def squash_embeddings(embeddings):
spinner = Halo('squashing embeddings down to 2d and normalising').start()
embeddings = UMAP(n_components=2).fit_transform(embeddings)
normalised_embeddings = ((embeddings - embeddings.min(axis=0)) /
(embeddings.max(axis=0) - embeddings.min(axis=0)))
spinner.succeed()
return normalised_embeddings
