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From "Eric Yang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-8220) Running Tensorflow on YARN with GPU and Docker - Examples
Date Fri, 01 Jun 2018 18:15:00 GMT

    [ https://issues.apache.org/jira/browse/YARN-8220?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16498365#comment-16498365

Eric Yang commented on YARN-8220:

[~leftnoteasy] {quote}
Entry point is a nice feature for static command. (For example default TF docker image which
start notebook by default: https://github.com/tensorflow/tensorflow/tree/r1.8/tensorflow/tools/docker).

For training program, since user need to do a lot of hyper parameter tuning, user will update
such parameters to make it work.{quote}

Additional parameters can pass to ENTRYPOINT via CMD, which is same as specifying it in launch_command,
if ENTRYPOINT is in use.  Yarnfile is shorten to:


Or any parameters that has not been specified in ENTRYPOINT+CMD combination.

> Running Tensorflow on YARN with GPU and Docker - Examples
> ---------------------------------------------------------
>                 Key: YARN-8220
>                 URL: https://issues.apache.org/jira/browse/YARN-8220
>             Project: Hadoop YARN
>          Issue Type: Sub-task
>          Components: yarn-native-services
>            Reporter: Sunil Govindan
>            Assignee: Sunil Govindan
>            Priority: Critical
>         Attachments: YARN-8220.001.patch
> Tensorflow could be run on YARN and could leverage YARN's distributed features.
> This spec fill will help to run Tensorflow on yarn with GPU/docker

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