Create Pytorch Informer/ClientSet

[migueltol22]

What this PR does / why we need it:
This PR runs code generator to create a pytorch client and informer.

Which issue(s) this PR fixes Fixes #1499

Checklist:

• Docs included if any changes are user facing

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[google-oss-prow]

[APPROVALNOTIFIER] This PR is NOT APPROVED

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[migueltol22]

@terrytangyuan here is an example of the conflicting import mentioned in this comment

[gaocegege]

Could you please also add XGBoostJob, MXNetJob, and MPIJob?

[migueltol22]

Could you please also add XGBoostJob, MXNetJob, and MPIJob?

Added all 3. Although the imports aliases conflict with each other. @gaocegege do you happen to know what's needed to resolve this or is the expectation to manually resolve them?

[migueltol22]

@gaocegege This is the issue I mentioned with the imports. I'm not sure if I missed something or I should manually fix them?

[gaocegege]

Oh, get it.

[gaocegege]

Ref kubernetes/code-generator#135

[cheimu]

I'm extremely curious, will this pr continue to update? If possible, I'd like to help : )

[cheimu]

Ref kubernetes/code-generator#135

I also think the problem is this groupName. See mpi group name, mxnet group name, pytorch group name, tensorflow group name and xgb group name: they are all kubeflow.org. I think there could be two solutions for it.

1. Our hierarchy is /pkg/apis/<ml_framework_x>/<version>/ml_framework_x_type.go, where in fact, each ml framework actually is a subgroup, so if we can add one more subgroupName to the groupName, such as tfjob.kubeflow.org, then packing collision could be fixed.
2. Like other projects, we change the hierarchy to /pkg/apis/<version>/<ml_framework_x>_type.go where they all span in same directory meaning they are in same subgroup, then when generating clientset informer, they will be in the same package.

@gaocegege @zw0610 what do you guys think? 🤔 If so, tons of work will need to adapt it I guess

[zw0610]

Ref kubernetes/code-generator#135

I also think the problem is this groupName. See mpi group name, mxnet group name, pytorch group name, tensorflow group name and xgb group name: they are all kubeflow.org. I think there could be two solutions for it.

1. Our hierarchy is /pkg/apis/<ml_framework_x>/<version>/ml_framework_x_type.go, where in fact, each ml framework actually is a subgroup, so if we can add one more subgroupName to the groupName, such as tfjob.kubeflow.org, then packing collision could be fixed.
2. Like other projects, we change the hierarchy to /pkg/apis/<version>/<ml_framework_x>_type.go where they all span in same directory meaning they are in same subgroup, then when generating clientset informer, they will be in the same package.

@gaocegege @zw0610 what do you guys think? 🤔 If so, tons of work will need to adapt it I guess

The second option looks more authentic to me.

[Arhell]

/ok-to-test

[johnugeorge]

We can close this PR as #1610 is merged

[github-actions]

This pull request has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

[tenzen-y]

/close

[google-oss-prow]

@tenzen-y: Closed this PR.

In response to this:

/close

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