capreolus.sampler

Package Contents

Classes

TrainDataset(qid_docid_to_rank, qrels, extractor, relevance_level=1)	Samples training data. Intended to be used with a pytorch DataLoader
PredDataset(qid_docid_to_rank, extractor)	Creates a Dataset for evaluation (test) data to be used with a pytorch DataLoader

capreolus.sampler.logger

class capreolus.sampler.TrainDataset(qid_docid_to_rank, qrels, extractor, relevance_level=1)

Bases: torch.utils.data.IterableDataset

Samples training data. Intended to be used with a pytorch DataLoader

get_hash(self)

get_total_samples(self)

generator_func(self)

class capreolus.sampler.PredDataset(qid_docid_to_rank, extractor)

Bases: torch.utils.data.IterableDataset

Creates a Dataset for evaluation (test) data to be used with a pytorch DataLoader

get_hash(self)

get_qid_docid_pairs(self)

Returns a generator for the (qid, docid) pairs. Useful if you want to sequentially access the pred pairs without extracting the actual content