Exposed KMeans' n_jobs param to LOPQModel for parallelized Cluster Computation

yahoo / lopq

Training of Locally Optimized Product Quantization (LOPQ) models for approximate nearest neighbor search of high dimensional data in Python and Spark.

Apache License 2.0

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Exposed KMeans' n_jobs param to LOPQModel for parallelized Cluster Computation #15

Closed mkurovski closed 6 years ago

coveralls commented 6 years ago

Coverage increased (+0.02%) to 88.462% when pulling 7b3be79fe4ae5f38a62a99c5ab17e8b5aa49e0be on squall-1002:python2_parallel into 5be92898ae856b8c75fb5ec577f8cd0c95754488 on yahoo:master.

coveralls commented 6 years ago

Coverage remained the same at 88.443% when pulling 46b43827986611ab32f52349cd454ba2539c2160 on squall-1002:python2_parallel into 5be92898ae856b8c75fb5ec577f8cd0c95754488 on yahoo:master.

mkurovski commented 6 years ago

So, I think it should be fine now ;)

pumpikano commented 6 years ago

Yup, looks great. @huyng, can you PTAL?

coveralls commented 6 years ago

Coverage remained the same at 88.443% when pulling 45f09035052c775aae66b2025f380b8d181a1750 on squall-1002:python2_parallel into 5be92898ae856b8c75fb5ec577f8cd0c95754488 on yahoo:master.

coveralls commented 6 years ago

Coverage remained the same at 88.443% when pulling c3dbd5eb91e448596c1d0181b214d4f012d3c1db on squall-1002:python2_parallel into 5be92898ae856b8c75fb5ec577f8cd0c95754488 on yahoo:master.

pumpikano commented 6 years ago

Awesome, LGTM. @huyng please merge when you get a chance.

huyng commented 6 years ago

Thanks for the contributions. 👍