1 将ckpt的meta文件转换成tensorboard需要的log文件
参考代码如下:
import tensorflow as tf
def write_ckpt_meta_to_tensorboard(ckpt_meta_file, log_dir):
g = tf.Graph()
with g.as_default() as g:
tf.train.import_meta_graph(ckpt_meta_file)
with tf.Session(graph=g) as sess:
file_writer = tf.summary.FileWriter(logdir=log_dir, graph=g)
file_writer.close()
if __name__ == "__main__":
meta_file = "/tmp/model.ckpt-806.meta"
log_dir = "/tmp/tensorboard_log_806"
write_ckpt_meta_to_tensorboard(meta_file, log_dir)
运行上面的代码,会产生log文件tensorboard_log_806.
2.启动Tensorboard服务
接着运行下面的命令启动tensorboard服务,前提是安装了tensorboard库.运行下面的pip命令进行安装
# 安装tensorboard
pip install tensorboard
# 启动tensorboard服务
tensorboard --logdir=/tmp/tensorboard_log_806
3.使用浏览器访问Tensorboard的Web
打开浏览器输入: localhost:6006, 即可查看图模型