Tensorflow win10环境下的安装方法 （二者安装其一即可使用）

方法一：

无脑安装法：

1、打开pychem 右下角 单击选择 解释器按钮

    2、单击选择 解释器设置

3、在弹出的窗口中 单击 右上角的 小 + 号

4、同时还会弹出个窗口 在窗口中 键入 tensorflow 即可

5、在左下角 单击 按钮安装包 即可

1. 等待几分钟即可 自动安装成功

方法二：

• 命令指令符安装

1. 单击 键盘 win键 或者 用鼠标单击电脑左下角
2. 单击 所有程序 打开 anaconda3 文件夹 选择黑色窗体
3. 输入      pip uninstall tensorflow
4. 输入            Y
5. 输入

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple/ --upgrade tensorflow==2.0

期间发现 没有运行了 嗯一下 键盘上的 Enter键 即回车键即可

   

1. 安装过程中 如果出现 红字 需键入如下代码：

pip install wrapt https://pypi.tuna.tsinghua.edu.cn/simple/--ignore-installed

当运行完成之后 再重复第五步操作

1. 安装过程中 如果出现 黄字 需键入如下代码：

python –m pip install --upgrade pip -i http://pypi.douban.com/simple --trusted-host pypi.douban.com[A1] 

  

代码历程如下：

(base) C:\Users\Administrator>pip uninstall tensorflow[A2] 

Found existing installation: tensorflow 2.6.0

Uninstalling tensorflow-2.6.0:

  Would remove:

    c:\programdata\anaconda3\lib\site-packages\tensorflow-2.6.0.dist-info\*

    c:\programdata\anaconda3\lib\site-packages\tensorflow\*

    c:\programdata\anaconda3\scripts\estimator_ckpt_converter.exe

    c:\programdata\anaconda3\scripts\import_pb_to_tensorboard.exe

    c:\programdata\anaconda3\scripts\saved_model_cli.exe

    c:\programdata\anaconda3\scripts\tensorboard.exe

    c:\programdata\anaconda3\scripts\tf_upgrade_v2.exe

    c:\programdata\anaconda3\scripts\tflite_convert.exe

    c:\programdata\anaconda3\scripts\toco.exe

    c:\programdata\anaconda3\scripts\toco_from_protos.exe

Proceed (Y/n)? Y[A3] 

  Successfully uninstalled tensorflow-2.6.0[A4] 

(base) C:\Users\Administrator>pip install -i https://pypi.tuna.tsinghua.edu.cn/simple/ --upgrade tensorflow==2.0[A5] 

Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple/

Collecting tensorflow==2.0

  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/d3/af/296748d4c8d8987423231b93aecce5ab5952f6f2243cb6cedb88dd425397/tensorflow-2.0.0-cp36-cp36m-win_amd64.whl (48.1 MB)

     |████████████████████████████████| 48.1 MB 66 kB/s

Requirement already satisfied: six>=1.10.0 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (1.15.0)

Requirement already satisfied: keras-preprocessing>=1.0.5 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (1.1.2)

Collecting astor>=0.6.0

  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/c3/88/97eef84f48fa04fbd6750e62dcceafba6c63c81b7ac1420856c8dcc0a3f9/astor-0.8.1-py2.py3-none-any.whl (27 kB)

Requirement already satisfied: numpy<2.0,>=1.16.0 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (1.19.5)

Requirement already satisfied: absl-py>=0.7.0 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (0.13.0)

Requirement already satisfied: protobuf>=3.6.1 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (3.17.3)

Requirement already satisfied: wheel>=0.26 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (0.37.0)

Requirement already satisfied: opt-einsum>=2.3.2 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (3.3.0)

Requirement already satisfied: wrapt>=1.11.1 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (1.12.1)

Requirement already satisfied: grpcio>=1.8.6 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (1.39.0)

Collecting tensorflow-estimator<2.1.0,>=2.0.0

  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/fc/08/8b927337b7019c374719145d1dceba21a8bb909b93b1ad6f8fb7d22c1ca1/tensorflow_estimator-2.0.1-py2.py3-none-any.whl (449 kB)

     |████████████████████████████████| 449 kB 726 kB/s

Collecting keras-applications>=1.0.8

  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/71/e3/19762fdfc62877ae9102edf6342d71b28fbfd9dea3d2f96a882ce099b03f/Keras_Applications-1.0.8-py3-none-any.whl (50 kB)

     |████████████████████████████████| 50 kB 518 kB/s

Requirement already satisfied: google-pasta>=0.1.6 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (0.2.0)

Collecting tensorboard<2.1.0,>=2.0.0

  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/76/54/99b9d5d52d5cb732f099baaaf7740403e83fe6b0cedde940fabd2b13d75a/tensorboard-2.0.2-py3-none-any.whl (3.8 MB)

     |████████████████████████████████| 3.8 MB 6.8 MB/s

Requirement already satisfied: termcolor>=1.1.0 in c:\programdata\anaconda3\lib\site-packages (from tensorflow==2.0) (1.1.0)

Collecting gast==0.2.2

  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/4e/35/11749bf99b2d4e3cceb4d55ca22590b0d7c2c62b9de38ac4a4a7f4687421/gast-0.2.2.tar.gz (10 kB)

Requirement already satisfied: h5py in c:\programdata\anaconda3\lib\site-packages (from keras-applications>=1.0.8->tensorflow==2.0) (3.1.0)

Requirement already satisfied: requests<3,>=2.21.0 in c:\programdata\anaconda3\lib\site-packages (from tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (2.26.0)

Requirement already satisfied: werkzeug>=0.11.15 in c:\programdata\anaconda3\lib\site-packages (from tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (0.14.1)

Requirement already satisfied: markdown>=2.6.8 in c:\programdata\anaconda3\lib\site-packages (from tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (3.3.4)

Requirement already satisfied: setuptools>=41.0.0 in c:\programdata\anaconda3\lib\site-packages (from tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (58.0.2)

Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in c:\programdata\anaconda3\lib\site-packages (from tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (0.4.6)

Requirement already satisfied: google-auth<2,>=1.6.3 in c:\programdata\anaconda3\lib\site-packages (from tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (1.35.0)

Requirement already satisfied: cachetools<5.0,>=2.0.0 in c:\programdata\anaconda3\lib\site-packages (from google-auth<2,>=1.6.3->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (4.2.2)

Requirement already satisfied: rsa<5,>=3.1.4 in c:\programdata\anaconda3\lib\site-packages (from google-auth<2,>=1.6.3->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (4.7.2)

Requirement already satisfied: pyasn1-modules>=0.2.1 in c:\programdata\anaconda3\lib\site-packages (from google-auth<2,>=1.6.3->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (0.2.8)

Requirement already satisfied: requests-oauthlib>=0.7.0 in c:\programdata\anaconda3\lib\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (1.3.0)

Requirement already satisfied: importlib-metadata in c:\programdata\anaconda3\lib\site-packages (from markdown>=2.6.8->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (4.8.1)

Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in c:\programdata\anaconda3\lib\site-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (0.4.8)

Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\programdata\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (1.22)

Requirement already satisfied: certifi>=2017.4.17 in c:\programdata\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (2018.1.18)

Requirement already satisfied: idna<4,>=2.5 in c:\programdata\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (2.6)

Requirement already satisfied: charset-normalizer~=2.0.0 in c:\programdata\anaconda3\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (2.0.4)

Requirement already satisfied: oauthlib>=3.0.0 in c:\programdata\anaconda3\lib\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (3.1.1)

Requirement already satisfied: cached-property in c:\programdata\anaconda3\lib\site-packages (from h5py->keras-applications>=1.0.8->tensorflow==2.0) (1.5.2)

Requirement already satisfied: zipp>=0.5 in c:\programdata\anaconda3\lib\site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (3.5.0)

Requirement already satisfied: typing-extensions>=3.6.4 in c:\programdata\anaconda3\lib\site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard<2.1.0,>=2.0.0->tensorflow==2.0) (3.7.4.3)

Building wheels for collected packages: gast

  Building wheel for gast (setup.py) ... done

  Created wheel for gast: filename=gast-0.2.2-py3-none-any.whl size=7554 sha256=73d1a09d81caf3b49dbf72c4527e1e57773e29cae9413290207285dc08ba30be

  Stored in directory: c:\users\administrator\appdata\local\pip\cache\wheels\7f\29\33\39057a768652bcbf21c1eab7e81a9ac598c433ae5c0e0f7deb

Successfully built gast

Installing collected packages: tensorflow-estimator, tensorboard, keras-applications, gast, astor, tensorflow

  Attempting uninstall: tensorflow-estimator

    Found existing installation: tensorflow-estimator 2.6.0

    Uninstalling tensorflow-estimator-2.6.0:

      Successfully uninstalled tensorflow-estimator-2.6.0

  Attempting uninstall: tensorboard

    Found existing installation: tensorboard 2.6.0

    Uninstalling tensorboard-2.6.0:

      Successfully uninstalled tensorboard-2.6.0

  Attempting uninstall: gast

    Found existing installation: gast 0.4.0

    Uninstalling gast-0.4.0:

      Successfully uninstalled gast-0.4.0

Successfully installed astor-0.8.1 gast-0.2.2 keras-applications-1.0.8 tensorboard-[A6] 2.0.2 tensorflow-2.0.0 tensorflow-estimator-2.0.1

1. 到这里还没有结束 由于是windows 的原因还需要 下载Visual Studio 2019

处理问题的网站：

https://blog.youkuaiyun.com/qq_36853469/article/details/105864905

以下网站是：

电脑无法下载Visual Studio 2019 ，无法打开上面网站的解决办法

https://blog.youkuaiyun.com/qq_36286039/article/details/112598556

Visual Studio 2019安装教程：

https://www.cnblogs.com/vs2019anzhuang/p/13382995.html

1. 安装期间 不需要全部选上 只需要选上 python开发模块即可

（如果你内存空间很大就当我没说）

1. 当安装完成后 回到一开始的黑框框 先输入 python 再输入：

import tensorflow as tf

hello = tf.constant(' Tensorflow YYDS!')

sess = tf.Session()

print(sess.run(hello))

如果显示:  b' Tensorflow YYDS!'

那就完全成功了！

代码历程如下：

(base) C:\Users\Administrator>python[A7] 

Python 3.6.4 |Anaconda, Inc.| (default, Jan 16 2018, 10:22:32) [MSC v.1900 64 bit (AMD64)] on win32

Type "help", "copyright", "credits" or "license" for more information.

>>> import tensorflow as tf[A8] 

>>> hello = tf.constant(' Tensorflow YYDS!')

>>> sess = tf.Session()

2021-09-07 14:39:55.726359: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

2021-09-07 14:39:55.737784: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

2021-09-07 14:39:55.750227: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

2021-09-07 14:39:55.771536: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

2021-09-07 14:39:55.793186: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

2021-09-07 14:39:55.819987: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

2021-09-07 14:39:55.838157: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

2021-09-07 14:39:55.858872: W c:\l\tensorflow_1501918863922\work\tensorflow-1.2.1\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.

>>> print(sess.run(hello))

b' Tensorflow YYDS!'

>>>

---

 [A1]这是为了 更新 pip

 [A2]将之前 安装错误的先清楚掉

 [A3]

 [A4]成功标志

 [A5]开始 正式安装

 [A6]成功标准

 [A7]进入python 环境

 [A8]将代码 复制粘贴 进入即可