SIF_Variant_5.pyx

def sif_embeddings(sentences, model):
    cdef int size = model.vector_size
    cdef float[:,:] vectors = model.wv.sif_vectors

    cdef int sentence_index, word_index, d, count = 0
    cdef float inv = 1.
    np_sum = np.sum
    
    output = np.zeros((len(sentences), size), dtype=np.float32)   
    cdef float[:,:] sv = output
    
    for sentence_index, sentence in enumerate(sentences):
        if len(sentence) > 0:
            count = 0
            for word_index in sentence:
                count += 1
                for d in range(size):
                    sv[sentence_index, d] += vectors[word_index, d]

            inv = (1./ <float>count)
            for d in range(size):
                sv[sentence_index, d] *= inv
    return output