def online_traning_api(input_file_name,model_id): print '%s' %settings.logging_file_training utils.setLog(settings.logging_file_training) logger=logging.getLogger('model-learner.train') #Log start of Full process utils.logInfoTime(logger, 'Started') # run hbc load data script logger.info('==> Load Data.') utils.logInfoTime(logger, 'Started Data Load') data_np_array, y_np_array = data_load_csv.csv_train_from_one_file(input_file_name); utils.logInfoTime(logger, 'Finished Data Load') # preprocessing featurizer sample data logger.info('==> Preprocessing feature data.') utils.logInfoTime(logger, 'Started Preprocessing') utils.logInfoTime(logger, 'Finished Preprocessing') # build models logger.info('==> Build Model.') utils.logInfoTime(logger, 'Started Model Building') model_building.modelsBuild(data_np_array, y_np_array,model_id,logger) utils.logInfoTime(logger, 'Finished Model Building') utils.logInfoTime(logger, 'Finished')
import datetime import data_load import data_preprocessing import model_building import utils import pprint as pp # to make log entries nicer to read # get the settings for the run import settings #Setup the logger utils.setLog(settings.LOGGING_FILE) logger=logging.getLogger('Master') #Log start of Full process utils.logInfoTime(logger, 'Started') # run data load script logger.info('--------------------------------- Data Load -----------------------------------') utils.logInfoTime(logger, 'Started Data Load') # initial_data = data_load.psqlLoad(settings.INPUT_TABLE, settings.INPUT_SCHEMA, columns='*') initial_data = data_load.csvfile(settings.INPUT_DIR, settings.file_name, settings.RESULTS_OUTPUT_DIR) utils.logInfoTime(logger, 'Finished Data Load') # run preprocessing script logger.info('--------------------------------- Data Preprocessing -----------------------------------') utils.logInfoTime(logger, 'Started Pre-Processing') data_np_array, y_np_array, var_results = data_preprocessing.main(initial_data) utils.logInfoTime(logger, 'Finished Pre-Processing')
def offline_train(): #Setup the logger print '%s' %settings.logging_file_training utils.setLog(settings.logging_file_training) logger=logging.getLogger('model-learner.train') #Log start of Full process utils.logInfoTime(logger, 'Started') # run hbc load data script logger.info('==> Load Data.') utils.logInfoTime(logger, 'Started Data Load') data_np_array, y_np_array = data_load_csv.csv_train_file(settings.INPUT_DIR, settings.train_file_name_white, settings.train_file_name_black) utils.logInfoTime(logger, 'Finished Data Load') # preprocessing featurizer sample data logger.info('==> Preprocessing feature data.') utils.logInfoTime(logger, 'Started Preprocessing') utils.logInfoTime(logger, 'Finished Preprocessing') # build models logger.info('==> Build Model.') utils.logInfoTime(logger, 'Started Model Building') model_building.modelsBuild(data_np_array, y_np_array, 'hbc_train_offline.model',logger) utils.logInfoTime(logger, 'Finished Model Building') utils.logInfoTime(logger, 'Finished') print('model training complete')