Comrade::Osiris::FastSOM_Neuron::FastSOM_Neuron(int num_ip)
{
num_inputs=num_ip;
weight_vector.resize(num_inputs,0);
input_vector.resize(num_inputs,0);
set_activation_function(Comrade::Osiris::unipolar_hardlimiting);
}
void model::readConfig(ifstream &config_file)
{
string line;
vector<string> fields;
int ngram_size, vocab_size, input_embedding_dimension, num_hidden, output_embedding_dimension;
activation_function_type activation_function = this->activation_function;
while (getline(config_file, line) && line != "")
{
splitBySpace(line, fields);
if (fields[0] == "ngram_size")
ngram_size = lexical_cast<int>(fields[1]);
else if (fields[0] == "vocab_size")
input_vocab_size = output_vocab_size = lexical_cast<int>(fields[1]);
else if (fields[0] == "input_vocab_size")
input_vocab_size = lexical_cast<int>(fields[1]);
else if (fields[0] == "output_vocab_size")
output_vocab_size = lexical_cast<int>(fields[1]);
else if (fields[0] == "input_embedding_dimension")
input_embedding_dimension = lexical_cast<int>(fields[1]);
else if (fields[0] == "num_hidden")
num_hidden = lexical_cast<int>(fields[1]);
else if (fields[0] == "output_embedding_dimension")
output_embedding_dimension = lexical_cast<int>(fields[1]);
else if (fields[0] == "activation_function")
activation_function = string_to_activation_function(fields[1]);
else if (fields[0] == "version")
{
int version = lexical_cast<int>(fields[1]);
if (version != 1)
{
cerr << "error: file format mismatch (expected 1, found " << version << ")" << endl;
exit(1);
}
}
else
cerr << "warning: unrecognized field in config: " << fields[0] << endl;
}
resize(ngram_size,
input_vocab_size,
output_vocab_size,
input_embedding_dimension,
num_hidden,
output_embedding_dimension);
set_activation_function(activation_function);
}
void ann::set_output_activation_function(int activation_function)
{
set_activation_function(activation_function, LAYER_OUTPUT);
}
void ann::set_hidden_activation_function(int activation_function)
{
set_activation_function(activation_function, LAYER_HIDDEN);
}
void ann::set_input_activation_function(int activation_function)
{
set_activation_function(activation_function, LAYER_INPUT);
}
void Perceptron::load(const char* filename)
{
std::fstream file;
file.open(filename, std::ios::in);
if(!file.is_open())
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Cannot open perceptron XML-type file." << std::endl;
exit(1);
}
std::string line;
std::string word;
// Declaration
getline(file, line);
if(line != "<Flood version='3.0' class='Perceptron'>")
{
// std::cerr << "Flood Error: Perceptron class." << std::endl
// << "void load(const char*) method." << std::endl
// << "Unknown file declaration: " << line << std::endl;
//
// exit(1);
}
// Number of inputs
file >> word;
if(word != "<InputsNumber>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown inputs number begin tag: " << line << std::endl;
exit(1);
}
int new_inputs_number;
file >> new_inputs_number;
set_inputs_number(new_inputs_number);
file >> word;
if(word != "</InputsNumber>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown inputs number end tag: " << line << std::endl;
exit(1);
}
// Activation function
file >> word;
if(word != "<ActivationFunction>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown activation function begin tag: " << line << std::endl;
exit(1);
}
std::string new_activation_function_name;
file >> new_activation_function_name;
set_activation_function(new_activation_function_name);
file >> word;
if(word != "</ActivationFunction>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown activation function end tag: " << line << std::endl;
exit(1);
}
// Bias
file >> word;
if(word != "<Bias>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown bias begin tag: " << line << std::endl;
exit(1);
}
double new_bias;
file >> new_bias;
set_bias(new_bias);
file >> word;
if(word != "</Bias>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown bias end tag: " << line << std::endl;
exit(1);
}
// Synaptic weights
file >> word;
if(word != "<SynapticWeights>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown synaptic weights begin tag: " << line << std::endl;
exit(1);
}
Vector<double> new_synaptic_weights(inputs_number);
file >> new_synaptic_weights;
set_synaptic_weights(new_synaptic_weights);
file >> word;
if(word != "</SynapticWeights>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown synaptic weights end tag: " << line << std::endl;
exit(1);
}
// Display
file >> word;
if(word != "<Display>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown display begin tag: " << line << std::endl;
exit(1);
}
bool new_display;
file >> new_display;
set_display(new_display);
file >> word;
if(word != "</Display>")
{
std::cerr << "Flood Error: Perceptron class." << std::endl
<< "void load(const char*) method." << std::endl
<< "Unknown display end tag: " << line << std::endl;
exit(1);
}
file.close();
}
