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added posibility to change internal weights of the network directly

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assigning the values
This commit is contained in:
rluna
2019-01-04 17:24:37 +01:00
parent aa3453baa8
commit f152b3030b
8 changed files with 149 additions and 6 deletions
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43
src/MLP.cpp
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@@ -48,7 +48,7 @@ void MLP::CreateMLP(const std::vector<uint64_t> & layers_nodes,
m_num_outputs = m_layers_nodes[m_layers_nodes.size() - 1];
m_num_hidden_layers = m_layers_nodes.size() - 2;
for (int i = 0; i < m_layers_nodes.size() - 1; i++) {
for (size_t i = 0; i < m_layers_nodes.size() - 1; i++) {
m_layers.emplace_back(Layer(m_layers_nodes[i],
m_layers_nodes[i + 1],
layers_activfuncs[i],
@@ -65,7 +65,7 @@ void MLP::SaveMLPNetwork(const std::string & filename)const {
fwrite(&m_num_hidden_layers, sizeof(m_num_hidden_layers), 1, file);
if (!m_layers_nodes.empty())
fwrite(&m_layers_nodes[0], sizeof(m_layers_nodes[0]), m_layers_nodes.size(), file);
for (int i = 0; i < m_layers.size(); i++) {
for (size_t i = 0; i < m_layers.size(); i++) {
m_layers[i].SaveLayer(file);
}
fclose(file);
@@ -83,7 +83,7 @@ void MLP::LoadMLPNetwork(const std::string & filename) {
if (!m_layers_nodes.empty())
fread(&m_layers_nodes[0], sizeof(m_layers_nodes[0]), m_layers_nodes.size(), file);
m_layers.resize(m_layers_nodes.size() - 1);
for (int i = 0; i < m_layers.size(); i++) {
for (size_t i = 0; i < m_layers.size(); i++) {
m_layers[i].LoadLayer(file);
}
fclose(file);
@@ -103,7 +103,7 @@ void MLP::GetOutput(const std::vector<double> &input,
std::vector<double> temp_out(temp_size, 0.0);
temp_in = input;
for (int i = 0; i < m_layers.size(); ++i) {
for (size_t i = 0; i < m_layers.size(); ++i) {
if (i > 0) {
//Store this layer activation
if (all_layers_activations != nullptr)
@@ -260,3 +260,38 @@ void MLP::Train(const std::vector<TrainingSample> &training_sample_set_with_bias
};
size_t MLP::GetNumLayers()
{
return m_layers.size();
}
std::vector<std::vector<double>> MLP::GetLayerWeights( size_t layer_i )
{
std::vector<std::vector<double>> ret_val;
// check parameters
if( 0 <= layer_i && layer_i < m_layers.size() )
{
Layer current_layer = m_layers[layer_i];
for( Node & node : current_layer.GetNodesChangeable() )
{
ret_val.push_back( node.GetWeights() );
}
return ret_val;
}
else
throw new std::logic_error("Incorrect layer number in GetLayerWeights call");
}
void MLP::SetLayerWeights( size_t layer_i, std::vector<std::vector<double>> & weights )
{
// check parameters
if( 0 <= layer_i && layer_i < m_layers.size() )
{
m_layers[layer_i].SetWeights( weights );
}
else
throw new std::logic_error("Incorrect layer number in SetLayerWeights call");
}