quaterion.eval.samplers.group_sampler module

class GroupSampler(sample_size=- 1, encode_batch_size=16, device: Optional[Union[device, str]] = None, log_progress: bool = True)

Bases: BaseSampler

Perform selection of embeddings and targets for group based tasks.

accumulate(model: SimilarityModel, dataset: Union[Sized, Iterable, Dataset])

Encodes objects and accumulates embeddings with the corresponding raw labels

Parameters:

• model – model to encode objects

• dataset – Sized object, like list, tuple, torch.utils.data.Dataset, etc. to accumulate

reset()

Reset accumulated state

sample(dataset: Sized, metric: GroupMetric, model: SimilarityModel) → Tuple[Tensor, Tensor]

Sample embeddings and targets for groups based tasks.

Parameters:

• dataset – Sized object, like list, tuple, torch.utils.data.Dataset, etc. to sample

• metric – GroupMetric instance to compute final labels representation

• model – model to encode objects

Returns:

torch.Tensor, torch.Tensor – metrics labels and computed distance matrix