Gracefully accept 'n_jobs', a common sklearn parameter, in NearestNeighbors Estimator #4178
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…meters; thank you, Dante!
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@NV-jpt there seems to be just some super minor pep8 issues that the style checker is complaining about: ./python/cuml/neighbors/nearest_neighbors.pyx:284:73: W291 trailing whitespace
./python/cuml/neighbors/nearest_neighbors.pyx:285:72: W291 trailing whitespace
./python/cuml/neighbors/nearest_neighbors.pyx:286:78: W291 trailing whitespace |
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… NearestNeighbors Estimator" (#4267) This pull request partially solves [[FEA] #3461](#3461) This quick-fix has been created to enable cuML's NearestNeighbor estimator to gracefully accept sklearns 'n_jobs' parameter as a pass-through. The purpose of making this quick fix is to allow Imbalanced-Learn samplers to rely on cuML's NearestNeighbor estimator, without producing an error when setting the estimators n_jobs parameter .set_params(**{"n_jobs": self.n_jobs}) The[ original PR ](#4178 address this issue was not sufficient, as [`set_params()`](https://github.com/rapidsai/cuml/blob/067344041b1563b19301e2e69240a56605a67997/python/cuml/common/base.pyx#L248) will still raise a ValueError if "n_jobs" is not returned by [`get_param_names()`](https://github.com/rapidsai/cuml/blob/067344041b1563b19301e2e69240a56605a67997/python/cuml/neighbors/nearest_neighbors.pyx#L453) Authors: - https://github.com/NV-jpt - Dante Gama Dessavre (https://github.com/dantegd) Approvers: - William Hicks (https://github.com/wphicks) URL: #4267
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…ghbors Estimator (rapidsai#4178) This pull request partially solves [[FEA] rapidsai#3461](rapidsai#3461). This quick-fix has been created to enable cuML's NearestNeighbor estimator to gracefully accept sklearns 'n_jobs' parameter as a pass-through. The purpose of making this quick fix is to allow Imbalanced-Learn samplers to rely on cuML's NearestNeighbor estimator, without producing an error when setting the estimators n_jobs parameter `.set_params(**{"n_jobs": self.n_jobs})` [1](https://github.com/scikit-learn-contrib/imbalanced-learn/blob/edf6eae2c00f7fa6d76ee381f5b625155061a725/imblearn/over_sampling/_adasyn.py#L112) Authors: - https://github.com/NV-jpt Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4178
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… NearestNeighbors Estimator" (rapidsai#4267) This pull request partially solves [[FEA] rapidsai#3461](rapidsai#3461) This quick-fix has been created to enable cuML's NearestNeighbor estimator to gracefully accept sklearns 'n_jobs' parameter as a pass-through. The purpose of making this quick fix is to allow Imbalanced-Learn samplers to rely on cuML's NearestNeighbor estimator, without producing an error when setting the estimators n_jobs parameter .set_params(**{"n_jobs": self.n_jobs}) The[ original PR ](rapidsai#4178 address this issue was not sufficient, as [`set_params()`](https://github.com/rapidsai/cuml/blob/2fee231ac28d982f64c4a746c25be19750812e81/python/cuml/common/base.pyx#L248) will still raise a ValueError if "n_jobs" is not returned by [`get_param_names()`](https://github.com/rapidsai/cuml/blob/2fee231ac28d982f64c4a746c25be19750812e81/python/cuml/neighbors/nearest_neighbors.pyx#L453) Authors: - https://github.com/NV-jpt - Dante Gama Dessavre (https://github.com/dantegd) Approvers: - William Hicks (https://github.com/wphicks) URL: rapidsai#4267
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This pull request partially solves [FEA] #3461.
This quick-fix has been created to enable cuML's NearestNeighbor estimator to gracefully accept sklearns 'n_jobs' parameter as a pass-through.
The purpose of making this quick fix is to allow Imbalanced-Learn samplers to rely on cuML's NearestNeighbor estimator, without producing an error when setting the estimators n_jobs parameter
.set_params(**{"n_jobs": self.n_jobs})1