tensorflow / tensorflow/tensorboard
Projector: default compute PCA issue
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- Dominant language
- TypeScript
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Description
When clicking on the projector tab, tensorboard starts loading tensor values and computes the PCA.
The problem is that if the tensor is very large (e.g. large embeddings), default computing the PCA will take super long time, and you can do nothing but wait a few minutes at least.
I believe this is flaw for the default logic, a better option would be to let the user decide whether to compute the PCA(T-SNE, etc), for example, a button saying visualize.
- TensorBoard version: 1.8.0
- OS Platform and version: Ubuntu 16.04
- Python version: 3.5
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 at the Projector tab's loading path and reproduce the delay with a large embedding, then trace where PCA computation begins. Review the existing Projector UI and related tests, if present, to determine how computation is triggered. Done means opening the tab no longer automatically blocks on PCA and the user can explicitly start visualization.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- typescript
- Domain
- data-visualization, frontend
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100