VIB/utils.py at master · grvmishra788/VIB · GitHub

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from sklearn.decomposition import PCA
from vectors import compute_weat_score


def process_seedwords(seedword_string):
    return [seedword.strip() for seedword in seedword_string.split(',')]


def make_projector(method='PCA'):
    if method == 'PCA':
        projector = PCA(n_components=2)
    else:
        raise AttributeError('Unknown method type for dimensionality reduction')
    return projector


def get_weat_score(embedding, seedwords1, seedwords2, male_words, female_words):
    return compute_weat_score(embedding, male_words, female_words, seedwords1, seedwords2)


def project_to_2d(projector, embedding, wordlist):
    return projector.transform(embedding.get_many(wordlist)).tolist()