patrick-kidger / patrick-kidger/optimistix
Support complex-to-real optimization
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Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 623
- Forks
- 54
- PR merge metrics
- No merged PRs in 30d
Description
- We chose first-argument conjugation, but our tree_dot does second-argument conjugation (https://github.com/patrick-kidger/lineax/pull/105)
- Complex functions require taking conjugates and/or real in various places (partially fixed in https://github.com/patrick-kidger/optimistix/pull/71)
- Lineax represents jvp as linear operator, but jvp of C->R function is not complex linear
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
No files, tests, or entry points are named. Start by reading the linked Lineax pull request, the Optimistix pull request, and JAX's complex-number differentiation cookbook section; define the required conjugation and real-value behavior before assessing how complex-to-real optimization and non-complex-linear JVPs should be supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100