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Upgrade to Treelite 1.2.0 #3829

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@hcho3 hcho3 commented May 5, 2021

This version incorporates two major new features:

Depends on rapidsai/integration#265

@hcho3 hcho3 requested a review from a team as a code owner May 5, 2021 18:10
@github-actions github-actions bot added conda conda issue gpuCI gpuCI issue labels May 5, 2021
Comment on lines +64 to +66
gpuci_conda_retry remove -c conda-forge -c rapidsai -c rapidsai-nightly -c nvidia \
--force rapids-build-env rapids-notebook-env
gpuci_conda_retry install -c conda-forge -c rapidsai -c rapidsai-nightly -c nvidia treelite=1.2.0
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I will remove these lines once Treelite is upgraded in integration.

@hcho3 hcho3 added Build or Dep Issues related to building the code or dependencies non-breaking Non-breaking change 3 - Ready for Review Ready for review by team feature request New feature or request labels May 5, 2021
@hcho3 hcho3 requested a review from a team as a code owner May 5, 2021 20:04
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hcho3 commented May 6, 2021

When I re-built cuML with dmlc/treelite#270 temporarily reverted, the Dask tests start passing again. It appears that dmlc/treelite#270 broke the in-memory serializer. I will investigate.

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hcho3 commented May 6, 2021

Here is a hotfix to fix the bug in the binary serializer: dmlc/treelite#273. I will publish a new patch version 1.2.1 and submit a new PR to use that version in cuML.

@hcho3 hcho3 closed this May 6, 2021
@hcho3 hcho3 deleted the upgrade_treelite branch May 6, 2021 22:17
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[FEA] Speed up sklearn imports to FIL / treelite
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