def create(model_name: str = None,
model: Union[str, ImageModel] = None,
folder_path: str = None,
dataset_name: str = None,
dataset: Union[str, ImageSet] = None,
config: Config = config,
class_dict: dict[str, type[ImageModel]] = class_dict,
**kwargs) -> ImageModel:
dataset_name = get_name(name=dataset_name,
module=dataset,
arg_list=['-d', '--dataset'])
model_name = get_name(name=model_name,
module=model,
arg_list=['-m', '--model'])
if dataset_name is None:
dataset_name = config.get_full_config()['dataset']['default_dataset']
if model_name is None:
model_name = config.get_config(
dataset_name=dataset_name)['model']['default_model']
result = config.get_config(
dataset_name=dataset_name)['model']._update(kwargs)
model_name = model_name if model_name is not None else result[
'default_model']
ModelType: type[ImageModel] = class_dict[get_model_class(model_name)]
if folder_path is None and isinstance(dataset, ImageSet):
folder_path = os.path.join(result['model_dir'], dataset.data_type,
dataset.name)
return ModelType(name=model_name,
dataset=dataset,
folder_path=folder_path,
**result)
def create(mark_path: str = None, data_shape: list[int] = None,
dataset_name: str = None, dataset: str | ImageSet = None,
config: Config = config, **kwargs) -> Watermark:
r"""
| Create a watermark instance.
| For arguments not included in :attr:`kwargs`,
use the default values in :attr:`config`.
| For watermark implementation, see :class:`Watermark`.
Args:
mark_path (str):
| Path to watermark image or npy file.
There are some preset marks in the package.
| Defaults to ``'square_white.png'``.
data_shape (list[int]): The shape of image data ``[C, H, W]``.
dataset_name (str): The dataset name.
dataset (str): The alias of `dataset_name`.
config (Config): The default parameter config.
**kwargs: Keyword arguments
passed to dataset init method.
Returns:
Watermark: Watermark instance.
"""
if data_shape is None:
assert isinstance(dataset, ImageSet), 'Please specify data_shape or dataset'
data_shape = dataset.data_shape
if dataset_name is None and dataset is not None:
dataset_name = dataset.name
result = config.get_config(dataset_name=dataset_name)[
'mark'].update(kwargs).update(mark_path=mark_path)
return Watermark(data_shape=data_shape, **result)
def create(model_name: str = None,
model: Union[str, ImageModel] = None,
layer: int = None,
dataset_name: str = None,
dataset: Union[str, ImageSet] = None,
config: Config = config,
class_dict: dict[str, type[ImageModel]] = class_dict,
**kwargs) -> ImageModel:
dataset_name = get_name(name=dataset_name,
module=dataset,
arg_list=['-d', '--dataset'])
if dataset_name is None:
dataset_name = config.get_full_config()['dataset']['default_dataset']
model_name = get_name(name=model_name,
module=model,
arg_list=['-m', '--model'])
if model_name is None:
model_name = config.get_config(
dataset_name=dataset_name)['model']['default_model']
model_name, layer = split_name(model_name, layer=layer)
return trojanzoo.models.create(model_name=model_name,
model=model,
dataset_name=dataset_name,
dataset=dataset,
config=config,
class_dict=class_dict,
layer=layer,
**kwargs)
def create(data_shape=None, dataset_name: str = None, dataset: ImageSet = None,
config: Config = config, **kwargs):
if data_shape is None:
assert isinstance(dataset, ImageSet)
data_shape: list = [dataset.n_channel]
data_shape.extend(dataset.n_dim)
if dataset_name is None and dataset is not None:
dataset_name = dataset.name
result = config.get_config(dataset_name=dataset_name)['mark']._update(kwargs)
return Watermark(data_shape=data_shape, **result)
def create(mark_path: str = None,
data_shape: list[int] = None,
dataset_name: str = None,
dataset: ImageSet = None,
config: Config = config,
**kwargs):
if data_shape is None:
assert isinstance(dataset, ImageSet)
data_shape = dataset.data_shape
if dataset_name is None and dataset is not None:
dataset_name = dataset.name
result = config.get_config(
dataset_name=dataset_name)['mark']._update(kwargs)
result.update(mark_path=mark_path)
return Watermark(data_shape=data_shape, **result)
def add_argument(
parser: argparse.ArgumentParser,
model_name: str = None,
model: Union[str, ImageModel] = None,
config: Config = config,
class_dict: dict[str, type[ImageModel]] = class_dict
) -> argparse._ArgumentGroup:
dataset_name = get_name(arg_list=['-d', '--dataset'])
if dataset_name is None:
dataset_name = config.get_full_config()['dataset']['default_dataset']
model_name = get_name(name=model_name,
module=model,
arg_list=['-m', '--model'])
if model_name is None:
model_name = config.get_config(
dataset_name=dataset_name)['model']['default_model']
model_name = get_model_class(model_name)
return trojanzoo.models.add_argument(parser=parser,
model_name=model_name,
model=model,
config=config,
class_dict=class_dict)
