spectral_layout gets stuck on eigsh

Nobody has claimed this yet.

On some datasets (in this case sentence embeddings, 25d vectors) spectral_layout gets stuck on eigsh.
Dataset size shape in my case: (50000, 25)
metric: cosine
I have been hunting this for a while now and if you do not mind i will try to implement this differently using truncated svd instead of eigsh and make a pull request. In any case eigsh does not seem to raise "ArpackNoConvergence" which it should if optimization gets stuck (i will raise this with scipy community).
As a sidenote: this is not really reproducable for all datasets - some datasets work, some don't. Changing n_neighbors (i.e. altering the graph) solves the issue for some datasets - not for others. Random init works just fine on all datasets i have tried.

In any event i really love UMAP and use it as drop in replacement for t-SNE and as dimensionality reduction kit of clustering, anomaly detection and topological data analysis (i.e. as a lens for the MAPPER algorithm)

Start at the spectral_layout entry point and reproduce the hang with a (50000, 25) sentence-embedding dataset using cosine distance. Trace the eigsh path and compare it with the proposed truncated-SVD approach; done means the affected datasets complete instead of remaining stuck, while preserving the existing random-init behavior.

Written by the indexing model from the issue text.