代码测试环境 : CPU 环境的 TensorFlow 

一. 默认 Log 配置

# coding:utf-8

import tensorflow as tf

def test0():
    v = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
    sess = tf.Session()
    with sess.as_default():
        print(tf.clip_by_value(v, 3, 5).eval())

def main():
    print('start.')
    test0()
    print('end.')

if __name__ == '__main__':
    main()

输出为 :

start.
2017-10-17 21:20:34.570991: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-10-17 21:20:34.571017: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-10-17 21:20:34.571023: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-10-17 21:20:34.571027: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
[[ 3.  3.  3.]
 [ 4.  5.  5.]]
end.

二. 指定 Log 配置

添加如下代码 : 

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'

start.
[[ 3.  3.  3.]
 [ 4.  5.  5.]]
end.

三. LOG 等级说明

import os
os.environ[‘TF_CPP_MIN_LOG_LEVEL‘]=‘1‘ # 这是默认的显示等级，显示所有信息

# 2级
import os
os.environ[‘TF_CPP_MIN_LOG_LEVEL‘]=‘2‘ # 只显示 warning 和 Error

# 3级
import os
os.environ[‘TF_CPP_MIN_LOG_LEVEL‘]=‘3‘ # 只显示 Error