tensorflow ckpt模型和pb模型获取节点名称，以及ckpt转pb模型

ckpt

from tensorflow.python import pywrap_tensorflow 
checkpoint_path = 'model.ckpt-8000' 
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)

pb

import tensorflow as tf
import os

model_name = './mobilenet_v2_140_inf_graph.pb'

def create_graph():
    with tf.gfile.FastGFile(model_name, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        tf.import_graph_def(graph_def, name='')

create_graph()
tensor_name_list = [tensor.name for tensor in tf.get_default_graph().as_graph_def().node]
for tensor_name in tensor_name_list:
    print(tensor_name,'\n')

ckpt转pb

def freeze_graph(input_checkpoint,output_graph):
    '''
    :param input_checkpoint:
    :param output_graph: PB模型保存路径
    :return:
    '''
    output_node_names = "xxx"
    saver = tf.train.import_meta_graph(input_checkpoint + '.meta', clear_devices=True)
    graph = tf.get_default_graph()
    input_graph_def = graph.as_graph_def()
    with tf.Session() as sess:
        saver.restore(sess, input_checkpoint)
        output_graph_def = graph_util.convert_variables_to_constants(  
            sess=sess,
            input_graph_def=input_graph_def,# 等于:sess.graph_def
            output_node_names=output_node_names.split(","))
        with tf.gfile.GFile(output_graph, "wb") as f:
            f.write(output_graph_def.SerializeToString()) 
        print("%d ops in the final graph." % len(output_graph_def.node)) 
 
        for op in graph.get_operations():
            print(op.name, op.values())