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Andrey VelichkevichandGitHub
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* Add Katib ROADMAP 2022/2023 * Add multi-objective optimization * Add Scalability Improvements * Remove Katib CRD naming
4.5 KiB
4.5 KiB
Katib 2022/2023 Roadmap
AutoML Features
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Support advance HyperParameter tuning algorithms:
-
Support multi-objective optimization - #1549
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Support various HP distributions (log-uniform, uniform, normal) - #1207
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Support Auto Model Compression - #460
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Support Auto Feature Engineering - #475
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Improve Neural Architecture Search design
Backend and API Enhancements
- Conformance tests for Katib - #2044
- Support push-based metrics collection in Katib - #577
- Support PostgreSQL as a Katib DB - #915
- Improve Katib scalability - #1847
- Promote Katib APIs to the
v1version - Support multiple CRD versions (
v1beta1,v1) with conversion webhook
Improve Katib User Experience
- Simplify Katib Experiment creation with Katib SDK - #1951
- Fully migrate to a new Katib UI - Project 1
- Expose Trial logs in Katib UI - #971
- Enhance Katib UI visualization metrics for AutoML Experiments
- Improve Katib Config UX - #2150
Integration with Kubeflow Components
- Kubeflow Pipeline as a Katib Trial target - #1914
- Improve data passing when Katib Experiment is part of Kubeflow Pipeline - #1846
History
Katib 2021 Roadmap
New Features
AutoML
- Support Population Based Training #1382
- Support ASHA
- Support Auto Model Compression #460
- Support Auto Feature Engineering #475
- Various CRDs for HP, NAS and other AutoML techniques.
UI
- Migrate to the new Katib UI Project 1
- Hyperparameter importances visualization with fANOVA algorithm
Enhancements
- Finish AWS CI/CD migration
- Support various parameter distribution #1207
- Finish validation for Algorithms #1126
- Refactor Hyperband #1389
- Support multiple CRD version with conversion webhook
- MLMD integration with Katib Experiments
Katib 2020 Roadmap
New Features
Hyperparameter Tuning
- Support Early Stopping #692
Neural Architecture Search
- Support Advanced NAS Algorithms like DARTs, ProxylessNAS #461
Other Features
Enhancements
Common
- Delete Suggestion deployment after Experiment is finished #1061
- Save Suggestion state after deployment is deleted #1062
- Reconsider the design of Trial Template #906
- Design an extensible model for integrating with custom resources.
- Add validation for algorithms (a.k.a suggestions) #1126
- Katib UI fixes and enhancements
- Investigate Kubeflow Metadata integration
- Investigate the alignment with concept and implementation of "experiments" and "jobs/runs" in KFP #4955