Step1
去到NVIDIA 官网下载 CUDA Toolkit 10.0
![](https://img.haomeiwen.com/i454212/debb033c956450b7.png)
选择自定义
![](https://img.haomeiwen.com/i454212/4e02037472d27181.png)
如果没有安装Visual Studio 可以把该项去掉✔
![](https://img.haomeiwen.com/i454212/d6650a8f98bdb8c3.png)
注意 如果新版本 < 当前版,注意要取消✔
![](https://img.haomeiwen.com/i454212/3b5197d4e25dac85.png)
Step2
下载 Download cuDNN v7.6.2 (July 22, 2019), for CUDA 10.0
![](https://img.haomeiwen.com/i454212/ac63e0ce9f134c50.png)
下载解压之后放在 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0 路径下并且改名为 cudnn
![](https://img.haomeiwen.com/i454212/320a905dcabae111.png)
Step3
配置系统环境变量
![](https://img.haomeiwen.com/i454212/8ef5821b480ba342.png)
![](https://img.haomeiwen.com/i454212/afe81a734d637db4.png)
![](https://img.haomeiwen.com/i454212/8ffc22689d93da1a.png)
Step4
检测nvcc
nvcc -V
![](https://img.haomeiwen.com/i454212/286d2867943bcf55.png)
Step5
测试 Tensorflow
安装TensorFlow2.0
pip install tensorflow==2.0.0-rc0
在终端启动 ipython
ipython
![](https://img.haomeiwen.com/i454212/a073674e6c8215dc.png)
导入tensorflow
import tensorflow as tf
![](https://img.haomeiwen.com/i454212/057cc8905d16624c.png)
测试是否支持GPU
tf.test.is_built_with_gpu_support
![](https://img.haomeiwen.com/i454212/c79cefde7d768206.png)
测试运算
tf.constant(1.) + tf.constant(2.)
![](https://img.haomeiwen.com/i454212/12df6b317ae27fca.png)
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