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## Motivation for features / changes
Fix a bug with knn computation in projector
## Technical description of changes
If we have 1000 points, and we sample 100 points, we cannot reuse the
old knn computation because it could contain points that are not part of
the sample.
## Screenshots of UI changes
N/A
## Detailed steps to verify changes work correctly (as executed by you)
1. Build and launch
[projector](https://github.com/tensorflow/tensorboard/blob/bbc9e4f29a55d48478c3f23a7d80221b5b1b1e3c/tensorboard/plugins/projector/README.md)
2. Use default demo tensor (Word2Vec 10K)
3. Change projection type from PCA to T-SNE. This should compute 10k
sample points with 90 neighbors for knn.
4. Change projection type from T-SNE to UMAP. You'll see a "Initializing
UMAP..." screen loading indefinitely. UMAP uses 5k sample points and 15
neighbors for knn by default
Verify the above step results in successful UMAP rendering after the
changes are applied
## Alternate designs / implementations considered
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