def get_config(
config_paths: Optional[Union[List[str], str]] = None,
opts: Optional[list] = None,
) -> CN:
r"""Create a unified config with default values overwritten by values from
:p:`config_paths` and overwritten by options from :p:`opts`.
:param config_paths: List of config paths or string that contains comma
separated list of config paths.
:param opts: Config options (keys, values) in a list (e.g., passed from
command line into the config. For example,
:py:`opts = ['FOO.BAR', 0.5]`. Argument can be used for parameter
sweeping or quick tests.
"""
config = _C.clone()
if config_paths:
if isinstance(config_paths, str):
if CONFIG_FILE_SEPARATOR in config_paths:
config_paths = config_paths.split(CONFIG_FILE_SEPARATOR)
else:
config_paths = [config_paths]
for config_path in config_paths:
config.merge_from_file(config_path)
if opts:
config.merge_from_list(opts)
config.freeze()
return config
def update_config(config: yacs.config.CfgNode) -> None:
if config.mode == 'MPIIGaze':
_set_eye_default_camera(config)
elif config.mode == 'MPIIFaceGaze':
_set_face_default_camera(config)
else:
raise ValueError
_update_camera_config(config)
_download_dlib_pretrained_model(config)
_expanduser_all(config)
_check_path_all(config)
config.freeze()
def get_config(
config_paths: Optional[Union[List[str], str]] = None,
opts: Optional[list] = None,
) -> CN:
r"""Create a unified config with default values overwritten by values from
:p:`config_paths` and overwritten by options from :p:`opts`.
:param config_paths: List of config paths or string that contains comma
separated list of config paths.
:param opts: Config options (keys, values) in a list (e.g., passed from
command line into the config. For example,
:py:`opts = ['FOO.BAR', 0.5]`. Argument can be used for parameter
sweeping or quick tests.
"""
config = _C.clone()
if config_paths:
if isinstance(config_paths, str):
if CONFIG_FILE_SEPARATOR in config_paths:
config_paths = config_paths.split(CONFIG_FILE_SEPARATOR)
else:
config_paths = [config_paths]
for config_path in config_paths:
config.merge_from_file(config_path)
if opts:
config.merge_from_list(opts)
# multi-task handling
# list of tasks to list of config nodes, levaraging `TASK` default values
tasks = []
for task in config.MULTI_TASK.TASKS:
# get default values
t = _C.TASK.clone()
task = CN(init_dict=task)
# each task can now have a different dataset, if unspecified the global one is used
t.DATASET = config.DATASET.clone()
# same thing for the episode iterator
t.EPISODE_ITERATOR_OPTIONS = (
config.ENVIRONMENT.ITERATOR_OPTIONS.clone()
)
t.merge_from_other_cfg(task)
tasks.append(t)
config.MULTI_TASK.TASKS = tasks
config.freeze()
return config
def load_config() -> yacs.config.CfgNode:
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str)
parser.add_argument('options', default=None, nargs=argparse.REMAINDER)
args = parser.parse_args()
config = get_default_config()
if args.config is not None:
config.merge_from_file(args.config)
config.merge_from_list(args.options)
if not torch.cuda.is_available():
config.device = 'cpu'
config.train.train_dataloader.pin_memory = False
config.train.val_dataloader.pin_memory = False
config.test.dataloader.pin_memory = False
config.freeze()
return config
def update_config(config: yacs.config.CfgNode) -> None:
_update_camera_config(config)
_download_dlib_pretrained_model(config)
_expanduser_all(config)
_check_path_all(config)
config.freeze()
