我也遇到过同样的问题，我用这个方法解决了:

# Ubuntu/Linux 64-bit, CPU only, Python 2.7
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp27-none-linux_x86_64.whl

# Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Installing from sources" below.

# Mac OS X, CPU only, Python 2.7:
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.1-py2-none-any.whl

# Mac OS X, GPU enabled, Python 2.7:
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow_gpu-0.12.1-py2-none-any.whl

# Ubuntu/Linux 64-bit, CPU only, Python 3.4
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp34-cp34m-linux_x86_64.whl

# Ubuntu/Linux 64-bit, GPU enabled, Python 3.4
# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Installing from sources" below.
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp34-cp34m-linux_x86_64.whl

# Ubuntu/Linux 64-bit, CPU only, Python 3.5
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp35-cp35m-linux_x86_64.whl

# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Installing from sources" below.
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp35-cp35m-linux_x86_64.whl

# Mac OS X, CPU only, Python 3.4 or 3.5:
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.1-py3-none-any.whl

# Mac OS X, GPU enabled, Python 3.4 or 3.5:
(tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow_gpu-0.12.1-py3-none-any.whl

加:

# Python 2
(tensorflow)$ pip install --upgrade $TF_BINARY_URL

# Python 3
(tensorflow)$ pip3 install --upgrade $TF_BINARY_URL

在Docs上找到。

更新!

有新版本的新链接

例如，要在OSX中安装tensorflow v1.0.0，你需要使用:

https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.0.0-py2-none-any.whl

而不是

https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.1-py2-none-any.whl

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

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

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

如果你正在使用Anaconda Python安装，pip install tensorflow将给出上面所述的错误，如下所示:

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

根据TensorFlow安装页面，当运行pip install时，你需要使用——ignore-installed标志。

然而，在此之前，请参阅此链接 确保TF_BINARY_URL变量与你想要安装的TensorFlow版本相关的设置正确。

2019年更新: 为了在谷歌Colab中安装TensorFlow 2预览版，您可以使用:

!wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda-repo-ubuntu1604-10-0-local-10.0.130-410.48_1.0-1_amd64 -O cuda-repo-ubuntu1604-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
!dpkg -i cuda-repo-ubuntu1604-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
!apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub
!apt-get update
!apt-get install cuda
!pip install tf-nightly-gpu-2.0-preview

为了安装TensorFlow 2 bye pip，你可以使用: 为GPU安装tf-night - GPU -2.0-preview PIP安装tf-night -2.0-preview CPU。