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.]