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_dataset = load_settings_file(args.config_file_dataset)
settings_features = load_settings_file(args.config_file_features)
main_logger.info('Settings loaded')
if settings_dataset['workflow']['create_dataset']:
main_logger.info('Starting Clotho dataset creation')
create_dataset(settings_dataset)
main_logger.info('Dataset created')
if settings_dataset['workflow']['extract_features']:
main_logger.info('Starting Clotho feature extraction')
extract_features(settings_dataset, settings_features)
main_logger.info('Features extracted')
def do_process(settings_path=None, settings=None, use_tf=False):
"""The process of the experiment for the proposed method.
:param settings_path: The path for the settings.
:type settings_path: str|None
:param settings: The settings to be used.
:type settings: dict|None
:param use_tf: Do we use teacher forcing?
:type use_tf: bool
:param use_tf: Do we use teacher forcing?
:type use_tf: bool
"""
if settings_path is not None:
settings = load_settings_file(settings_path)
model = TFCRNN if use_tf else CRNN
if not use_tf:
print_msg('Baseline experiment')
print_msg('Starting experiment with folds', end='\n\n')
p_print = partial(print_msg,
decorate_prv='*',
decorate_nxt='*',
end='\n\n')
for i in range(2, 4):
settings['data_loader'].update({'data_fold': i + 1})
p_print('Fold {}'.format(i + 1))
experiment(settings, model, use_tf=use_tf)
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 do_process(settings_path=None, settings=None):
"""The process of the baseline experiment.
:param settings_path: The path for the settings.
:type settings_path: str|None
:param settings: The settings.
:type settings: dict|None
"""
if settings_path is not None:
settings = load_settings_file(settings_path)
print_msg('Starting baseline experiment', end='\n\n')
experiment(settings, CRNN)
def main():
"""Main entry point for the project.
"""
print_date_and_time()
arg_parser = get_argument_parser()
args = arg_parser.parse_args()
experiment_process = baseline if args.baseline else tf_process
settings = load_settings_file(args.config_file)
print_yaml_settings(settings)
experiment_process(settings=settings)
def main():
"""Main entry point for the project.
"""
print_date_and_time()
arg_parser = get_argument_parser()
args = arg_parser.parse_args()
settings = load_settings_file(args.config_file)
print_yaml_settings(settings)
experiment_process = with_folds_process if settings['global']['has_folds'] \
else no_folds_process
experiment_process(settings=settings, use_tf=not args.baseline)
def main():
args = get_argument_parser().parse_args()
model_to_use = args.model
config_file = args.config_file
file_ext = args.file_ext
settings_dir = args.file_dir
date_and_time()
with InformAboutProcess('Loading settings'):
settings = load_settings_file(
file_name=Path(f'{config_file}{file_ext}'),
settings_dir=Path(settings_dir))
do_process(settings_path=None,
settings=settings,
model_to_use=model_to_use)
def do_process(settings_path=None, settings=None):
"""The process of the experiment for the proposed method.
:param settings_path: The path for the settings.
:type settings_path: str|None
:param settings: The settings to be used.
:type settings: dict|None
"""
if settings_path is not None:
settings = load_settings_file(settings_path)
print_msg('Starting teacher forcing experiment', end='\n\n')
p_print = partial(print_msg, decorate_prv='*', decorate_nxt='*', end='\n\n')
for i in range(4):
settings['data_loader'].update({'data_fold': i + 1})
p_print('Fold {}'.format(i + 1))
experiment(settings, TFCRNN)
def do_process(settings_path=None, settings=None, use_tf=False):
"""The process of the baseline experiment.
:param settings_path: The path for the settings.
:type settings_path: str|None
:param settings: The settings.
:type settings: dict|None
:param use_tf: Do we use teacher forcing?
:type use_tf: bool
"""
if settings_path is not None:
settings = load_settings_file(settings_path)
model = TFCRNN if use_tf else CRNN
if not use_tf:
print_msg('Baseline experiment')
print_msg('Starting experiment without folds', end='\n\n')
experiment(settings, model, use_tf=use_tf)
def do_process(settings_path: Optional[Union[Path, None]] = None,
settings: Optional[Union[MutableMapping, None]] = None,
model_to_use: Optional[Union[str, None]] = None) \
-> None:
"""The process of the baseline experiment.
:param settings_path: Path for the settings. Defaults to None.
:type settings_path: str|None, optional
:param settings: Settings. Defaults to None.
:type settings: dict|None, optional
:param model_to_use: Model to use. Defaults to None.
:type model_to_use: str, optional
"""
if settings_path is not None:
settings = load_settings_file(Path(f'{settings_path}.yaml'))
if model_to_use == 'baseline':
msg = 'Baseline experiment'
model = CRNN
elif model_to_use == 'baseline_dilated':
msg = 'Baseline with dilated convolutions experiment'
model = BaselineDilated
elif model_to_use == 'dessed':
msg = 'Depth-wise separable with RNN experiment'
model = DESSED
elif model_to_use == 'dessed_dilated':
msg = 'Depth-wise separable with dilated convolutions experiment'
model = DESSEDDilated
else:
raise AttributeError(f'Unrecognized model `{model_to_use}`. '
f'Accepted model names are: `baseline`, '
'`baseline_dilated`, `dessed`, '
'`dessed_dilated`.')
cmd_msg(msg, start='\n-- ')
model_settings = settings[model_to_use]
cmd_msg('Starting experiment', end='\n\n')
experiment(settings=settings,
model_settings=model_settings,
model_class=model)