我正在尝试使用pip安装TensorFlow:
$ pip install tensorflow --user
Collecting tensorflow
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow
我做错了什么?到目前为止,我使用Python和pip没有任何问题。
我正在尝试使用pip安装TensorFlow:
$ pip install tensorflow --user
Collecting tensorflow
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow
我做错了什么?到目前为止,我使用Python和pip没有任何问题。
当前回答
我可以在我的Mac上安装tensorflow-macos和tensrflow-metal
$ python -m pip install -U pip
$ pip install tensorflow-macos
$ pip install tensorflow-metal
其他回答
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
如果你的命令pip install——upgrade tensorflowcompililes,那么你的tensorflow版本应该是最新的。我个人更喜欢用水蟒。tensorflow可以简单地安装和升级:
conda install -c conda-forge tensorflow # to install
conda upgrade -c conda-forge tensorflow # to upgrade
另外,如果你想用你的GPU使用它,你有一个简单的安装:
conda install -c anaconda tensorflow-gpu
我已经用了一段时间了,从来没有任何问题。
摘自tensorflow网站 https://www.tensorflow.org/install/install_windows
Installing with native pip If the following version of Python is not installed on your machine, install it now: Python 3.5.x from python.org TensorFlow only supports version 3.5.x of Python on Windows. Note that Python 3.5.x comes with the pip3 package manager, which is the program you'll use to install TensorFlow. To install TensorFlow, start a terminal. Then issue the appropriate pip3 install command in that terminal. To install the CPU-only version of TensorFlow, enter the following command:
C:\> pip3 install --upgrade tensorflow
To install the GPU version of TensorFlow, enter the following command:
C:\> pip3 install --upgrade tensorflow-gpu
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。
如果您尝试了上面的解决方案,但没有解决问题,可能是因为版本不一致。
我安装了python 3.9,无法用pip安装tensorflow。
然后我卸载了3.9,然后安装了3.8.7,成功…tensorflow支持的最大版本是3.8。X(2021年) 所以,检查你的python版本是否与当前的tensorflow兼容。