我发现TensorFlow 1.12.0只适用于Python 3.5.2版本。我用的是Python 3.7，但它不起作用。所以，我不得不降级Python，然后我可以安装TensorFlow让它工作。

将python版本从3.7降级到3.6

conda install python=3.6.8

为了解决这个错误，你可能需要先升级pip，然后安装TensorFlow，如下所示

# Requires the latest pip
pip install --upgrade pip

# Current stable release for CPU and GPU
pip install tensorflow

如果你使用蟒蛇提示，那么试试这个

conda install -c anaconda tensorflow-gpu

试试这个:

export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.1-py3-none-any.whl
pip3 install --upgrade $TF_BINARY_URL

来源:https://www.tensorflow.org/get_started/os_setup(页面已不存在)

更新2/23/17 文档移至:https://www.tensorflow.org/install

使用Git更容易，他们提供了网站上的方法，但链接访问可能不是很重要，你可以从中读取

引用https://www.tensorflow.org/install/source_windows

git clone https://github.com/tensorflow/tensorflow.git

我的Python版本是3.9.7。我也使用Windows 10，要求如下:

1. Microsoft C++ Retribution installed from Microsoft Visual Studio that matches with x64bits as required in the list.

1.1 Microsoft Visual C++ 2012 Redistribution ( x64 ) and updates    
1.2 Microsoft Visual C++ 2013 Redistributable (x64) - 12.0.40664
1.3 Microsoft Visual C++ 2015-2019 Redistributable (x64) - 14.29.30133
1.4 vs_community__1795732196.1624941787.exe updates

2. Python and AI learning 
tensorboard                2.6.0
tensorboard-data-server    0.6.1
tensorboard-plugin-profile 2.5.0
tensorboard-plugin-wit     1.8.0
***tensorflow                 2.6.0
tensorflow-datasets        4.4.0
tensorflow-estimator       2.6.0
***tensorflow-gpu             2.6.0
tensorflow-hub             0.12.0
tensorflow-metadata        1.2.0
tensorflow-text            2.6.0
***PyOpenGL                   3.1.5
pyparsing                  2.4.7
python-dateutil            2.8.2
python-slugify             5.0.2
python-speech-features     0.6
PyWavelets                 1.1.1
PyYAML                     5.4.1
scikit-image               0.18.3
scikit-learn               1.0.1
***gym                        0.21.0

2.0兼容方案:

在终端(Linux/MacOS)或命令提示符(Windows)中执行以下命令，使用Pip安装Tensorflow 2.0:

#Install tensorflow using pip virtual env 
pip install virtualenv
virtualenv tf_2.0.0   # tf_2.0.0 is virtual env name
source tf_2.0.0/bin/activate
#You should see tf_2.0.0 Env now. Execute the below steps
pip install tensorflow==2.0.0
python
>>import tensorflow as tf
>>tf.__version__
2.0.0

在终端(Linux/MacOS)或命令提示符(Windows)中执行以下命令，使用Bazel安装Tensorflow 2.0:

git clone https://github.com/tensorflow/tensorflow.git
cd tensorflow

#The repo defaults to the master development branch. You can also checkout a release branch to build:
git checkout r2.0

#Configure the Build => Use the Below line for Windows Machine
python ./configure.py 

#Configure the Build => Use the Below line for Linux/MacOS Machine
./configure
#This script prompts you for the location of TensorFlow dependencies and asks for additional build configuration options. 

#Build Tensorflow package

#CPU support
bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package 

#GPU support
bazel build --config=opt --config=cuda --define=no_tensorflow_py_deps=true //tensorflow/tools/pip_package:build_pip_package

如果你最近遇到了这个问题(比如，在2018年Python 3.7发布之后)，这很可能是由于tensorflow方面缺乏Python 3.7支持造成的。如果您不介意，可以尝试使用Python 3.6。你可以从https://github.com/tensorflow/tensorflow/issues/20444上找到一些技巧，但使用它们的风险由你自己承担。我使用了harpone建议的方法——首先下载Python 3.6的tensorflow wheel，然后手动重命名它……

cp tensorflow-1.11.0-cp36-cp36m-linux_x86_64.whl tensorflow-1.11.0-cp37-cp37m-linux_x86_64.whl
pip install tensorflow-1.11.0-cp37-cp37m-linux_x86_64.whl

好消息是，已经有了3.7支持的pull请求。希望能尽快发布。