sktime / sktime/pytorch-forecasting
[ENH] Add v2 interface support for DeepAR
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Description
Referencing #1992
The DeepAR model currently does not have a v2-compliant estimator/package. Unlike DLinear, SAMformer, and TFT, it does not provide a *_pkg_v2 wrapper inheriting from _BasePtForecasterV2, so it cannot be used through the v2 interface.
Should we add a v2 package for DeepAR? If so, would interfacing with the existing implementation or forking and adapting it be preferred?
CC: @fkiraly
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Compare the v2 wrappers for DLinear, SAMformer, and TFT with the existing DeepAR implementation. First determine whether DeepAR should be interfaced directly or forked and adapted; done means it has a v2-compliant package usable through the v2 interface.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- api, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 42/100