windows - Python3.6 环境下tensorflow1.8升级到2.1版本， tensorflow安装

电玩女神 2023-07-05 13:26 3阅读 0赞

1. 下载最新的 tensorflow

根据自己电脑的系统和Python版本下载tensorflow，注意cpu与GPU，电脑显卡不行的，就下cpu版本。

一些安装机制需要TensorFlow Python软件包的URL。您指定的值取决于您的Python版本。

<table> 
 <tbody> 
 <tr> 
 <td> 版 </td> 
 <td> 网址 </td> 
 </tr> 
 <tr> 
 <td colspan="2" style="vertical-align:top;"> 的Linux </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 2.7 GPU支持 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp27-cp27mu-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> 仅Python 2.7 CPU </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp27-cp27mu-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.5 GPU支持 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp35-cp35m-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> 仅限Python 3.5 CPU </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp35-cp35m-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.6 GPU支持 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp36-cp36m-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> 仅Python 3.6 CPU </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp36-cp36m-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.7 GPU支持 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp37-cp37m-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> 仅Python 3.7 CPU </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp37-cp37m-manylinux2010_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td colspan="2" style="vertical-align:top;"> macOS（仅CPU） </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 2.7 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp27-cp27m-macosx_10_9_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.5 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp35-cp35m-macosx_10_6_intel.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.6 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp36-cp36m-macosx_10_9_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.7 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp37-cp37m-macosx_10_9_x86_64.whl </td> 
 </tr> 
 <tr> 
 <td colspan="2" style="vertical-align:top;"> 视窗 </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.5 GPU支持 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.1.0-cp35-cp35m-win_amd64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> 仅限Python 3.5 CPU </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.1.0-cp35-cp35m-win_amd64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.6 GPU支持 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.1.0-cp36-cp36m-win_amd64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> 仅Python 3.6 CPU </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.1.0-cp36-cp36m-win_amd64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3.7 GPU支持 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.1.0-cp37-cp37m-win_amd64.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> 仅Python 3.7 CPU </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.1.0-cp37-cp37m-win_amd64.whl </td> 
 </tr> 
 <tr> 
 <td colspan="2" style="vertical-align:top;"> Raspberry PI（仅CPU） </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3，Pi0或Pi1 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.1.0-cp35-none-linux_armv6l.whl </td> 
 </tr> 
 <tr> 
 <td style="vertical-align:top;"> Python 3，Pi2或Pi3 </td> 
 <td style="vertical-align:top;"> https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.1.0-cp35-none-linux_armv7l.whl </td> 
 </tr> 
 </tbody> 
</table>

下载之后，放到一个文件夹下面。

2. 修改pip源地址

为什么要修改pip源呢？安装时候，需要下载一些包，官方的源比较慢。

(1):在windows文件管理器中,输入 %APPDATA%

(2):会定位到一个新的目录下，在该目录下新建pip文件夹，然后到pip文件夹里面去新建个pip.ini文件

(3):在新建的pip.ini文件中输入以下内容，搞定文件路径："C:\\Users\\Administrator\\AppData\\Roaming\\pip\\pip.ini"

Pip.ini文件内容：

\[global\]

timeout = 6000

index-url = https://pypi.tuna.tsinghua.edu.cn/simple

trusted-host = pypi.tuna.tsinghua.edu.cn

上述使用的是清华的源镜像，还可以使用以下的国内源镜像：**（强烈建议使用清华源，其它有些坑）**

V2EX：http://pypi.v2ex.com/simple

豆瓣：http://pypi.douban.com/simple

中国科学技术大学：http://pypi.mirrors.ustc.edu.cn/simple

清华：[https://pypi.tuna.tsinghua.edu.cn/simple][https_pypi.tuna.tsinghua.edu.cn_simple]

**3. 升级安装**

由于我的电脑已经安装了tensorflow1.8，所以按照下图所示升级，会出现不兼容的问题。

pip3 install --upgrade tensorflow\_cpu-2.1.0-cp36-cp36m-win\_amd64.whl![2020021515594461.png][]

安装最后出现错误：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ_size_16_color_FFFFFF_t_70][]

(1）tensorflow1.8与2.1不兼容，升级2.1之前，需要手动卸载1.8

pip uninstall tensorflow

（2）cmd命令的权限不够，需要管理员权限

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ_size_16_color_FFFFFF_t_70 1][]

卸载tensorflow1.8以后，重新安装。

pip3 install --upgrade tensorflow\_cpu-2.1.0-cp36-cp36m-win\_amd64.whl

中间有些错误，主要是几个包版本不对，根据红色字体的需求，安装相应的包即可。

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ_size_16_color_FFFFFF_t_70 2][]

安装之后，输入： **import tensorflow,** 没有错误说明安装OK

![20200215155946351.png][]

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![20200204150324686.png][]

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[https_pypi.tuna.tsinghua.edu.cn_simple]: https://pypi.tuna.tsinghua.edu.cn/simple
[2020021515594461.png]: https://img-blog.csdnimg.cn/2020021515594461.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20200215155946812.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20200215155944653.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ==,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ_size_16_color_FFFFFF_t_70 2]: https://img-blog.csdnimg.cn/2020021515594662.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3N1bnNreWRheQ==,size_16,color_FFFFFF,t_70
[20200215155946351.png]: https://img-blog.csdnimg.cn/20200215155946351.png
[20200204150324686.png]: https://img-blog.csdnimg.cn/20200204150324686.png