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https://issues.apache.org/jira/browse/YARN-8220?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16498365#comment-16498365
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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:
{code}
{
..
"launch_command":"--train-steps=10000,--trans-batch-size=16"
..
}
{code}
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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