foolbox.models

Models

Model
PyTorchModel
TensorFlowModel
JAXModel
NumPyModel

Wrappers

TransformBoundsWrapper

Detailed description

class foolbox.models.Model

transform_bounds(bounds)

Returns a new model with the desired bounds and updates the preprocessing accordingly

Parameters

bounds (Union[foolbox.types.Bounds, Tuple[float, float]]) –

Return type

foolbox.models.base.Model

class foolbox.models.PyTorchModel(model, bounds, device=None, preprocessing=None)

Parameters

• model (Any) –

• bounds (Union[foolbox.types.Bounds, Tuple[float, float]]) –

• device (Any) –

• preprocessing (Optional[Dict[str, Any]]) –

class foolbox.models.TensorFlowModel(model, bounds, device=None, preprocessing=None)

Parameters

• model (Any) –

• bounds (Union[foolbox.types.Bounds, Tuple[float, float]]) –

• device (Any) –

• preprocessing (Optional[Dict[str, Any]]) –

class foolbox.models.JAXModel(model, bounds, preprocessing=None, data_format='channels_last')

Parameters

• model (Any) –

• bounds (Union[foolbox.types.Bounds, Tuple[float, float]]) –

• preprocessing (Optional[Dict[str, Any]]) –

• data_format (Optional[str]) –

class foolbox.models.NumPyModel(model, bounds, data_format=None)

Parameters

• model (Callable) –

• bounds (Union[foolbox.types.Bounds, Tuple[float, float]]) –

• data_format (Optional[str]) –

class foolbox.models.TransformBoundsWrapper(model, bounds)

Parameters

• model (foolbox.models.base.Model) –

• bounds (Union[foolbox.types.Bounds, Tuple[float, float]]) –

transform_bounds(bounds, inplace=False)

Returns a new model with the desired bounds and updates the preprocessing accordingly

Parameters

• bounds (Union[foolbox.types.Bounds, Tuple[float, float]]) –

• inplace (bool) –

Return type

foolbox.models.base.Model