__fastcall TNeyron::TNeyron(TIniFile* F, AnsiString SectionName, vector<TNeyron*> &Layer) { int cnt_inputs = F->ReadInteger( SectionName, "SYNAPSES", 0); w.resize(cnt_inputs); s.resize(cnt_inputs); sn.resize(cnt_inputs); LoadWeights(F, SectionName); LoadSynapses(F, SectionName, Layer); }
void LogLinearModel::Init (String _sName) { d_LearningRate = (config)(_sName + ":learning_rate"); d_RegularizationFactor = (config)(_sName + ":regularization_factor"); if (1 == (int)(config)(_sName + ":load_weights")) LoadWeights (_sName); else if (true == Path::Exists ((config)(_sName + ":weights_file"))) Path::RemoveFile ((config)(_sName + ":weights_file")); d_MaxWeightCeiling = (config)(_sName + ":max_weight_ceiling"); cout << "Initializing log-linear model (" << _sName << ')' << endl; cout << " Learning rate : " << d_LearningRate << endl; cout << " Regularization : " << d_RegularizationFactor << endl; }