将张量值保存为二进制格式的文件的最佳方法是什么? [英] What is the best way to save tensor value to file as binary format?

问题描述

我正在尝试将张量值保存为二进制格式的文件. 特别是我正在尝试将float32张量值保存为二进制格式(IEEE-754格式).你能帮我吗??

I'm trying to save tensor value to file as binary format. Especially I'm trying to save float32 tensor value as binary format(IEEE-754 format). Could you please help me ??

import tensorflow as tf

x = tf.constant([[1.0, 2.0, 3.0], [5.5, 4.3, 2.5]])

# how to save tensor x as binary format ?? 

推荐答案

推荐的方法是检查模型.如保存和恢复程序员指南中所述，您将创建

The recommended approach is to checkpoint your model. As documented in the Saving and Restoring programmer's guide, you create a tf.train.Saver object, optionally specifying which variables/saveable objects are to be saved. Then, whenever you want to save the values of the tensors, you invoke the save() method of the tf.train.Saver object:

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

#...

saver.save(session, 'my-checkpoints', global_step = step)

..其中第二个参数(在上例中为'my-checkpoints')是存储检查点二进制文件的目录的路径.

.. where the second argument ('my-checkpoints' in the above example) is the path to a directory in which the checkpoint binary files are stored.

另一种方法是评估单个张量(将为NumPy ndarrays)，然后将单个ndarray保存到NPY文件中(通过

Another approach is to evaluate individual tensors (which will be NumPy ndarrays) and then save individual ndarrays to NPY files (via numpy.save()) or multiple ndarrays to a single NPZ archive (via numpy.savez() or numpy.savez_compressed()):

np.save('x.npy', session.run(x), allow_pickle = False)

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