Support for RNN based decoder units
Open
Nobody has claimed this yet.
enhancement
- Dominant language
- C++
- Stars
- 4.7k
- Forks
- 536
- Avg merge
- 12h 12m
- Merged PRs (30d)
- 4
Description
Are there any plans to support inference of heterogeneous encoder-decoder architectures where in we use transformer based encoder and RNN/LSTM based decoders ?
Would like to submit this as a new feature request.
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
The issue mentions no files, tests, or entry points. Start by locating the existing inference support for transformer encoder-decoder models and reviewing how decoder architectures are represented. Done means demonstrating inference for a transformer-based encoder paired with an RNN or LSTM decoder, with appropriate coverage for the supported heterogeneous architecture.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100