使用每晚的TensorFlow构建进行Cloud ML Engine培训 [英] Using a nightly TensorFlow build for training with Cloud ML Engine

问题描述

如果我需要在Cloud ML Engine培训工作中使用每晚的TensorFlow构建，该怎么办?

If I need to use a nightly TensorFlow build in a Cloud ML Engine training job, how do I do it?

推荐答案

• 从 https://github.com/tensorflow/tensorflow#installation . 如何选择合适的版本:

  • Download a nightly build from https://github.com/tensorflow/tensorflow#installation. How to pick the right build:

    • 根据是否需要使用GPU进行培训，使用仅Linux CPU"或"Linux GPU"
    • 使用Python 2构建.

    重命名.whl文件，例如

    Rename the .whl file, for example

    
    mv tensorflow-1.0.1-cp27-cp27mu-linux_x86_64.whl \
       tensorflow-1.0.1-cp27-none-linux_x86_64.whl
    

    (这里我们将cpu27mu重命名为none.Pip解析该部分以检测.whl软件包是否适合平台，但是该特定名称在某些较早版本的pip上不起作用)

    (here we renamed the cpu27mu to none. Pip parses that part to detect whether a .whl package is suitable for a platform, but that particular name doesn't work on some older versions of pip)

    将.whl文件上传到GCS并将其指定为package_uris之一 提交Cloud ML Engine培训作业时.

    Upload the .whl file to GCS and specify it as one of the package_uris when submitting a Cloud ML Engine training job.

    请注意，除了使用夜间构建外，您还可以按照 https://中所述从源代码构建TensorFlow. www.tensorflow.org/install/install_sources .

    Note that instead of using a nightly build you can also build TensorFlow from source as described in https://www.tensorflow.org/install/install_sources.

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