解决模型加载NotFoundError (see above for traceback) Key v1 not found in checkp错误

NotFoundError (see above for traceback): Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Key v1 not found in checkpoint
     [[Node: save/RestoreV2 = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_save/Const_0_0, save/RestoreV2/tensor_names, save/RestoreV2/shape_and_slices)]]

出现这样的问题，大多是在使用时，checkpoint文件中的变量名和调用的文件名不匹配造成的。解决方法就是查看checkpoint文件中的变量名，将程序调用变量名修改为checkpoint文件中的变量名即可解决问题。下边具体讲如何查看checkpoint文件中的变量名、修改程序调用变量名

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下边例子是《TensorFlow实战Google深度学习框架》中模型持久化的例子，同时也解决书中ch5 重命名加载的问题：

模型保存的代码为：

#!/usr/bin/env python
# -*- coding:utf-8 -*-

im