Add more AI/ML Training Example with Kubeflow Trainer

[andreyvelich]

As we discussed previously: #2021 (comment) we want to add more AI/ML examples to the Kubeflow Trainer.

We can make these examples Data Scientists friendly and re-use our Python SDK within Jupyter Notebooks to simplify the user submission.
I like the example structure of HF Transformers, so I propose the following path: examples/<framework>/<ml-use-case>

We can start with these examples (feel free to add more ML use-cases in this issue):

• Language Modeling
• Image Classification
• Text Classification
• Audio Classification
• Question Answering
• Speech Recognition
• Text Generation
• FSDP Example with PyTorch

We should investigate how to configure our CI/CD to make sure that these examples are functional.

cc @kuizhiqing @johnugeorge @tenzen-y @kubeflow/wg-training-leads

/help
/good-first-issue
/area example

[google-oss-prow]

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Details

In response to this:

As we discussed previously: #2021 (comment) we want to add more AI/ML examples to the Kubeflow Training Operator. Right now, most of our examples have very basic and simple CNN training for MNIST. Since Training Operator is capable to train large-scale ML models, we would like to contribute more AI/ML use-cases.

We can make these examples Data Scientists friendly and re-use our Python SDK within Jupyter Notebooks to simplify the user submission.
I like the example structure of HF Transformers, so I propose the following path: examples/<framework>/<ml-use-case>

We can start with these examples (feel free to add more ML use-cases in this issue):

• Language Modeling
• Image Classification
• Text Classification
• Audio Classification
• Question Answering
• Speech Recognition
• Text Generation

We should investigate how to configure our CI/CD to make sure that these examples are functional.

cc @kuizhiqing @johnugeorge @tenzen-y

/help
/good-first-issue
/area example

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[xr-dev-saurabh]

/assign

[StefanoFioravanzo]

@andreyvelich I love this. Few thoughts:

• Whenever we publish a new example, please reach out to me or Amber so that we can help turning it into either a short blog post or at least disseminate via social media.
• How do you define the actual use case for these topics?
• Are these examples supposed to be specific to the training operator or were you thinking of a wider applicability (serving, tuning, metadata, etc.)

[github-actions]

This issue 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.

[andreyvelich]

/remove-lifecycle stale

[github-actions]

This issue 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.

[andreyvelich]

/remove-lifecycle stale