问题描述
Datalab目前似乎正在运行0.6.0。我想更新到0.8.0版本我做了：
！pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-linux_x86_64
我得到：
SSLError：[SSL：CERTIFICATE_VERIFY_FAILED]证书验证失败（_ssl.c：581）
在/root/.pip/pip.log存储调试日志失败
我该如何解决这个问题？
不建议更新已安装的软件包在Datalab中默认。这是为了确保您不会破坏Datalab环境。
ul>如果您使用，请访问页面并提交问题以获得新版本的datalab已经发布。在github上的Datalab源代码中，tensorflow的版本是0.8.0）
如果您已经在本地安装了Datalab，或者在GCE上安装了Datalab，那么只需重新构建Datalab图像得到张量流0.8.0。有关详细信息，请参阅。
如果您想暂时将较新版本安装到您现有的环境中进行测试（尽管这不推荐），那么您可以尝试使用no dependencies选项（--no-deps）安装tensorflow以减少打破正在运行的datalab环境的机会。
%% bash
wget https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-linux_x86_64.whl&& pip install --ignore-installed --no-deps tensorflow-0.8.0-cp27-none-linux_x86_64.whl
在运行上述命令后，我可以看到tensorflow的版本是0.8.0。
>>导入tensorflow
>> tensorflow .__ version__
'0.8.0'
>>！pip显示张量流
---
---
元数据版本： 2.0
名称：tensorflow
版本：0.8.0
简介：TensorFlow帮助张量流动
主页：http://tensorflow.org/
作者： Google Inc.
作者信箱：[email protected]
安装者：pip
许可证：Apache 2.0
位置：/usr/local/lib/python2.7/dist-包
需要：six，protobuf，wheel，numpy
请留意任何现在您已经更新了datalab使用的软件包的异常情况。例如，某些样本笔记本可能无法工作。另请注意，此设置可能不受支持。例如，您可能会遇到与更新datalab使用的软件包有直接关系的问题。在这种情况下，解决方案可能是恢复更新的软件包并查看是否解决了您的问题。
Datalab currently seems to be running 0.6.0. I wanted to update to version 0.8.0
I did:
!pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-linux_x86_64
I got:
SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:581)
Storing debug log for failure in /root/.pip/pip.log
How can I fix this?
It is not recommended to update packages which are installed in Datalab by default. This is to ensure that you do not break a working Datalab environment.
Please try one of the following solutions:
If you deployed Datalab using https://datalab.cloud.google.com/ , visit the Datalab GitHub Issues page and submit an issue to have a new version of datalab published. In the Datalab source code on github, tensorflow is at version 0.8.0)
If you have installed Datalab locally, or on GCE, then simply rebuild the Datalab image to get tensorflow 0.8.0 . See the Datalab Getting Started Wiki page for more information.
If you want to temporarily install a newer version into your existing environment for testing purposes (although this isn't recommended) , then you could try installing tensorflow with the no dependencies option (--no-deps) in order to reduce the chance of breaking the working datalab environment.
%%bash
wget https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-linux_x86_64.whl && pip install --ignore-installed --no-deps tensorflow-0.8.0-cp27-none-linux_x86_64.whl
After running the above command, I can see tensorflow is at version 0.8.0.
>> import tensorflow
>> tensorflow.__version__
'0.8.0'
>>!pip show tensorflow
---
---
Metadata-Version: 2.0
Name: tensorflow
Version: 0.8.0
Summary: TensorFlow helps the tensors flow
Home-page: http://tensorflow.org/
Author: Google Inc.
Author-email: [email protected]
Installer: pip
License: Apache 2.0
Location: /usr/local/lib/python2.7/dist-packages
Requires: six, protobuf, wheel, numpy
Please keep an eye out for any anomalies now that you have updated a package used by datalab. For example, certain sample notebooks may not work. Also, please note that this setup may not be supported. For example, you may encounter an issue which is directly related to updating a package used by datalab. In that case, the solution may be to revert the updated package and see if that resolves your issue.
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