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https://issues.apache.org/jira/browse/YARN-8220?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16507542#comment-16507542
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Eric Yang commented on YARN-8220:
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[~leftnoteasy] Launch_command containers environment variables and Hadoop
versions that have better ways to be handled with care. As soon as Hadoop
version changes, the launch_command is out dated, and manual care is required
to clean up the messy code. I don't think this is a good idea to ignore
ENTRYPOINT advice.
> 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, YARN-8220.002.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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