lm_polygraph.estimators.mahalanobis_distance module

class lm_polygraph.estimators.mahalanobis_distance.MahalanobisDistanceSeq(embeddings_type: str = 'decoder', parameters_path: str = None, normalize: bool = False)

Bases: Estimator

lm_polygraph.estimators.mahalanobis_distance.compute_inv_covariance(centroids, train_features, jitters=None)

This function computes inverse covariance matrix that is required by Mahalanobis distance: MD = sqrt((h(x) - mu)^{T} Sigma^{-1} (h(x) - mu))

lm_polygraph.estimators.mahalanobis_distance.create_cuda_tensor_from_numpy(array)

lm_polygraph.estimators.mahalanobis_distance.mahalanobis_distance_with_known_centroids_sigma_inv(centroids, centroids_mask, sigma_inv, eval_features)

• This function takes in centroids, centroids_mask, sigma_inv, and eval_features.

• tensor of Mahalanobis distances is returned.