alibi_detect.utils.pytorch.misc module

alibi_detect.utils.pytorch.misc.get_device(device=None)[source]

Instantiates a PyTorch device object.

Parameters:: device (Union[Literal[‘cuda’, ‘gpu’, ‘cpu’], device, None]) – Either None, a str (‘gpu’, ‘cuda’ or ‘cpu’) indicating the device to choose, or an already instantiated device object. If None, the GPU is selected if it is detected, otherwise the CPU is used as a fallback.
Return type:: device
Returns:: The instantiated device object.

alibi_detect.utils.pytorch.misc.get_optimizer(name='Adam')[source]

Get an optimizer class from its name.

alibi_detect.utils.pytorch.misc.quantile(sample, p, type=7, sorted=False)[source]

Estimate a desired quantile of a univariate distribution from a vector of samples

Parameters:

sample (Tensor) – A 1D vector of values
p (float) – The desired quantile in (0,1)
type (int) – The method for computing the quantile. See https://wikipedia.org/wiki/Quantile#Estimating_quantiles_from_a_sample
sorted (bool) – Whether or not the vector is already sorted into ascending order

Return type:

float

Returns:

An estimate of the quantile

alibi_detect.utils.pytorch.misc.zero_diag(mat)[source]

Set the diagonal of a matrix to 0