alibi_detect.od.pytorch.gmm

GMMTorch

Inherits from: TorchOutlierDetector, Module, FitMixinTorch, ABC

Constructor

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

Name	Type	Default	Description
n_components	int		Number of components in gaussian mixture model.
device	Union[Literal[cuda, gpu, cpu], torch.device, None]	None	Device type used. The default tries to use the GPU and falls back on CPU if needed. Can be specified by passing either 'cuda', 'gpu', 'cpu' or an instance of torch.device.

Methods

fit

fit(x_ref: torch.Tensor, optimizer: type[torch.optim.optimizer.Optimizer] = <class 'torch.optim.adam.Adam'>, learning_rate: float = 0.1, max_epochs: int = 10, batch_size: int = 32, tol: float = 0.001, n_iter_no_change: int = 25, verbose: int = 0) -> Dict

Fit the GMM model.

Name	Type	Default	Description
x_ref	torch.Tensor		Training data.
optimizer	type[torch.optim.optimizer.Optimizer]	<class 'torch.optim.adam.Adam'>	Optimizer used to train the model.
learning_rate	float	0.1	Learning rate used to train the model.
max_epochs	int	10	Maximum number of training epochs.
batch_size	int	32	Batch size used to train the model.
tol	float	0.001	Convergence threshold. Training iterations will stop when the lower bound average gain is below this threshold.
n_iter_no_change	int	25	The number of iterations over which the loss must decrease by tol in order for optimization to continue.
verbose	int	0	Verbosity level during training. 0 is silent, 1 a progress bar.

Returns

• Type: Dict

format_fit_kwargs

format_fit_kwargs(fit_kwargs: Dict) -> Dict

Format kwargs for fit method.

Name	Type	Default	Description
fit_kwargs	Dict
kwargs			dictionary of Kwargs to format. See fit method for details.

Returns

• Type: Dict

forward

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

Detect if x is an outlier.

Name	Type	Default	Description
x	torch.Tensor		torch.Tensor with leading batch dimension.

Returns

• Type: torch.Tensor

score

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

Computes the score of x

Name	Type	Default	Description
x	torch.Tensor		torch.Tensor with leading batch dimension.

Returns

• Type: torch.Tensor