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()
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