import gensim.downloader
import numpy as np

class Word2Vec():
    def __init__(self) -> None:
        pass

    def load(self):
        self.model = gensim.downloader.load('word2vec-google-news-300')

    def sentence2vec(self, sentence):
        return np.mean([self.model[word] if word in self.model else np.zeros(300) for word in sentence])

    def list_of_sentences2vec(self, sentences):
        return [self.sentence2vec(x) for x in sentences]