def main(): args = get_argument_parser().parse_args() file_dir = args.file_dir config_file = args.config_file file_ext = args.file_ext verbose = args.verbose # Load settings file. settings = load_yaml_file(Path(file_dir, f'{config_file}.{file_ext}')) init_loggers(verbose=verbose, settings=settings['dirs_and_files']) logger_main = logger.bind(is_caption=False, indent=0) logger_sec = logger.bind(is_caption=False, indent=1) logger_main.info(datetime.now().strftime('%Y-%m-%d %H:%M')) logger_main.info('Doing only dataset creation') # Create the dataset. logger_main.info('Starting Clotho dataset creation') logger_sec.info('Creating examples') create_dataset(settings_dataset=settings['dataset_creation_settings'], settings_dirs_and_files=settings['dirs_and_files']) logger_sec.info('Examples created') logger_sec.info('Extracting features') extract_features(root_dir=settings['dirs_and_files']['root_dirs']['data'], settings_data=settings['dirs_and_files']['dataset'], settings_features=settings['feature_extraction_settings']) logger_sec.info('Features extracted') logger_main.info('Dataset created')
def main(): logger.remove() logger.add(stdout, format='{level} | [{time:HH:mm:ss}] {name} -- {message}.', level='INFO', filter=lambda record: record['extra']['indent'] == 1) logger.add(stdout, format=' {level} | [{time:HH:mm:ss}] {name} -- {message}.', level='INFO', filter=lambda record: record['extra']['indent'] == 2) main_logger = logger.bind(indent=1) args = get_argument_parser().parse_args() if not args.verbose: main_logger.info('Verbose if off. Not logging messages') logger.disable('__main__') logger.disable('processes') main_logger.info(datetime.now().strftime('%Y-%m-%d %H:%M')) main_logger.info('Loading settings') settings = load_settings_file(args.config_file) settings_dataset = settings['dataset_creation_settings'] settings_files_io = settings['dirs_and_files'] main_logger.info('Settings loaded') main_logger.info('Starting Clotho dataset creation') create_dataset( settings_dataset=settings_dataset, settings_dirs_and_files=settings_files_io) main_logger.info('Dataset created')
def main(): args = get_argument_parser().parse_args() file_dir = args.file_dir config_file = args.config_file file_ext = args.file_ext verbose = args.verbose settings = load_yaml_file(Path(file_dir, f'{config_file}.{file_ext}')) init_loggers(verbose=verbose, settings=settings['dirs_and_files']) logger_main = logger.bind(is_caption=False, indent=0) logger_inner = logger.bind(is_caption=False, indent=1) if settings['workflow']['dataset_creation']: logger_main.info('Starting creation of dataset') logger_inner.info('Creating examples') dataset_multiprocess.create_dataset( settings_dataset=settings['dataset_creation_settings'], settings_dirs_and_files=settings['dirs_and_files']) logger_inner.info('Examples created') logger_inner.info('Extracting features') dataset_multiprocess.extract_features( root_dir=settings['dirs_and_files']['root_dirs']['data'], settings_data=settings['dirs_and_files']['dataset'], settings_features=settings['feature_extraction_settings']) logger_inner.info('Features extracted') logger_main.info('Creation of dataset ended')
def main(): # Treat the logging. logger.remove() logger.add(stdout, format='{level} | [{time:HH:mm:ss}] {name} -- {message}.', level='INFO', filter=lambda record: record['extra']['indent'] == 1) logger.add(stdout, format=' {level} | [{time:HH:mm:ss}] {name} -- {message}.', level='INFO', filter=lambda record: record['extra']['indent'] == 2) main_logger = logger.bind(indent=1) args = get_argument_parser().parse_args() main_logger.info('Doing only dataset creation') # Check for verbosity. if not args.verbose: main_logger.info('Verbose if off. Not logging messages') logger.disable('__main__') logger.disable('processes') main_logger.info(datetime.now().strftime('%Y-%m-%d %H:%M')) # Load settings file. main_logger.info('Loading settings') settings = load_settings_file(args.config_file_dataset) main_logger.info('Settings loaded') # Create the dataset. main_logger.info('Starting Clotho dataset creation') create_dataset(settings) main_logger.info('Dataset created')
def main(): args = get_argument_parser().parse_args() file_dir = args.file_dir config_file = args.config_file file_ext = args.file_ext verbose = args.verbose settings = load_yaml_file(Path( file_dir, f'{config_file}.{file_ext}')) init_loggers(verbose=verbose, settings=settings['dirs_and_files']) logger_main = logger.bind(is_caption=False, indent=0) logger_inner = logger.bind(is_caption=False, indent=1) if settings['workflow']['dataset_creation']: logger_main.info('Starting creation of dataset') logger_inner.info('Creating examples') dataset.create_dataset( settings_dataset=settings['dataset_creation_settings'], settings_dirs_and_files=settings['dirs_and_files']) logger_inner.info('Examples created') logger_inner.info('Extracting features') dataset.extract_features( root_dir=settings['dirs_and_files']['root_dirs']['data'], settings_data=settings['dirs_and_files']['dataset'], settings_features=settings['feature_extraction_settings']) logger_inner.info('Features extracted') logger_main.info('Creation of dataset ended') if settings['workflow']['dnn_testing']: # Create test dataset if not yet created test_split_feat_dir = Path(settings['dirs_and_files']['root_dirs']['data']) \ .joinpath(settings['dirs_and_files']['dataset']['features_dirs']['output'], settings['dirs_and_files']['dataset']['features_dirs']['test']) if not test_split_feat_dir.exists(): logger_main.info('Starting creation of test dataset') logger_inner.info('Extracting features') dataset.extract_features_test( root_dir=settings['dirs_and_files']['root_dirs']['data'], settings_data=settings['dirs_and_files']['dataset'], settings_features=settings['feature_extraction_settings'], settings_audio=settings['dataset_creation_settings']['audio']) logger_inner.info('Features extracted') logger_main.info('Creation of test dataset ended') else: logger_inner.info('Found existing test data') if settings['workflow']['dnn_training'] or \ settings['workflow']['dnn_evaluation'] or \ settings['workflow']['dnn_testing']: method.method(settings)
def main(): args = get_argument_parser().parse_args() file_dir = args.file_dir config_file = args.config_file file_ext = args.file_ext verbose = args.verbose settings = load_yaml_file(Path(file_dir, f'{config_file}.{file_ext}')) init_loggers(verbose=verbose, settings=settings['logging']) method.method(settings)
def main(): args = get_argument_parser().parse_args() file_dir = args.file_dir config_file = args.config_file file_ext = args.file_ext verbose = args.verbose job_id = args.job_id settings = load_yaml_file(Path(file_dir, f'{config_file}.{file_ext}')) init_loggers(verbose=verbose, settings=settings['dirs_and_files'], job_id=job_id) method.method(settings, job_id)
def main(): args = get_argument_parser().parse_args() file_dir = args.file_dir config_file = args.config_file file_ext = args.file_ext verbose = args.verbose settings = file_io.load_yaml_file( Path(file_dir, f'{config_file}.{file_ext}')) printing.init_loggers(verbose=verbose, settings=settings['dirs_and_files']) logger_main = logger.bind(is_caption=False, indent=0) logger_main.info('Starting method only') method(settings) logger_main.info('Method\'s done')
batch_size = 16 nhead = 4 nhid = 192 nlayers = 2 ninp = 64 ntoken = 4367 + 1 clip_grad = 2.5 lr = 3e-4 # learning rate beam_width = 3 training_epochs = 50 log_interval = 100 checkpoint_save_interval = 5 device = torch.device('cuda:0') args = get_argument_parser().parse_args() file_dir = args.file_dir config_file = args.config_file file_ext = args.file_ext verbose = args.verbose print("load settings start") settings = load_yaml_file(Path(file_dir, f'{config_file}.{file_ext}')) settings_training = settings['dnn_training_settings']['training'], settings_data = settings['dnn_training_settings']['data'], settings_io = settings['dirs_and_files'] indices_list = _load_indices_file(