Question

之前我已经在Ubuntu 16.04上为Python 2.7安装了来自source的tensorflow，它运行良好。

对于Python 3.5（我创建了一个新的anaconda环境），我安装了一个二进制版本，但是我收到了警告信息..

编辑，使用下载的二进制轮，我得到的消息是......

W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:910] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero

...并且代码似乎运行速度明显慢于使用我的本机编译的py27运行。

所以，我卸载了“旧的”tensorflow二进制文件（对于py35），并通过the Tensorflow Install from Sources page的说明，安装了所有软件包，运行./configure，将其指向正确版本的python（〜/ anaconda2 / envs / py35 / bin / python及其相应的库路径），选择了我的CUDA选项，一直到最后都没有错误构建...

在最后一步，它告诉我“这个平台上没有支持的轮子” - 你的意思是我刚建立的平台？

$ ./configure
...
$ bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package 
...
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
Thu Mar 9 23:17:35 CST 2017 : === Using tmpdir: /tmp/tmp.RrsUxPKxFg
~/tmp/tensorflow/bazel-bin/tensorflow/tools/pip_package/build_pip_package.runfiles ~/tmp/tensorflow
~/tmp/tensorflow
/tmp/tmp.RrsUxPKxFg ~/tmp/tensorflow
Thu Mar 9 23:17:36 CST 2017 : === Building wheel
~/tmp/tensorflow
Thu Mar 9 23:17:45 CST 2017 : === Output wheel file is in: /tmp/tensorflow_pkg
$ sudo -H pip install /tmp/tensorflow_pkg/tensorflow-1.0.1-cp35-cp35m-linux_x86_64.whl 
tensorflow-1.0.1-cp35-cp35m-linux_x86_64.whl is not a supported wheel on this platform.

以下是一些检查......

$ python --version
Python 3.5.3 :: Continuum Analytics, Inc.
$ which python
/home/myusername/anaconda2/envs/py35/bin/python
$ which pip
/home/myusername/anaconda2/envs/py35/bin/pip
$ pip install --upgrade pip
Requirement already up-to-date: pip in /home/myusername/anaconda2/envs/py35/lib/python3.5/site-packages
$

有人可以提出建议吗？

我已经看过关于问题的各种帖子了。 “不支持的轮子”，人们正在使用与正确版本的python不匹配的下载二进制轮（例如cp34 vs cp35），以及关于在Windows上从源安装的帖子，但没有看过像我这样的帖子：涉及安装来源，在Linux上更正Python的“匹配”版本。检查了Github问题的张力流，也没有看到这个。

Answer 1

运行git push --force安装已编译的PIP包导致此错误。 Anaconda使用虚拟环境，该环境覆盖sudo -H pip install ...可执行文件的路径。但是，pip命令does not preserve the user's $PATH environment variable，sudo将使用系统安装的sudo -H pip install ...，在这种情况下，它对应于不同版本的Python。

幸运的是，如果您使用的是Anaconda，则无需使用pip来运行sudo，因为整个环境都存储在您的用户拥有的目录中。

从源头安装Tensorflow py3.5：“不支持轮子”？

1 个答案: