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convert_pb.py
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convert_pb.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun May 13 18:52:05 2018
@author: wu
"""
import tensorflow as tf
import os.path
import argparse
from tensorflow.python.framework import graph_util
MODEL_DIR = '/home/wu/TF_Project/Compression/model_sample/'
MODEL_NAME = "frozen_model.pb"
if not tf.gfile.Exists(MODEL_DIR): #创建目录
tf.gfile.MakeDirs(MODEL_DIR)
def freeze_graph(model_folder):
checkpoint = tf.train.get_checkpoint_state(model_folder) #检查目录下ckpt文件状态是否可用
input_checkpoint = checkpoint.model_checkpoint_path #得ckpt文件路径
output_graph = os.path.join(MODEL_DIR, MODEL_NAME) #PB模型保存路径
output_node_names = "fc8" #原模型输出操作节点的名字
saver = tf.train.import_meta_graph(input_checkpoint + '.meta', clear_devices=True) #得到图、clear_devices :Whether or not to clear the device field for an `Operation` or `Tensor` during import.
graph = tf.get_default_graph() #获得默认的图
input_graph_def = graph.as_graph_def() #返回一个序列化的图代表当前的图
with tf.Session() as sess:
saver.restore(sess, input_checkpoint) #恢复图并得到数据
#print("predictions : ", sess.run("predictions:0", feed_dict={"input_holder:0": [10.0]})) # 测试读出来的模型是否正确,注意这里传入的是输出 和输入 节点的 tensor的名字,不是操作节点的名字
output_graph_def = graph_util.convert_variables_to_constants( #模型持久化,将变量值固定
sess,
input_graph_def,
output_node_names.split(",") #如果有多个输出节点,以逗号隔开
)
with tf.gfile.GFile(output_graph, "wb") as f: #保存模型
f.write(output_graph_def.SerializeToString()) #序列化输出
print("%d ops in the final graph." % len(output_graph_def.node)) #得到当前图有几个操作节点
for op in graph.get_operations():
print(op.name, op.values())
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("model_folder", type=str, help="input ckpt model dir") #命令行解析,help是提示符,type是输入的类型,
# 这里运行程序时需要带上模型ckpt的路径,不然会报 error: too few arguments
aggs = parser.parse_args()
freeze_graph(aggs.model_folder)
# freeze_graph("model/ckpt") #模型目录