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hub / github.com/antmachineintelligence/mtgbmcode / InitTrain

Method InitTrain

src/application/application.cpp:166–201  ·  view source on GitHub ↗

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164}
165
166void Application::InitTrain() {
167 if (config_.is_parallel) {
168 // need init network
169 Network::Init(config_);
170 Log::Info("Finished initializing network");
171 config_.feature_fraction_seed =
172 Network::GlobalSyncUpByMin(config_.feature_fraction_seed);
173 config_.feature_fraction =
174 Network::GlobalSyncUpByMin(config_.feature_fraction);
175 config_.drop_seed =
176 Network::GlobalSyncUpByMin(config_.drop_seed);
177 }
178
179 // create boosting
180 boosting_.reset(
181 Boosting::CreateBoosting(config_.boosting,
182 config_.input_model.c_str()));
183 // create objective function
184 objective_fun_.reset(
185 ObjectiveFunction::CreateObjectiveFunction(config_.objective,
186 config_));
187 // load training data
188 LoadData();
189 // initialize the objective function
190 objective_fun_->Init(train_data_->metadata(), train_data_->num_data());
191 // initialize the boosting
192 boosting_->Init(&config_, train_data_.get(), objective_fun_.get(),
193 Common::ConstPtrInVectorWrapper<Metric>(train_metric_));
194 // add validation data into boosting
195 for (size_t i = 0; i < valid_datas_.size(); ++i) {
196 boosting_->AddValidDataset(valid_datas_[i].get(),
197 Common::ConstPtrInVectorWrapper<Metric>(valid_metrics_[i]));
198 Log::Debug("Number of data points in validation set #%zu: %zu", i + 1, valid_datas_[i]->num_data());
199 }
200 Log::Info("Finished initializing training");
201}
202
203void Application::Train() {
204 Log::Info("Started training...");

Callers

nothing calls this directly

Calls 6

resetMethod · 0.80
InitMethod · 0.45
num_dataMethod · 0.45
getMethod · 0.45
sizeMethod · 0.45
AddValidDatasetMethod · 0.45

Tested by

no test coverage detected