Embedding Projector: fix knn for non-normalized vectors

[alicialics]

Motivation for features / changes

Fixes #6271 Fixes #5547

Technical description of changes

the reason is that knn expects normalized vectors for cosine distance (cosDistNorm) rather than arbitrary vectors.

Screenshots of UI changes

N/A

Detailed steps to verify changes work correctly (as executed by you)

• Build and launch projector (must be from master, not https://projector.tensorflow.org)
• Select Iris demo tensor dataset
• Keep "Sphereize data" unchecked
• change projection type to T-SNE
• The end result is different from what happens when using https://projector.tensorflow.org/
• change projection tyoe to UMAP
• See "Initialize UMAP..." modal loading forever

Alternative repo:

• Build and launch projector (must be from master, not https://projector.tensorflow.org)
• Uncheck "Sphereize data" on the default Word2Vec 10k dataset
• Switch projection from "PCA" to either t-SNE or UMAP
• See the UI breaks with "Initializing t-SNE..."/"Initialize UMAP..." modal loading forever

Alternate designs / implementations considered