【发布时间】:2017-10-28 15:58:08
【问题描述】:
我正在尝试使用说明here进行安装
我在系统上安装了兼容的 nVIDIA GEFORCE 920M GPU 和 CRUD DNN 工具包和驱动程序。 当我在 python 程序上执行步骤以测试 GPU 上的 tensorflow 安装时:
import tensorflow as tf
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
我得到的输出是:
>>> sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
2017-05-28 09:38:01.349304: W c:\tf_jenkins\home\workspace\release-
win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45]
The TensorFlow library wasn't compiled to use SSE instructions, but these
are available on your machine and could speed up CPU computations.
2017-05-28 09:38:01.349459: W c:\tf_jenkins\home\workspace\release-
win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45]
The TensorFlow library wasn't compiled to use SSE2 instructions, but these
are available on your machine and could speed up CPU computations.
2017-05-28 09:38:01.349583: W c:\tf_jenkins\home\workspace\release-
win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45]
The TensorFlow library wasn't compiled to use SSE3 instructions, but these
are available on your machine and could speed up CPU computations.
2017-05-28 09:38:01.349705: W c:\tf_jenkins\home\workspace\release-
win\device\cpu\os\windows\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.
2017-05-28 09:38:01.354312: I c:\tf_jenkins\home\workspace\release-
win\device\cpu\os\windows\tensorflow\core\common_runtime\direct_session.cc:257] Device mapping:
我向您提出的问题是:
为什么在安装所有库和工具包时未检测到 nVIDIA GPU?
为什么输出显示“TensorFlow 库未编译为使用 SSE4.1 指令,但是这些 可以在您的机器上使用,并且可以加快 CPU 计算速度”,我该如何解决这个问题?
请给出一步一步的解决方案。没有别的。
提前感谢您的回答。
【问题讨论】:
标签: python-3.x gpu tensorflow-gpu