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在tensorflow中实现屏蔽输出的log信息
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tensorflow中可以通过配置环境变量 'TF_CPP_MIN_LOG_LEVEL' 的值，控制tensorflow是否屏蔽通知信息、警告、报错等输出信息。

使用方法：

import os
import tensorflow as tf
 
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}

TF_CPP_MIN_LOG_LEVEL 取值 0 ： 0也是默认值，输出所有信息

TF_CPP_MIN_LOG_LEVEL 取值 1 ： 屏蔽通知信息

TF_CPP_MIN_LOG_LEVEL 取值 2 ： 屏蔽通知信息和警告信息

TF_CPP_MIN_LOG_LEVEL 取值 3 ： 屏蔽通知信息、警告信息和报错信息

测试代码：

import tensorflow as tf
import os
 
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0'
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1'
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
v1 = tf.constant([1.0, 2.0, 3.0], shape=[3], name='v1')
v2 = tf.constant([1.0, 2.0, 3.0], shape=[3], name='v2')
sumV12 = v1 + v2
 
with tf.Session(config=tf.ConfigProto(log_device_placement=True)) as sess:
 print sess.run(sumV12)

TF_CPP_MIN_LOG_LEVEL 为 0 的输出：

2018-04-21 14:59:09.910415: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-04-21 14:59:09.910442: 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.
2018-04-21 14:59:09.910448: 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.
2018-04-21 14:59:09.910453: 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.
2018-04-21 14:59:09.910457: 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.
2018-04-21 14:59:09.911260: I tensorflow/core/common_runtime/direct_session.cc:300] Device mapping:
2018-04-21 14:59:09.911816: I tensorflow/core/common_runtime/simple_placer.cc:872] add: (Add)/job:localhost/replica:0/task:0/cpu:0
2018-04-21 14:59:09.911835: I tensorflow/core/common_runtime/simple_placer.cc:872] v2: (Const)/job:localhost/replica:0/task:0/cpu:0
2018-04-21 14:59:09.911841: I tensorflow/core/common_runtime/simple_placer.cc:872] v1: (Const)/job:localhost/replica:0/task:0/cpu:0
Device mapping: no known devices.
add: (Add): /job:localhost/replica:0/task:0/cpu:0
v2: (Const): /job:localhost/replica:0/task:0/cpu:0
v1: (Const): /job:localhost/replica:0/task:0/cpu:0
[ 2. 4. 6.]

值为0也是默认的输出，分为三部分，一个是警告信息说没有优化加速，二是通知信息告知操作所用的设备，三是程序中代码指定要输出的结果信息

TF_CPP_MIN_LOG_LEVEL 为 1 的输出，没有通知信息了：

2018-04-21 14:59:09.910415: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-04-21 14:59:09.910442: 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.
2018-04-21 14:59:09.910448: 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.
2018-04-21 14:59:09.910453: 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.
2018-04-21 14:59:09.910457: 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.
Device mapping: no known devices.
add: (Add): /job:localhost/replica:0/task:0/cpu:0
v2: (Const): /job:localhost/replica:0/task:0/cpu:0
v1: (Const): /job:localhost/replica:0/task:0/cpu:0
[ 2. 4. 6.]

TF_CPP_MIN_LOG_LEVEL 为 2和3 的输出，设置为2就没有警告信息了，设置为3警告和报错信息（如果有）就都没有了：

Device mapping: no known devices.
add: (Add): /job:localhost/replica:0/task:0/cpu:0
v2: (Const): /job:localhost/replica:0/task:0/cpu:0
v1: (Const): /job:localhost/replica:0/task:0/cpu:0
[ 2. 4. 6.]

以上这篇在tensorflow中实现屏蔽输出的log信息就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。

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