使用tf.train.Saver()保存到checkpoint文件，我们可以用tensorflow查看。
# import the inspect_checkpoint library
from tensorflow.python.tools import inspect_checkpoint as chkp # print all tensors in checkpoint file
chkp.print_tensors_in_checkpoint_file("/tmp/model.ckpt", tensor_name='', all_tensors=True) # tensor_name: v1
# [ 1. 1. 1.]
# tensor_name: v2
# [-1. -1. -1. -1. -1.] # print only tensor v1 in checkpoint file
chkp.print_tensors_in_checkpoint_file("/tmp/model.ckpt", tensor_name='v1', all_tensors=False) # tensor_name: v1
# [ 1. 1. 1.] # print only tensor v2 in checkpoint file
chkp.print_tensors_in_checkpoint_file("/tmp/model.ckpt", tensor_name='v2', all_tensors=False) # tensor_name: v2
# [-1. -1. -1. -1. -1.]