Source code for fonduer.features.feature_extractors

from typing import Callable, Dict, Iterator, List, Tuple, Union

from fonduer.candidates.models import Candidate
from fonduer.features.feature_libs.structural_features import (
    extract_structural_features,
)
from fonduer.features.feature_libs.tabular_features import extract_tabular_features
from fonduer.features.feature_libs.textual_features import extract_textual_features
from fonduer.features.feature_libs.visual_features import extract_visual_features

FEATURES: Dict[str, Callable[[List[Candidate]], Iterator[Tuple[int, str, int]]]] = {
    "textual": extract_textual_features,
    "structural": extract_structural_features,
    "tabular": extract_tabular_features,
    "visual": extract_visual_features,
}


[docs]class FeatureExtractor(object): """A class to extract features from candidates. :param features: a list of which Fonduer feature types to extract, defaults to ["textual", "structural", "tabular", "visual"] :type features: list, optional :param customize_feature_funcs: a list of customized feature extractors where the extractor takes a list of candidates as input and yield tuples of (candidate_id, feature, value), defaults to [] :type customize_feature_funcs: list, optional """ def __init__( self, features: List[str] = ["textual", "structural", "tabular", "visual"], customize_feature_funcs: List[ Callable[[List[Candidate]], Iterator[Tuple[int, str, int]]] ] = [], ) -> None: if not isinstance(customize_feature_funcs, list): customize_feature_funcs = [customize_feature_funcs] self.feature_extractors: List[ Callable[[List[Candidate]], Iterator[Tuple[int, str, int]]] ] = [] for feature in features: if feature not in FEATURES: raise ValueError(f"Unrecognized feature type: {feature}") self.feature_extractors.append(FEATURES[feature]) self.feature_extractors.extend(customize_feature_funcs)
[docs] def extract( self, candidates: Union[List[Candidate], Candidate] ) -> Iterator[Tuple[int, str, int]]: """Extract features from candidates. :param candidates: A list of candidates to extract features from :type candidates: list """ candidates = candidates if isinstance(candidates, list) else [candidates] for feature_extractor in self.feature_extractors: for candidate_id, feature, value in feature_extractor(candidates): yield candidate_id, feature, value