OOD_AE#

class dataeval.detectors.ood.OOD_AE(model: Module, device: str | device | None = None)#

Autoencoder based out-of-distribution detector.

Parameters:

model (AriaAutoencoder) – An Autoencoder model.

fit(x_ref: ArrayLike, threshold_perc: float, loss_fn: Callable[[...], Module] | None = None, optimizer: Optimizer | None = None, epochs: int = 20, batch_size: int = 64, verbose: bool = False) → None#

Train the model and infer the threshold value.

Parameters:

  • x_ref (ArrayLike) – Training data.

  • threshold_perc (float, default 100.0) – Percentage of reference data that is normal.

  • loss_fn (Callable | None, default None) – Loss function used for training.

  • optimizer (Optimizer, default keras.optimizers.Adam) – Optimizer used for training.

  • epochs (int, default 20) – Number of training epochs.

  • batch_size (int, default 64) – Batch size used for training.

  • verbose (bool, default True) – Whether to print training progress.

predict(X: ArrayLike, batch_size: int = 10000000000, ood_type: Literal['feature', 'instance'] = 'instance') → OODOutput#

Predict whether instances are out of distribution or not.

Parameters:

  • X (ArrayLike) – Input data for out-of-distribution prediction.

  • batch_size (int, default 1e10) – Number of instances to process in each batch.

  • ood_type ("feature" | "instance", default "instance") – Predict out-of-distribution at the ‘feature’ or ‘instance’ level.

Returns:

  • Dictionary containing the outlier predictions for the selected level,

  • and the OOD scores for the data including both ‘instance’ and ‘feature’ (if present) level scores.

score(X: ArrayLike, batch_size: int = 10000000000) → OODScoreOutput#

Compute the out of distribution scores for a given dataset.

Parameters:

  • X (ArrayLike) – Input data to score.

  • batch_size (int, default 1e10) – Number of instances to process in each batch. Use a smaller batch size if your dataset is large or if you encounter memory issues.

Returns:

An object containing the instance-level and feature-level OOD scores.

Return type:

OODScoreOutput