add Sparsemax activation
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enhancement
- Dominant language
- Julia
- Stars
- 258
- Forks
- 138
- Avg merge
- 2d 1h
- Merged PRs (30d)
- 3
Description
Source paper: http://arxiv.org/abs/1602.02068
PyTorch implementation: https://github.com/Qwicen/node/blob/master/lib/nn_utils.py
I started working on implementing sparsemax in Julia for TabNet. I thought that it would best fit in NNlib.jl. It should have the exact same functionality as softmax.
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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
Read the sparsemax paper and the referenced PyTorch implementation in lib/nn_utils.py, then inspect NNlib.jl's existing softmax functionality. Implement sparsemax with the same functionality as softmax, and verify that its behavior matches the stated algorithm and API.
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Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100