在不同机器上恢复张量流模型

Question

我在GPU集群上训练了TensorFlow模型，用

saver = tf.train.Saver()
saver.save(sess, config.model_file, global_step=global_step)

现在我正试图用

^{pr2}$

用于评估，在不同的系统上。问题是saver.restore 产生以下错误：

    Traceback (most recent call last):
  File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 1664, in <module>
    main()
  File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 1658, in main
    globals = debugger.run(setup['file'], None, None, is_module)
  File "/Applications/PyCharm.app/Contents/helpers/pydev/pydevd.py", line 1068, in run
    pydev_imports.execfile(file, globals, locals)  # execute the script
  File "/Applications/PyCharm.app/Contents/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "/Users/jonpdeaton/Developer/BraTS18-Project/segmentation/evaluate.py", line 205, in <module>
    main()
  File "/Users/jonpdeaton/Developer/BraTS18-Project/segmentation/evaluate.py", line 162, in main
    restore_and_evaluate(save_path, model_file, output_dir)
  File "/Users/jonpdeaton/Developer/BraTS18-Project/segmentation/evaluate.py", line 127, in restore_and_evaluate
    saver.restore(sess, tf.train.latest_checkpoint(save_path))
  File "/Users/jonpdeaton/anaconda3/envs/BraTS/lib/python3.6/site-packages/tensorflow/python/training/saver.py", line 1857, in latest_checkpoint
    if file_io.get_matching_files(v2_path) or file_io.get_matching_files(
  File "/Users/jonpdeaton/anaconda3/envs/BraTS/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 337, in get_matching_files
    for single_filename in filename
  File "/Users/jonpdeaton/anaconda3/envs/BraTS/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 519, in __exit__
    c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.NotFoundError: /afs/cs.stanford.edu/u/jdeaton/dfs/unet; No such file or directory

似乎有一些存储在模型或checkpoint文件中的路径，这些路径在我正在进行评估的系统上不再有效。复制了model-X.meta、model-X.index和checkpoint文件后，如何在另一台计算机上恢复模型（用于评估）？在

Answer 1

默认情况下，Saver对象将把绝对模型检查点路径写入checkpoint文件。因此，tf.train.latest_checkpoint(save_path)返回的路径是旧机器上的绝对路径。在

临时解决方案：

1. 将实际的模型文件路径直接传递给restore方法，而不是tf.train.latest_checkpoint的结果。在
2. 手动编辑checkpoint文件，它是一个简单的文本文件。在

长期解决方案：

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

Answer 2

用您最喜欢的文本编辑器打开检查点文件，只需将其中找到的绝对路径更改为仅文件名。在