Reduce vector memory usage #340
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Drone builds are failing and BCH is complaining about an extra line in a method, but I'm ignoring those as the important tests are all clear. |
Drone builds fixed by #341. |
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This PR changes the data type of many NumPy arrays used to encode subject and suggestion vectors. Suggestions are now encoded using float32 (instead of float64) and known subjects are encoded using boolean arrays (instead of int8).
The end result is reduced memory usage and in some cases also faster execution. For example the
evalcommand on atfidfbackend is now noticeably faster (around a third in one test).Among other improvements this should reduce the memory consumption of the PAV backend during training (#339)