title: change the optimizer of the model and restore the original model from the checkpoint, but there is an error happened
body: <p>I train the model, called as model A. Then, I change the optimizer and initialize the model by the checkpoint from model A. But there is an error happened.
  Because I want to save all the variables of the new model, I didn't use the import_meta_graph('**.ckpt') and don't set the variables in the tf.train.Saver(). 
  How can I solve this problem?</p>
  
  <pre><code>saver = tf.train.Saver(max_to_keep=args.num_snapshot) 
  saver.restore(sess, tf.train.get_checkpoint_state(path).model_checkpoint_path)
  </code></pre>
  
  <p>There is the error log:</p>
  
  <pre><code>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 OptimizeLoss/fully_connected_11/biases/Adam not found in checkpoint
  [[node save/RestoreV2 (defined at ***.py:130) ]]
  </code></pre>