alibi_detect.od.pytorch.base

TorchOutlierDetector

Inherits from: Module, FitMixinTorch, ABC

Base class for torch backend outlier detection algorithms.

Constructor

TorchOutlierDetector(self, device: Union[typing_extensions.Literal['cuda', 'gpu', 'cpu'], ForwardRef('torch.device'), NoneType] = None)

Name	Type	Default	Description
device	Union[Literal[cuda, gpu, cpu], torch.device, None]	None

Methods

check_threshold_inferred

check_threshold_inferred()

Check if threshold is inferred.

infer_threshold

infer_threshold(x: torch.Tensor, fpr: float)

Infer the threshold for the data. Prerequisite for outlier predictions.

Name	Type	Default	Description
x	torch.Tensor		Data to infer the threshold for.
fpr	float		False positive rate to use for threshold inference.

predict

predict(x: torch.Tensor) -> alibi_detect.od.pytorch.base.TorchOutlierDetectorOutput

Predict outlier labels for the data.

Computes the outlier scores. If the detector is not fit on reference data we raise an error. If the threshold is inferred, the outlier labels and p-values are also computed and returned. Otherwise, the outlier labels and p-values are set to None.

Name	Type	Default	Description
x	torch.Tensor		Data to predict.

Returns

• Type: alibi_detect.od.pytorch.base.TorchOutlierDetectorOutput

score

score(x: torch.Tensor) -> torch.Tensor

Score the data.

Name	Type	Default	Description
x	torch.Tensor		Data to score.

Returns

• Type: torch.Tensor

TorchOutlierDetectorOutput

Output of the outlier detector.

Fields

Field	Type	Default
threshold_inferred	bool	``
instance_score	torch.Tensor	``
threshold	Optional[torch.Tensor]	``
is_outlier	Optional[torch.Tensor]	``
p_value	Optional[torch.Tensor]	``

Constructor

TorchOutlierDetectorOutput(self, threshold_inferred: bool, instance_score: torch.Tensor, threshold: Optional[torch.Tensor], is_outlier: Optional[torch.Tensor], p_value: Optional[torch.Tensor]) -> None

Name	Type	Default	Description
threshold_inferred	bool
instance_score	torch.Tensor
threshold	Optional[torch.Tensor]
is_outlier	Optional[torch.Tensor]
p_value	Optional[torch.Tensor]

Methods

to_frontend_dtype

to_frontend_dtype()

Functions

to_frontend_dtype

to_frontend_dtype(x: Union[torch.Tensor, alibi_detect.od.pytorch.base.TorchOutlierDetectorOutput]) -> Union[numpy.ndarray, Dict[str, numpy.ndarray]]

Converts any torch tensors found in input to numpy arrays.

Takes a torch tensor or TorchOutlierDetectorOutput and converts any torch tensors found to numpy arrays

Name	Type	Default	Description
x	Union[torch.Tensor, alibi_detect.od.pytorch.base.TorchOutlierDetectorOutput]		Data to convert.

Returns

• Type: Union[numpy.ndarray, Dict[str, numpy.ndarray]]