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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_word_vectors(vocab):
 """ Create a word2vec embedding matrix for all the words in the vocab """

    wv = get_data('word2vec')
    vectors = np.array(len(vocab), len(wv['the']))
    for i, tok in enumerate(vocab):
        word = tok[0]
        variations = (word, word.lower(), word.lower()[:-1])
        for w in variations:
            if w in wv:
                vectors[i, :] = wv[w]
        if not np.sum(np.abs(vectors[i])):
            logger.warning('Unable to find {}, {}, or {} in word2vec.'.format(*variations))
    return vectors