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# Katib 2020 Roadmap | ||
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This document provides a high level view of where Katib will grow in 2020. | ||
## New Features | ||
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The original Katib design document can be found [here](https://docs.google.com/document/d/1ZEKhou4z1utFTOgjzhSsnvysJFNEJmygllgDCBnYvm8/edit#heading=h.7fzqir88ovr). | ||
- Support Early Stopping [#692](https://github.com/kubeflow/katib/issues/692) | ||
- Support Advanced NAS Algorithms like DARTs, ProxylessNAS [#461](https://github.com/kubeflow/katib/issues/461) | ||
- Support Auto Model Compression [#460](https://github.com/kubeflow/katib/issues/460) | ||
- Support Auto Feature Engineering [#475](https://github.com/kubeflow/katib/issues/475) | ||
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# Katib 1.0 Readiness | ||
## Enhancements | ||
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* Stabilize APIs for Experiments | ||
* Reconsider the design of Trial Template [#906](https://github.com/kubeflow/katib/issues/906) | ||
* Early Stopping [#692](https://github.com/kubeflow/katib/issues/692) | ||
* Resuming Experiment [#1061](https://github.com/kubeflow/katib/issues/1061), [#1062](https://github.com/kubeflow/katib/issues/1062) | ||
* Fully integrate Katib with existing E2E examples: | ||
* Xgboost | ||
* Mnist | ||
* GitHub issue summarization | ||
* Publish API documentation, best practices, tutorials | ||
* [Issues list](https://github.com/kubeflow/katib/issues) | ||
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# Enhance HP Tuning Experience | ||
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The objectives here are organized around the three stages defined in the CUJ: | ||
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## 1. Defining Model and Parameters | ||
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Integration with KF distributed training components | ||
* TFJob | ||
* PyTorch | ||
* Allow Katib to support other operator types generically [#341](https://github.com/kubeflow/katib/issues/341) | ||
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## 2. Configuring a Experiment | ||
* Supporting additional suggestion algorithms [#15](https://github.com/kubeflow/katib/issues/15) | ||
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## 3. Tracking Model Performance | ||
* UI enhancements: allowing data scientists to visualize results easier | ||
* Support for persistent model and metadata storage | ||
* Ideally users should be able to export and reuse trained models from a common storage | ||
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# Test and Release Infrastructure | ||
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* Improve e2e test coverage | ||
* Improve test harness | ||
* Enhance release process; adding automation (see https://bit.ly/2F7o4gM) | ||
- Delete Suggestion deployment after Experiment is finished [#1061](https://github.com/kubeflow/katib/issues/1061) | ||
- Save Suggestion state after deployment is deleted [#1062](https://github.com/kubeflow/katib/issues/1062) | ||
- Reconsider the design of Trial Template [#906](https://github.com/kubeflow/katib/issues/906) |