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https://issues.apache.org/jira/browse/YARN-8220?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16498270#comment-16498270
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Wangda Tan commented on YARN-8220:
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Thanks [~eyang] for your comments,
For your comments:
bq. 1. Avoid using bash style launch command
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.
bq. 2. It might be good to show case some yarnfile features:
We intentionally want to avoid user specify this. It is a burden for user to
specify such mounting. In side submit_tf.py, we use the feature you mentioned.
bq. 3. Downloading source code from individual github contributors might be
risky and prone to break
This is a good suggestion, will check if it is possible to commit example code
to sub folder of this example.
> 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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