Feature-Request: Matrix Exponentiation
Open
Nobody has claimed this yet.
enhancement
low priority
- Dominant language
- C++
- Stars
- 28.5k
- Forks
- 2.3k
- Avg merge
- 3d 8h
- Merged PRs (30d)
- 62
Description
Useful for orthogonal optimization and other algorithms where calculating unitary matrices or dealing with complex numbers is necessary.
Pytorch impl:
https://discuss.pytorch.org/t/what-implementation-is-used-for-matrix-exp/159608/5
https://pytorch.org/docs/stable/generated/torch.linalg.matrix_exp.html
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
Start by reviewing the linked PyTorch matrix_exp implementation and documentation to understand the expected operation and supported inputs. Then locate MLX's corresponding array-operation entry points; done should include a documented matrix exponentiation feature with coverage for the intended real and complex matrix cases.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100