[Breaking] Upgrade cuDF and RMM to 0.18 nightlies; require RMM 0.18+ for RMM plugin (#6510)
* [CI] Upgrade cuDF and RMM to 0.18 nightlies * Modify RMM plugin to be compatible with RMM 0.18 * Update src/common/device_helpers.cuh Co-authored-by: Mark Harris <mharris@nvidia.com> Co-authored-by: Mark Harris <mharris@nvidia.com>
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@ -429,7 +429,7 @@ struct XGBDefaultDeviceAllocatorImpl : XGBBaseDeviceAllocator<T> {
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}
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#if defined(XGBOOST_USE_RMM) && XGBOOST_USE_RMM == 1
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XGBDefaultDeviceAllocatorImpl()
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: SuperT(rmm::mr::get_current_device_resource(), cudaStream_t{nullptr}) {}
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: SuperT(rmm::cuda_stream_default, rmm::mr::get_current_device_resource()) {}
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#endif // defined(XGBOOST_USE_RMM) && XGBOOST_USE_RMM == 1
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};
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@ -19,7 +19,7 @@ ENV PATH=/opt/python/bin:$PATH
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# Create new Conda environment with cuDF, Dask, and cuPy
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RUN \
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conda create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
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python=3.7 cudf=0.17* rmm=0.17* cudatoolkit=$CUDA_VERSION_ARG dask dask-cuda dask-cudf cupy \
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python=3.7 cudf=0.18* rmm=0.18* cudatoolkit=$CUDA_VERSION_ARG dask dask-cuda dask-cudf cupy \
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numpy pytest scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz hypothesis
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ENV GOSU_VERSION 1.10
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@ -29,7 +29,7 @@ ENV PATH=/opt/python/bin:$PATH
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# Create new Conda environment with RMM
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RUN \
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conda create -n gpu_test -c nvidia -c rapidsai-nightly -c rapidsai -c conda-forge -c defaults \
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python=3.7 rmm=0.17* cudatoolkit=$CUDA_VERSION_ARG
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python=3.7 rmm=0.18* cudatoolkit=$CUDA_VERSION_ARG
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ENV GOSU_VERSION 1.10
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