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Add use_rmm flag to global configuration #6656

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merged 12 commits into from Mar 9, 2021
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@hcho3 hcho3 commented Jan 28, 2021

Closes #6297. The user should explicitly inform XGBoost if RMM is used. If RMM is used, XGBoost should not allocate from the CUB allocator.

@hcho3 hcho3 mentioned this pull request Jan 28, 2021
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@@ -8,7 +8,7 @@ dependencies:
- pyyaml
- cpplint
- pylint
- numpy
- numpy=1.19.4
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This is a workaround, as the latest shap package appears to break with NumPy 1.19.5:
https://xgboost-ci.net/blue/organizations/jenkins/xgboost/detail/PR-6656/4/pipeline/221

     try:
>       from .. import _cext
E    ImportError: numpy.core.multiarray failed to import

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@trivialfis Have you run into this issue? What's your take on it?

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never seen it before.

What's your take on it?

@RAMitchell worked on the c extension before so maybe have better insight.

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Using shap from conda-forge also fixes the issue, but unfortunately conda-forge has an outdated version of shap.

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codecov-io commented Mar 5, 2021

Codecov Report

Merging #6656 (f850b12) into master (5ae7f99) will not change coverage.
The diff coverage is n/a.

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@@           Coverage Diff           @@
##           master    #6656   +/-   ##
=======================================
  Coverage   81.83%   81.83%           
=======================================
  Files          13       13           
  Lines        3809     3809           
=======================================
  Hits         3117     3117           
  Misses        692      692           

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demo/rmm_plugin/rmm_mgpu_with_dask.py Show resolved Hide resolved
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@hcho3 hcho3 merged commit 366f3cb into dmlc:master Mar 9, 2021
@hcho3 hcho3 deleted the rmm_global_config branch March 9, 2021 22:53
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Add an explicit option to use RMM
3 participants