如何在张量流中恢复会话？ [复制]

Question

我想在不再次训练网络的情况下使用我的神经网络。 我读到了

save_path = saver.save(sess, "model.ckpt")
print("Model saved in file: %s" % save_path)

现在文件夹中有 3 个文件：checkpoint、model.ckpt 和 model.ckpt.meta

我想在 python 的另一个类中恢复数据，获取我的神经网络的权重并进行单个预测。

我该怎么做？

Answer 1

要保存模型，您可以这样做：

model_checkpoint = 'model.chkpt'

# Create the model
...
...

with tf.Session() as sess:
    sess.run(tf.initialize_all_variables())

    # Create a saver so we can save and load the model as we train it
    tf_saver = tf.train.Saver(tf.all_variables())

    # (Optionally) do some training of the model
    ...
    ...

    tf_saver.save(sess, model_checkpoint)

我假设你已经这样做了，因为你已经得到了三个文件。 当你想在另一个类中加载模型时，你可以这样做：

# The same file as we saved earlier
model_checkpoint = 'model.chkpt'

# Create the SAME model as before
...
...

with tf.Session() as sess:
    # Restore the model
    tf_saver = tf.train.Saver()
    tf_saver.restore(sess, model_checkpoint)

    # Now your model is loaded with the same values as when you saved,
    #   and you can do prediction or continue training