cj0012/ai-practice-tensorflow-notes

人工智能实践：Tensorflow笔记

ai-practice-tensorflow-notes's Issues

mnist_lenet5_backward：tensorflow.python.framework.errors_impl.UnknownError: Failed to rename

大佬们谁知道这个如何解决？

After 47001 training step(s), loss on training batch is 0.654984.
Traceback (most recent call last):
  File "D:/yuangezhizao/Documents/PycharmProjects/Tensorflow-Study/7_2/mnist_lenet5_backward.py", line 82, in <module>
    main()
  File "D:/yuangezhizao/Documents/PycharmProjects/Tensorflow-Study/7_2/mnist_lenet5_backward.py", line 78, in main
    backward(mnist)
  File "D:/yuangezhizao/Documents/PycharmProjects/Tensorflow-Study/7_2/mnist_lenet5_backward.py", line 73, in backward
    saver.save(sess, os.path.join(MODEL_SAVE_PATH, MODEL_NAME), global_step=global_step)
  File "C:\Python37\lib\site-packages\tensorflow\python\training\saver.py", line 1181, in save
    save_relative_paths=self._save_relative_paths)
  File "C:\Python37\lib\site-packages\tensorflow\python\training\checkpoint_management.py", line 242, in update_checkpoint_state_internal
    text_format.MessageToString(ckpt))
  File "C:\Python37\lib\site-packages\tensorflow\python\lib\io\file_io.py", line 547, in atomic_write_string_to_file
    rename(temp_pathname, filename, overwrite)
  File "C:\Python37\lib\site-packages\tensorflow\python\lib\io\file_io.py", line 508, in rename
    rename_v2(oldname, newname, overwrite)
  File "C:\Python37\lib\site-packages\tensorflow\python\lib\io\file_io.py", line 526, in rename_v2
    compat.as_bytes(src), compat.as_bytes(dst), overwrite, status)
  File "C:\Python37\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 528, in __exit__
    c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.UnknownError: Failed to rename: ./model\checkpoint.tmpec679952c87543f1adbd45d8f61ca058 to: ./model\checkpoint : \udcbeܾ\udcf8\udcb7\udcc3\udcceʡ\udca3
; Input/output error

Process finished with exit code 1

Source

What is the source you use for these practices?

Recommend to use TensorFlow2 and Pyhton3

Recommend to use TensorFlow2 and Pyhton3