tensorflow / tensorflow/tensorboard
Mechanism for persistent user settings
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- Dominant language
- TypeScript
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Description
As mentioned in #893 (e.g., in this comment, https://github.com/tensorflow/tensorboard/issues/893#issuecomment-668712228), we need a mechanism for persisting user settings / preferences.
I'm capturing some items / ideas here that should be put into a RFC / requirements doc.
- This needs to work both in regular TensorBoard and in TensorBoard.dev, etc.
- Tiered preference system:
- Global preferences (per user): example: smoothing
- Experiment specific preference (when viewing this experiment, change the run color to #aaa)
- We may want to make smoothing weight, ignore outlier experiment specific OR global (i.e., it is unclear what is more correct)
- Shareable UI configuration (so your colleague sees exactly the same UI when you share a URL)
Based on above considerations, schema/mechanism of the backend will change (simple KV pair or relational structure)
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 with issue #893 and its linked comment, then turn the listed preference scopes and deployment targets into an RFC or requirements document. A completed proposal should cover persistence scope, shareable UI configuration, and the backend schema or mechanism; no implementation files or tests are named in this issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- typescript
- Domain
- backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100