在tensorflow中實(shí)現(xiàn)屏蔽輸出的log信息
更新時間：2020年02月04日 08:39:29 作者：-牧野-
今天小編就為大家分享一篇在tensorflow中實(shí)現(xiàn)屏蔽輸出的log信息，具有很好的參考價值，希望對大家有所幫助。一起跟隨小編過來看看吧
tensorflow中可以通過配置環(huán)境變量 'TF_CPP_MIN_LOG_LEVEL' 的值，控制tensorflow是否屏蔽通知信息、警告、報錯等輸出信息。
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也是默認(rèn)值，輸出所有信息
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、警告信息和報錯信息
測試代碼：
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 為 0 的輸出：
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.]
值為0也是默認(rèn)的輸出，分為三部分，一個是警告信息說沒有優(yōu)化加速，二是通知信息告知操作所用的設(shè)備，三是程序中代碼指定要輸出的結(jié)果信息
TF_CPP_MIN_LOG_LEVEL 為 1 的輸出，沒有通知信息了： 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 為 2和3 的輸出，設(shè)置為2就沒有警告信息了，設(shè)置為3警告和報錯信息（如果有）就都沒有了：
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.]
以上這篇在tensorflow中實(shí)現(xiàn)屏蔽輸出的log信息就是小編分享給大家的全部內(nèi)容了，希望能給大家一個參考，也希望大家多多支持腳本之家。
相關(guān)文章
使用Python在Windows下獲取USB PID&VID的方法
今天小編就為大家分享一篇使用Python在Windows下獲取USB PID&VID的方法，具有很好的參考價值，希望對大家有所幫助。一起跟隨小編過來看看吧2019-07-07
Python中函數(shù)調(diào)用9大方法小結(jié)
在Python中,函數(shù)是一種非常重要的編程概念,它們使得代碼模塊化、可重用,并且能夠提高代碼的可讀性,本文將深入探討Python函數(shù)調(diào)用的9種方法,需要的可以參考下2024-01-01
這篇文章主要介紹了Python unittest模塊用法,結(jié)合實(shí)例形式分析了unittest模塊功能及相關(guān)函數(shù)使用技巧,需要的朋友可以參考下2018-05-05
本章我們將介紹下經(jīng)典的軟件開發(fā)所遵循的MVC (Model-View-Controller, 模型-視圖-控制器) 設(shè)計模式以及Django的MVT設(shè)計模式(Model-View-Template)是如何遵循這種設(shè)計理念的。2021-04-04
python統(tǒng)計多維數(shù)組的行數(shù)和列數(shù)實(shí)例
今天小編就為大家分享一篇python統(tǒng)計多維數(shù)組的行數(shù)和列數(shù)實(shí)例，具有很好的參考價值，希望對大家有所幫助。一起跟隨小編過來看看吧2018-06-06
Pycharm Available Package無法顯示/安裝包的問題Error Loading Package Li
這篇文章主要介紹了Pycharm Available Package無法顯示/安裝包的問題Error Loading Package List解決，文中通過示例代碼介紹的非常詳細(xì)，對大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價值，需要的朋友們下面隨著小編來一起學(xué)習(xí)學(xué)習(xí)吧2020-09-09
python 解決mysql where in 對列表(list,,array)問題
這篇文章主要介紹了python 解決mysql where in 對列表(list,,array)問題，具有很好的參考價值，希望對大家有所幫助。一起跟隨小編過來看看吧2020-06-06
PyCharm MySQL可視化Database配置過程圖解
這篇文章主要介紹了PyCharm MySQL可視化Database配置過程圖解,文中通過示例代碼介紹的非常詳細(xì)，對大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價值,需要的朋友可以參考下2020-06-06
解決pycharm下載庫時出現(xiàn)Failed to install package的問題
很多小伙伴遇到pycharm下載庫時出現(xiàn)Failed to install package不知道怎么解決，下面小編給大家?guī)砹私鉀Q方法，需要的朋友參考下吧2021-09-09
Python基礎(chǔ)知識+結(jié)構(gòu)+數(shù)據(jù)類型
這篇文章主要介紹了Python基礎(chǔ)知識+結(jié)構(gòu)+數(shù)據(jù)類型，文章基于python基礎(chǔ)知識圍繞主題展開詳細(xì)內(nèi)容介紹，具有一定的參考價值，需要的小伙伴可以參考一下2022-05-05