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Protect balanced k-means out-of-memory in some cases (rapidsai#1161)
There's no guarantee that our balanced k-means implementation always produces balanced clusters. In the first stage, when mesoclusters are trained, the biggest cluster can grow larger than half of all input data. This becomes a problem at the second stage, when in `build_fine_clusters`, the mesocluster data is copied in a temporary buffer. If size is too big, there may be not enough memory on the device. A quick workaround: 1. Expand the error reporting (RAFT_LOG_WARN) 2. Artificially limit the mesocluster size in the event of highly unbalanced clustering Authors: - Artem M. Chirkin (https://github.com/achirkin) Approvers: - Tamas Bela Feher (https://github.com/tfeher) URL: rapidsai#1161
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