PB文件相关操作

一、获取pb模型的节点名称

import tensorflow as tf
import os


model_dir = ‘  ’
model_name = ' '

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]
f = open('/home/yk/Desktop/Conv-TasNet-master-20190508/op.txt', 'wb')
for tensor_name in tensor_name_list:
    print(tensor_name,'\n')
    f.write(tensor_name + '\n')

二、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())

三、pb TensorBoard 可视化

1. 从pb文件中恢复计算图
import tensorflow as tf

model = 'model.pb' #请将这里的pb文件路径改为自己的
graph = tf.get_default_graph()
graph_def = graph.as_graph_def()
graph_def.ParseFromString(tf.gfile.FastGFile(model, 'rb').read())
tf.import_graph_def(graph_def, name='graph')
summaryWriter = tf.summary.FileWriter('log/', graph)

执行以上代码就会生成文件在log/events.out.tfevents.1535079670.DESKTOP-5IRM000。


2. 在tensorboard中加载

tensorboard --logdir path/to/log

3. 在浏览器中打开链接

附加：ckpt模型节点获取

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