我知道这个问题很老了，但最近我在MacBook Air M1上遇到了这个问题。解决方案是使用pip install tensorflow-macos命令。

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

通过勾选“添加python到路径”来安装python Pip3安装——升级https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.0-py3-none-any.whl

这适用于windows 10.0

这个问题有很多种答案。这个答案旨在概括一组答案:

可能没有一个TensorFlow版本与你的Python版本兼容。如果您使用的是Python的新版本，这一点尤其正确。例如，在Python的新版本发布和该版本的Python的TensorFlow发布之间可能会有延迟。

在这种情况下，我相信你的选择是:

升级或降级到不同版本的Python。(虚拟环境很好，例如conda install python=3.6) 选择与你的python版本兼容的特定版本的tensorflow，例如，如果你仍在使用python3.4: pip install tensorflow==2.0 从源代码编译TensorFlow。 等待一个与你的Python版本兼容的TensorFlow的新版本。

以下是我为Windows 10所做的!我也没有打扰之前的Python 2.7安装

步骤1:从链接安装Windows x86-64可执行安装程序: https://www.python.org/downloads/release/python-352/

步骤2:以管理员身份打开cmd

步骤3:输入以下命令:

pip install https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-0.12.0rc0-cp35-cp35m-win_amd64.whl

您应该看到它可以正常工作，如下图所示，我还尝试了示例示例。

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