解决TensorFlow程序无限制占用GPU的方法


Posted in Python onJune 30, 2020

今天遇到一个奇怪的现象,使用tensorflow-gpu的时候,出现内存超额~~如果我训练什么大型数据也就算了,关键我就写了一个y=W*x…显示如下图所示:

程序如下:

import tensorflow as tf

w = tf.Variable([[1.0,2.0]])
b = tf.Variable([[2.],[3.]])

y = tf.multiply(w,b)

init_op = tf.global_variables_initializer()

with tf.Session() as sess:
 sess.run(init_op)
 print(sess.run(y))

出错提示:

占用的内存越来越多,程序崩溃之后,整个电脑都奔溃了,因为整个显卡全被吃了

2018-06-10 18:28:00.263424: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2018-06-10 18:28:00.598075: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1356] Found device 0 with properties: 
name: GeForce GTX 1060 major: 6 minor: 1 memoryClockRate(GHz): 1.6705
pciBusID: 0000:01:00.0
totalMemory: 6.00GiB freeMemory: 4.97GiB
2018-06-10 18:28:00.598453: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1435] Adding visible gpu devices: 0
2018-06-10 18:28:01.265600: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:923] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-06-10 18:28:01.265826: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:929]  0 
2018-06-10 18:28:01.265971: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:942] 0: N 
2018-06-10 18:28:01.266220: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1053] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4740 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060, pci bus id: 0000:01:00.0, compute capability: 6.1)
2018-06-10 18:28:01.331056: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 4.63G (4970853120 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.399111: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 4.17G (4473767936 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.468293: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 3.75G (4026391040 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.533138: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 3.37G (3623751936 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.602452: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 3.04G (3261376768 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.670225: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 2.73G (2935238912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.733120: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 2.46G (2641714944 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.800101: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 2.21G (2377543424 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.862064: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 1.99G (2139789056 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.925434: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 1.79G (1925810176 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:01.986180: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 1.61G (1733229056 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.043456: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 1.45G (1559906048 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.103531: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 1.31G (1403915520 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.168973: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 1.18G (1263524096 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.229387: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 1.06G (1137171712 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.292997: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 976.04M (1023454720 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.356714: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 878.44M (921109248 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.418167: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 790.59M (828998400 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-06-10 18:28:02.482394: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_driver.cc:936] failed to allocate 711.54M (746098688 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY

分析原因:

显卡驱动不是最新版本,用__驱动软件__更新一下驱动,或者自己去下载更新。

TF运行太多,注销全部程序冲洗打开。

由于TF内核编写的原因,默认占用全部的GPU去训练自己的东西,也就是像meiguo一样优先政策吧

这个时候我们得设置两个方面:

  • 选择什么样的占用方式?优先占用__还是__按需占用
  • 选择最大占用多少GPU,因为占用过大GPU会导致其它程序奔溃。最好在0.7以下

先更新驱动:

解决TensorFlow程序无限制占用GPU的方法

再设置TF程序:

注意:单独设置一个不行!按照网上大神博客试了,结果效果还是很差(占用很多GPU)

设置TF:

  • 按需占用
  • 最大占用70%GPU

修改代码如下:

import tensorflow as tf

w = tf.Variable([[1.0,2.0]])
b = tf.Variable([[2.],[3.]])

y = tf.multiply(w,b)

init_op = tf.global_variables_initializer()

config = tf.ConfigProto(allow_soft_placement=True)
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.7)
config.gpu_options.allow_growth = True
with tf.Session(config=config) as sess:
 sess.run(init_op)
 print(sess.run(y))

成功解决:

2018-06-10 18:21:17.532630: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2018-06-10 18:21:17.852442: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1356] Found device 0 with properties: 
name: GeForce GTX 1060 major: 6 minor: 1 memoryClockRate(GHz): 1.6705
pciBusID: 0000:01:00.0
totalMemory: 6.00GiB freeMemory: 4.97GiB
2018-06-10 18:21:17.852817: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1435] Adding visible gpu devices: 0
2018-06-10 18:21:18.511176: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:923] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-06-10 18:21:18.511397: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:929]  0 
2018-06-10 18:21:18.511544: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:942] 0: N 
2018-06-10 18:21:18.511815: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1053] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4740 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060, pci bus id: 0000:01:00.0, compute capability: 6.1)
[[2. 4.]
 [3. 6.]]

参考资料:

主要参考博客

错误实例

到此这篇关于解决TensorFlow程序无限制占用GPU的方法 的文章就介绍到这了,更多相关TensorFlow 占用GPU内容请搜索三水点靠木以前的文章或继续浏览下面的相关文章希望大家以后多多支持三水点靠木!

Python 相关文章推荐
Python、Javascript中的闭包比较
Feb 04 Python
Python动刷新抢12306火车票的代码(附源码)
Jan 24 Python
Python微信操控itchat的方法
May 31 Python
Pytorch 使用不同版本的cuda的方法步骤
Apr 02 Python
解决jupyter运行pyqt代码内核重启的问题
Apr 16 Python
PyQt5如何将.ui文件转换为.py文件的实例代码
May 26 Python
django 模型字段设置默认值代码
Jul 15 Python
解决python中0x80072ee2错误的方法
Jul 19 Python
Scrapy中如何向Spider传入参数的方法实现
Sep 28 Python
在Python中实现字典反转案例
Dec 05 Python
Python入门基础之数字字符串与列表
Feb 01 Python
python爬虫scrapy框架之增量式爬虫的示例代码
Feb 26 Python
tensorflow 大于某个值为1,小于为0的实例
Jun 30 #Python
基于tf.shape(tensor)和tensor.shape()的区别说明
Jun 30 #Python
Tensorflow全局设置可见GPU编号操作
Jun 30 #Python
Python logging模块异步线程写日志实现过程解析
Jun 30 #Python
浅谈多卡服务器下隐藏部分 GPU 和 TensorFlow 的显存使用设置
Jun 30 #Python
Tensorflow中批量读取数据的案列分析及TFRecord文件的打包与读取
Jun 30 #Python
使用Tensorflow-GPU禁用GPU设置(CPU与GPU速度对比)
Jun 30 #Python
You might like
PHP 文件上传功能实现代码
2009/06/24 PHP
MayFish PHP的MVC架构的开发框架
2009/08/13 PHP
php返回json数据函数实例
2014/10/09 PHP
PHP输出九九乘法表代码实例
2015/03/27 PHP
PHP实现通过正则表达式替换回调的内容标签
2015/06/15 PHP
完美利用Yii2微信后台开发的系列总结
2016/07/18 PHP
PHP重置数组为连续数字索引的几种方式总结
2018/03/12 PHP
JavaScript设置FieldSet展开与收缩
2009/05/15 Javascript
jquery下onpropertychange事件的绑定方法
2010/08/01 Javascript
33个优秀的 jQuery 图片展示插件分享
2012/03/14 Javascript
jquery select动态加载选择(兼容各种浏览器)
2013/02/01 Javascript
js获取判断上传文件后缀名的示例代码
2014/02/19 Javascript
基于jQuery实现网页进度显示插件
2015/03/04 Javascript
详解Vue.js入门环境搭建
2017/03/17 Javascript
Angular中管道操作符(|)的使用方法
2017/12/15 Javascript
修改node.js默认的npm安装目录实例
2018/05/15 Javascript
微信小程序input框中加入小图标的实现方法
2018/06/19 Javascript
Python中使用 Selenium 实现网页截图实例
2014/07/18 Python
Python入门之三角函数tan()函数实例详解
2017/11/08 Python
Python语言描述连续子数组的最大和
2018/01/04 Python
Python解析多帧dicom数据详解
2020/01/13 Python
解决python图像处理图像赋值后变为白色的问题
2020/06/04 Python
如何在python中处理配置文件代码实例
2020/09/27 Python
Python 随机按键模拟2小时
2020/12/30 Python
jupyter notebook更换皮肤主题的实现
2021/01/07 Python
python math模块的基本使用教程
2021/01/16 Python
是否可以从一个static方法内部发出对非static方法的调用?
2014/08/18 面试题
运动会广播稿30字
2014/01/21 职场文书
大家访活动实施方案
2014/03/10 职场文书
网络工程师自荐书范文
2014/04/01 职场文书
电子装配专业毕业生求职信
2014/04/23 职场文书
面试必备的求职信
2014/05/25 职场文书
多媒体教室标语
2014/06/26 职场文书
公司晚宴祝酒词
2015/08/11 职场文书
Python中OpenCV实现简单车牌字符切割
2021/06/11 Python
Python装饰器的练习题
2021/11/23 Python