您可以使用inspect_checkpoint.py工具。

因此，例如，如果将检查点存储在当前目录中，则可以按如下所示打印变量及其值

import tensorflow as tf
from tensorflow.python.tools.inspect_checkpoint import print_tensors_in_checkpoint_file


latest_ckp = tf.train.latest_checkpoint('./')
print_tensors_in_checkpoint_file(latest_ckp, all_tensors=True, tensor_name='')

一些细节。

例如，如果您的模型是使用V2格式保存的，则目录/my/dir/有以下文件

model-10000.data-00000-of-00001
model-10000.index
model-10000.meta

那么file_name参数应该仅是前缀，即

print_tensors_in_checkpoint_file(file_name='/my/dir/model_10000', tensor_name='', all_tensors=True)

参见https://github.com/tensorflow/tensorflow/issues/7696进行讨论。

用法示例：

from tensorflow.python.tools.inspect_checkpoint import print_tensors_in_checkpoint_file
import os
checkpoint_path = os.path.join(model_dir, "model.ckpt")

# List ALL tensors example output: v0/Adam (DT_FLOAT) [3,3,1,80]
print_tensors_in_checkpoint_file(file_name=checkpoint_path, tensor_name='')

# List contents of v0 tensor.
# Example output: tensor_name:  v0 [[[[  9.27958265e-02   7.40226209e-02   4.52989563e-02   3.15700471e-02
print_tensors_in_checkpoint_file(file_name=checkpoint_path, tensor_name='v0')

# List contents of v1 tensor.
print_tensors_in_checkpoint_file(file_name=checkpoint_path, tensor_name='v1')

更新：从Tensorflow 0.12.0-rc0开始， 已将 all_tensors参数添加到print_tensors_in_checkpoint_file因此如果需要，您可能需要添加all_tensors=False或all_tensors=True 。

替代方法：

from tensorflow.python import pywrap_tensorflow
import os

checkpoint_path = os.path.join(model_dir, "model.ckpt")
reader = pywrap_tensorflow.NewCheckpointReader(checkpoint_path)
var_to_shape_map = reader.get_variable_to_shape_map()

for key in var_to_shape_map:
    print("tensor_name: ", key)
    print(reader.get_tensor(key)) # Remove this is you want to print only variable names

希望能帮助到你。