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Dispatch thrust versions and upgrade rmm. #7254

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merged 3 commits into from Sep 24, 2021
Merged

Dispatch thrust versions and upgrade rmm. #7254

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9dd9e00
Dispatch thrust versions and upgrade rmm.
trivialfis Sep 24, 2021
44f9710
Newer cuDF.
trivialfis Sep 24, 2021
8449425
Update CMakeLists.txt
trivialfis Sep 24, 2021
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3 changes: 3 additions & 0 deletions CMakeLists.txt
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Expand Up @@ -112,6 +112,9 @@ endif (ENABLE_ALL_WARNINGS)
if (BUILD_STATIC_LIB AND (R_LIB OR JVM_BINDINGS))
message(SEND_ERROR "Cannot build a static library libxgboost.a when R or JVM packages are enabled.")
endif (BUILD_STATIC_LIB AND (R_LIB OR JVM_BINDINGS))
if (PLUGIN_RMM AND (NOT BUILD_WITH_CUDA_CUB))
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Disabled the cub submodule to simplify things.

message(SEND_ERROR "Cannot build with RMM using cub cubmodule.")
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endif (PLUGIN_RMM AND (NOT BUILD_WITH_CUDA_CUB))

#-- Sanitizer
if (USE_SANITIZER)
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2 changes: 1 addition & 1 deletion Jenkinsfile
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Expand Up @@ -249,7 +249,7 @@ def BuildCUDA(args) {
docker_args = "--build-arg CUDA_VERSION_ARG=${args.cuda_version}"
sh """
rm -rf build/
${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/build_via_cmake.sh --conda-env=gpu_test -DUSE_CUDA=ON -DUSE_NCCL=ON -DPLUGIN_RMM=ON ${arch_flag}
${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/build_via_cmake.sh --conda-env=gpu_test -DUSE_CUDA=ON -DUSE_NCCL=ON -DPLUGIN_RMM=ON -DBUILD_WITH_CUDA_CUB=ON ${arch_flag}
${dockerRun} ${container_type} ${docker_binary} ${docker_args} bash -c "cd python-package && rm -rf dist/* && python setup.py bdist_wheel --universal"
${dockerRun} ${container_type} ${docker_binary} ${docker_args} python tests/ci_build/rename_whl.py python-package/dist/*.whl ${commit_id} manylinux2014_x86_64
"""
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11 changes: 9 additions & 2 deletions python-package/xgboost/data.py
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Expand Up @@ -435,7 +435,11 @@ def _cudf_array_interfaces(data) -> Tuple[list, bytes]:
interface is finished.

"""
from cudf.utils.dtypes import is_categorical_dtype
try:
from cudf.api.types import is_categorical_dtype
except ImportError:
from cudf.utils.dtypes import is_categorical_dtype

cat_codes = []
interfaces = []
if _is_cudf_ser(data):
Expand All @@ -461,7 +465,10 @@ def _transform_cudf_df(
feature_types: Optional[List[str]],
enable_categorical: bool,
):
from cudf.utils.dtypes import is_categorical_dtype
try:
from cudf.api.types import is_categorical_dtype
except ImportError:
from cudf.utils.dtypes import is_categorical_dtype

if feature_names is None:
if _is_cudf_ser(data):
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10 changes: 7 additions & 3 deletions src/common/device_helpers.cuh
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Expand Up @@ -708,6 +708,10 @@ constexpr std::pair<int, int> CUDAVersion() {
#endif // defined(__CUDACC_VER_MAJOR__)
}

constexpr std::pair<int32_t, int32_t> ThrustVersion() {
return std::make_pair(THRUST_MAJOR_VERSION, THRUST_MINOR_VERSION);
}

namespace detail {
template <typename T>
using TypedDiscardCTK114 = thrust::discard_iterator<T>;
Expand All @@ -721,9 +725,9 @@ class TypedDiscard : public thrust::discard_iterator<T> {

template <typename T>
using TypedDiscard =
std::conditional_t<((CUDAVersion().first == 11 &&
CUDAVersion().second >= 4) ||
CUDAVersion().first > 11),
std::conditional_t<((ThrustVersion().first == 1 &&
ThrustVersion().second >= 12) ||
ThrustVersion().first > 1),
detail::TypedDiscardCTK114<T>, detail::TypedDiscard<T>>;

/**
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2 changes: 1 addition & 1 deletion tests/ci_build/Dockerfile.gpu
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Expand Up @@ -19,7 +19,7 @@ ENV PATH=/opt/python/bin:$PATH
# Create new Conda environment with cuDF, Dask, and cuPy
RUN \
conda create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
python=3.7 cudf=21.08* rmm=21.08* cudatoolkit=$CUDA_VERSION_ARG dask dask-cuda dask-cudf cupy=9.1* \
python=3.8 cudf=21.10* rmm=21.10* cudatoolkit=$CUDA_VERSION_ARG dask dask-cuda=21.10* dask-cudf=21.10* cupy=9.1* \
numpy pytest scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz hypothesis

ENV GOSU_VERSION 1.10
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2 changes: 1 addition & 1 deletion tests/ci_build/Dockerfile.rmm
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Expand Up @@ -29,7 +29,7 @@ ENV PATH=/opt/python/bin:$PATH
# Create new Conda environment with RMM
RUN \
conda create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
python=3.7 rmm=21.08* cudatoolkit=$CUDA_VERSION_ARG
python=3.8 rmm=21.10* cudatoolkit=$CUDA_VERSION_ARG

ENV GOSU_VERSION 1.10

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