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Skip flaky e2e MultiKueue test for XGBoost #2861

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merged 2 commits into from
Aug 21, 2024
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Skip flaky e2e MultiKueue test for XGBoost #2861

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Skip flaky e2e multikueue test for XGBoost
mszadkow Aug 20, 2024
2f3240e
add comment with the link issue
mszadkow Aug 21, 2024
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2 changes: 2 additions & 0 deletions test/e2e/multikueue/e2e_test.go
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Expand Up @@ -633,6 +633,8 @@ var _ = ginkgo.Describe("MultiKueue", func() {
})

ginkgo.It("Should run a kubeflow XGBoostJob on worker if admitted", func() {
// Skipped due to known bug - https://github.com/kubeflow/training-operator/issues/1711
ginkgo.Skip("Skipped due to state transitioning bug in training-operator")
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Put a comment with a link to the open issue in the training-operator repo

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I agree and I would have done that, but they don't have actual issue open, just the reference - kubeflow/training-operator#1711

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Let's use that issue

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I believe that only PyTorchJob e2e would be enough since we already commonized the KFJobs MK adapters into the kubeflowjob.MKAdapter in #2795.

So, after we merge this PR, can you refactor the e2e and integration tests for the KFJob MK adapter?

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Ok, then I will use this.
@tenzen-y Yes I will publish the test refactor - I pretty much have it.

// Since it requires 1.5 CPU, this job can only be admitted in worker 1.
xgboostJob := testingxgboostjob.MakeXGBoostJob("xgboostjob1", managerNs.Name).
Queue(managerLq.Name).
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