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RFC: Add a new command for generating example TFjobs #509

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merged 1 commit into from
Mar 30, 2018

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mitake
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@mitake mitake commented Mar 28, 2018

This command adds a new command genjob to hack/ directory. The command
generates TFJobs for testing purpose. Currently the generated jobs are
following the definitions of examples/tf_job.yaml and
examples/tf_job_gpu.yaml.

Example usage (generating 30 TFJobs):

$ ./genjob --kube-config-path ~/.kube/config --nr-tfjobs 30 --use-gpu --scheduler-name tfjob

I think the command is useful for testing tf-operator and kube-batchd. The remaining major todo is adding more realistic TFJob (especially distributed examples).


This change is Reviewable

This command adds a new command genjob to hack/ directory. The command
generates TFJobs for testing purpose. Currently the generated jobs are
following the definitions of examples/tf_job.yaml and
examples/tf_job_gpu.yaml.

Example usage:
```
$ ./genjob --kube-config-path ~/.kube/config --nr-tfjobs 30 --use-gpu --scheduler-name tfjob
```
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coveralls commented Mar 28, 2018

Coverage Status

Coverage remained the same at 45.323% when pulling 7cb420f on mitake:genjob into 6214e56 on kubeflow:master.

@gaocegege
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gaocegege commented Mar 28, 2018

/ok-to-test

I like the idea!

Thanks for your contribution!

@ankushagarwal ankushagarwal removed their request for review March 29, 2018 07:42
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mitake commented Mar 30, 2018

/assign @gaocegege

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/lgtm

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[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: gaocegege

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@k8s-ci-robot k8s-ci-robot merged commit c69acf8 into kubeflow:master Mar 30, 2018
@mitake mitake deleted the genjob branch March 30, 2018 02:56
jetmuffin pushed a commit to jetmuffin/tf-operator that referenced this pull request Jul 9, 2018
This command adds a new command genjob to hack/ directory. The command
generates TFJobs for testing purpose. Currently the generated jobs are
following the definitions of examples/tf_job.yaml and
examples/tf_job_gpu.yaml.

Example usage:
```
$ ./genjob --kube-config-path ~/.kube/config --nr-tfjobs 30 --use-gpu --scheduler-name tfjob
```
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4 participants