Function main

rnn_class/visualize_embeddings.py:16–28

(we_file='word_embeddings.npy', w2i_file='wikipedia_word2idx.json', Model=PCA)

from sklearn.decomposition import PCA, TruncatedSVD

def main(we_file='word_embeddings.npy', w2i_file='wikipedia_word2idx.json', Model=PCA):
    We = np.load(we_file)
    V, D = We.shape
    with open(w2i_file) as f:
        word2idx = json.load(f)
    idx2word = {v:k for k,v in iteritems(word2idx)}

    model = Model()
    Z = model.fit_transform(We)
    plt.scatter(Z[:,0], Z[:,1])
    for i in range(V):
        plt.annotate(s=idx2word[i], xy=(Z[i,0], Z[i,1]))
    plt.show()


if __name__ == '__main__':