如何在C ++中保存和恢复TensorFlow图及其状态？ [英] How to save and restore a TensorFlow graph and its state in C++?

问题描述

我正在使用C ++中的TensorFlow训练我的模型。 Python仅用于构造图形。那么，有没有一种方法可以仅使用C ++来保存和恢复图形及其状态？我知道Python类 tf.train.Saver ，但据我所知，它在C ++中不存在。

I'm training my model using TensorFlow in C++. Python is used only for constructing the graph. So is there a way to save and restore the graph and its state purely in C++? I know about the Python class tf.train.Saver but as far as I understand it does not exist in C++.

推荐答案

tf.train.Saver 类当前仅在Python中存在，但但是（i）是从TensorFlow ops构建的，可以从C ++运行，并且（ii）公开 Saver.as_saver_def（） 方法，该方法可让您获取 SaverDef 协议缓冲区，带有您所拥有的ops名称必须运行才能保存或还原模型。

The tf.train.Saver class currently exists only in Python, but (i) it is built from TensorFlow ops that you can run from C++, and (ii) it exposes the Saver.as_saver_def() method that lets you get a SaverDef protocol buffer with the names of ops that you must run to save or restore a model.

在Python中，您可以按以下方式获取保存和还原操作的名称：

In Python, you can get the names of the save and restore ops as follows:

saver = tf.train.Saver(...)
saver_def = saver.as_saver_def()

# The name of the tensor you must feed with a filename when saving/restoring.
print saver_def.filename_tensor_name

# The name of the target operation you must run when restoring.
print saver_def.restore_op_name

# The name of the target operation you must run when saving.
print saver_def.save_tensor_name

在C ++中从检查点还原时，调用 Session :: Run（），将检查点文件的名称输入为 saver_def.filename_tensor_name ，目标操作数为 saver_def.restore_op_name 。要保存另一个检查点，请调用 Session :: Run（），再次将检查点文件的名称输入为 saver_def.filename_tensor_name ，并获取 saver_def.save_tensor_name 的值。

In C++ to restore from a checkpoint, you call Session::Run(), feeding in the name of the checkpoint file as saver_def.filename_tensor_name, with a target op of saver_def.restore_op_name. To save another checkpoint, you call Session::Run(), again feeding in the name of the checkpoint file as saver_def.filename_tensor_name, and fetching the value of saver_def.save_tensor_name.

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