foolbox.models
Models
Wrappers
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
- 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