代码：

import tensorflow as tf sess = tf.Session()check_point_path = 'variables' saver = tf.train.import_meta_graph('variables/save_variables.ckpt.meta') saver.restore(sess, tf.train.latest_checkpoint(check_point_path)) graph = tf.get_default_graph() #print(graph.get_operations()) #with open('op.txt','a') as f:# f.write(str(graph.get_operations()))op1 = graph.get_tensor_by_name('fully_connected/biases:0')print(op1)

使用函数graph.get_operations()获取ckpt.meta中保存的graph中的所有operation，而tensor_name为'op_name:0'。

然后使用graph.get_tensor_by_name('op_name:0') 获取tensor信息。

代码从ckpt文件中获取保存的variable的数据(tensor的name和value)：

import osimport tensorflow as tffrom tensorflow.python import pywrap_tensorflowcheck_point_path = 'variables'#checkpoint_path = os.path.join(logs_train_dir, 'model.ckpt')ckpt = tf.train.get_checkpoint_state(checkpoint_dir=check_point_path)checkpoint_path = os.path.join('.', ckpt.model_checkpoint_path)#print(ckpt.model_checkpoint_path)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))

法二：

from tensorflow.python.tools.inspect_checkpoint import print_tensors_in_checkpoint_file print_tensors_in_checkpoint_file("variables/save_variables.ckpt",tensor_name='', all_tensors=False, all_tensor_names=False)

注意：tf.train.latest_checkpoint(check_point_path) 方法用来获取最后一次ckeckpoint的路径，等价于

ckpt = tf.train.get_checkpoint_state(check_point_path)ckpt.model_checkpoint_path

不能将tf.train.latest_checkpoint与tf.train.get_checkpoint_state 搞混了

以上这篇tensorflow 实现从checkpoint中获取graph信息就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。