_potentials->at(ti) +=
this->connection_list->at(ci)->eval(*this->connection_weights) * potential;
this->connection_list.at(ci)->eval(*this->connection_weights) * potential;
}
}
}
......@@ -679,9 +689,9 @@ namespace lib4neuro {
size_t ci = c.second;
neuron_potential_t = this->neurons->at(ti)->get_last_activation_value( );
connection_weight = this->connection_list->at(ci)->eval(*this->connection_weights);
connection_weight = this->connection_list.at(ci)->eval(*this->connection_weights);
this->connection_list->at(ci)->eval_partial_derivative(*this->get_parameter_ptr_weights(),
this->connection_list.at(ci)->eval_partial_derivative(*this->get_parameter_ptr_weights(),
gradient,
neuron_potential_t *
scaling_backprog[neuron_idx]);
......@@ -756,11 +766,11 @@ namespace lib4neuro {
size_t ci = c.second;
neuron_activation_t = this->neurons->at(ti)->get_last_activation_value( );
connection_weight = this->connection_list->at(ci)->eval(*this->connection_weights);
connection_weight = this->connection_list.at(ci)->eval(*this->connection_weights);
std::cout << " [backpropagation] value ("<<ti<< "): " << neuron_activation_t << ", scaling: " << scaling_backprog[neuron_idx] << std::endl;
this->connection_list->at(ci)->eval_partial_derivative(*this->get_parameter_ptr_weights(),
this->connection_list.at(ci)->eval_partial_derivative(*this->get_parameter_ptr_weights(),
gradient,
neuron_activation_t *
scaling_backprog[neuron_idx]);
......@@ -946,7 +956,7 @@ namespace lib4neuro {
void NeuralNetwork::write_stats() {
::std::cout << std::flush
<< "Number of neurons: " << this->neurons->size() << ::std::endl
<< "Number of connections: " << this->connection_list->size() << ::std::endl
<< "Number of connections: " << this->connection_list.size() << ::std::endl
<< "Number of active weights: " << this->connection_weights->size() << ::std::endl
<< "Number of active biases: " << this->neuron_biases->size() << ::std::endl;
......@@ -968,7 +978,7 @@ namespace lib4neuro {
}
ofs << "Number of neurons: " << this->neurons->size() << ::std::endl
<< "Number of connections: " << this->connection_list->size() << ::std::endl
<< "Number of connections: " << this->connection_list.size() << ::std::endl
<< "Number of active weights: " << this->connection_weights->size() << ::std::endl
<< "Number of active biases: " << this->neuron_biases->size() << ::std::endl;
......@@ -985,7 +995,7 @@ namespace lib4neuro {
void NeuralNetwork::write_stats(std::ofstream* file_path) {
*file_path << "Number of neurons: " << this->neurons->size() << ::std::endl
<< "Number of connections: " << this->connection_list->size() << ::std::endl
<< "Number of connections: " << this->connection_list.size() << ::std::endl
<< "Number of active weights: " << this->connection_weights->size() << ::std::endl
<< "Number of active biases: " << this->neuron_biases->size() << ::std::endl;
......@@ -1006,9 +1016,14 @@ namespace lib4neuro {
return this->connection_weights;
}
size_t NeuralNetwork::add_new_connection_to_list(ConnectionFunctionGeneral *con) {
this->connection_list->push_back(con);
return this->connection_list->size() - 1;
// size_t NeuralNetwork::add_new_connection_to_list(ConnectionFunctionGeneral *con) {
// this->connection_list.push_back(std::make_shared<ConnectionFunctionGeneral>(*con));
// return this->connection_list.size() - 1;
// }
size_t NeuralNetwork::add_new_connection_to_list(std::shared_ptr<ConnectionFunctionGeneral> con) {
this->connection_list.push_back(con);
return this->connection_list.size() - 1;
}
void NeuralNetwork::add_inward_connection(size_t s, size_t t, size_t con_idx) {
......@@ -1222,7 +1237,7 @@ namespace lib4neuro {
this->neuron_bias_indices = new ::std::vector<int>(0);
this->connection_weights = new ::std::vector<double>(0);
this->connection_list = new ::std::vector<ConnectionFunctionGeneral *>(0);
this->connection_list = ::std::vector<std::shared_ptr<ConnectionFunctionGeneral>>(0);
this->inward_adjacency = new ::std::vector<std::vector<std::pair<size_t, size_t>> *>(0);
this->outward_adjacency = new ::std::vector<std::vector<std::pair<size_t, size_t>> *>(0);
......
src/Network/NeuralNetwork.h
+ 5
− 2
View file @ 6d69861a
......@@ -17,6 +17,7 @@
#include <algorithm>
#include <utility>
#include <fstream>
#include <memory>
#include "../settings.h"
#include "../Neuron/Neuron.h"
......@@ -89,7 +90,7 @@ namespace lib4neuro {
/**
*
*/
std::vector<ConnectionFunctionGeneral *> *connection_list = nullptr;
std::vector<std::shared_ptr<ConnectionFunctionGeneral>> connection_list; // = nullptr;
/**
*
......@@ -136,7 +137,9 @@ namespace lib4neuro {
* @param con Connection object to be added
* @return Returns the index of the added connection among all the connections
*/
size_t add_new_connection_to_list(ConnectionFunctionGeneral *con);
// size_t add_new_connection_to_list(ConnectionFunctionGeneral *con);
size_t add_new_connection_to_list(std::shared_ptr<ConnectionFunctionGeneral> con);
/**
* Adds a new entry (oriented edge s -> t) to the adjacency list of this network
......
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