alibi_detect.models.tensorflow.gmm module
- alibi_detect.models.tensorflow.gmm.gmm_energy(z, phi, mu, cov, L, log_det_cov, return_mean=True)[source]
Compute sample energy from Gaussian Mixture Model.
- Parameters:
z (
Tensor
) – Observations.phi (
Tensor
) – Mixture component distribution weights.mu (
Tensor
) – Mixture means.cov (
Tensor
) – Mixture covariance.L (
Tensor
) – Cholesky decomposition of cov.log_det_cov (
Tensor
) – Log of the determinant of cov.return_mean (
bool
) – Take mean across all sample energies in a batch.
- Return type:
Tuple
[Tensor
,Tensor
]- Returns:
sample_energy – The sample energy of the GMM.
cov_diag – The inverse sum of the diagonal components of the covariance matrix.
- alibi_detect.models.tensorflow.gmm.gmm_params(z, gamma)[source]
Compute parameters of Gaussian Mixture Model.
- Parameters:
z (
Tensor
) – Observations.gamma (
Tensor
) – Mixture probabilities to derive mixture distribution weights from.
- Return type:
Tuple
[Tensor
,Tensor
,Tensor
,Tensor
,Tensor
]- Returns:
phi – Mixture component distribution weights.
mu – Mixture means.
cov – Mixture covariance.
L – Cholesky decomposition of cov.
log_det_cov – Log of the determinant of cov.