Kubeflow e2e example

[Tomcli]

Which issue is resolved by this Pull Request:
Resolves #

Description of your changes:

This Kubeflow e2e example demonstrates how to use katib + tfjob + kfserving with volumeop using distributed training. To run this pipeline, make sure your cluster has at least 16 cpu and 32GB in total. Otherwise some jobs might not able to run because TFJob needs to run 4 TensorFlow pods in parallel for distributed training.

Environment tested:

• Python Version (use python --version): 3.6.4
• Tekton Version (use tkn version): 0.11.3
• Kubernetes Version (use kubectl version): 1.16
• OS (e.g. from /etc/os-release):

[kubeflow-bot]

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[fenglixa]

Oh, seems we are working on same item, I am also worked out this item, but found this ticket.

[ckadner]

/area example

[animeshsingh]

@Tomcli @fenglixa are we good to go with this?

[Tomcli]

@fenglixa do you want to add anything to this example?

[fenglixa]

No, it's OK to me, Thanks @Tomcli
/lgtm

[animeshsingh]

@Tomcli if its end-to-end, why we still call it e2e-katib?

[Tomcli]

Sorry for the confusion. I renamed it to e2e-mnist to align with the Kubeflow pipeline naming.

[animeshsingh]

thanks
/lgtm
/approve

[k8s-ci-robot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: animeshsingh

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