tensorflow框架.ckpt .pb模型节点tensor_name打印及ckpt模型转.pb模型

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转换模型首先要知道的是从哪个节点输出，如果没有源代码是很难清楚节点信息。

获取ckpt模型的节点名称

import os
from tensorflow.python import pywrap_tensorflow

checkpoint_path = os.path.join('./ade20k', "model.ckpt-27150")
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)) #相应的值

获取pb模型的节点名称

import tensorflow as tf
import os

model_dir = './'
model_name = 'model.pb'

def create_graph():
    with tf.gfile.FastGFile(os.path.join(
            model_dir, 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转换为pb模型

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

saver = tf.train.import_meta_graph("./ade20k/model.ckpt-27150.meta", clear_devices=True)

#【敲黑板！】这里就是填写输出节点名称惹
output_nodes = ["xxx"] 

with tf.Session(graph=tf.get_default_graph()) as sess:
    input_graph_def = sess.graph.as_graph_def()
    saver.restore(sess, "./ade20k/model.ckpt-27150")
    output_graph_def = tf.graph_util.convert_variables_to_constants(sess,
                                                                    input_graph_def,
                                                                    output_nodes)
    with open("frozen_model.pb", "wb") as f:
        f.write(output_graph_def.SerializeToString())