从今天开始，如果还有人想知道， Python >= 3.9也会导致同样的问题 卸载python 3.9，然后安装3.8，应该会解决这个问题

我也面临着同样的问题。我尝试了下面的方法，它奏效了。 安装Mac OS X, anaconda python 2.7

PIP卸载tensorflow export TF_BINARY_URL=<从http://tflearn.org/installation/>得到正确的url pip install——upgrade $TF_BINARY_URL

安装tensorflow-1.0.0

我发现了问题所在。

我使用的是一台Windows电脑，之前已经安装了Python 2。 安装Python 3后(没有设置路径，我成功检查了pip3的版本-但Python可执行文件仍然指向Python2)

然后我将路径设置为python3可执行文件(删除所有python2路径)，然后启动一个新的命令提示符，尝试重新安装Tensorflow。它的工作原理!

我认为这个问题也可能发生在MAC OS上，因为MAC系统上有一个默认的python。

对于窗户，这个方法对我很有效，

从这个链接下载车轮。然后从命令行导航到车轮所在的下载文件夹，只需键入以下命令-

PIP安装tensorflow-1.0.0-cp36-cp36m-win_amd64.whl

我的环境:Win 10, python 3.6

pip3 install --upgrade tensorflow
pip install --upgrade tensorflow

错误:

> Collecting tensorflow Could not find a version that satisfies the
> requirement tensorflow (from versions: ) No matching distribution
> found for tensorflow

我还尝试了pip install tensorflow和pip install tensorflow-gpu。 但错误:

> Could not find a version that satisfies the requirement tensorflow (from versions: ) No matching distribution found for tensorflow
> Could not find a version that satisfies the requirement tensorflow-gpu (from versions: ) No matching distribution found for tensorflow-gpu

使用Step (https://www.tensorflow.org/install/install_windows)尝试安装OK

Follow the instructions on the Anaconda download site to download and install Anaconda. https://www.continuum.io/downloads Create a conda environment named tensorflow by invoking the following command: C:> conda create -n tensorflow pip python=3.5 Activate the conda environment by issuing the following command: C:> activate tensorflow (tensorflow)C:> # Your prompt should change Issue the appropriate command to install TensorFlow inside your conda environment. To install the CPU-only version of TensorFlow, enter the following command: (tensorflow)C:> pip install --ignore-installed --upgrade tensorflow To install the GPU version of TensorFlow, enter the following command (on a single line): (tensorflow)C:> pip install --ignore-installed --upgrade tensorflow-gpu

你可以试试这个

pip install --upgrade tensorflow