model.py 文件源码

def gen(self):
        embedding, _ = self.embedding()
        saver = tf.train.Saver()
        with tf.Session() as sess:
            sess.run(tf.global_variables_initializer())
            saver.restore(sess, tf.train.latest_checkpoint('.'))
            embedding = sess.run(embedding)
        # ???
        data = embedding[:self.viz_words, :]
        # ???????
        tsne = TSNE(n_components=2, init='pca', random_state=0)
        embed_tsne = tsne.fit_transform(data)
        # ??
        plt.subplots(figsize=(10, 10))
        for idx in range(self.viz_words):
            plt.scatter(*embed_tsne[idx, :], color='steelblue')
            plt.annotate(self.train_text.int_to_vocab[idx], (embed_tsne[idx, 0], embed_tsne[idx, 1]), alpha=0.7)
        plt.show()