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[CI] Fix Docker build for CUDA 11 (#6202)

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Philip Hyunsu Cho 2020-10-05 17:54:14 -07:00 committed by GitHub
parent fd58005edf
commit f121f2738f
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GPG Key ID: 4AEE18F83AFDEB23
8 changed files with 36 additions and 33 deletions
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18
Jenkinsfile vendored
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@ -132,7 +132,7 @@ def ClangTidy() {
echo "Running clang-tidy job..."
def container_type = "clang_tidy"
def docker_binary = "docker"
def dockerArgs = "--build-arg CUDA_VERSION=10.1"
def dockerArgs = "--build-arg CUDA_VERSION_ARG=10.1"
sh """
${dockerRun} ${container_type} ${docker_binary} ${dockerArgs} python3 tests/ci_build/tidy.py
"""
@ -205,7 +205,7 @@ def BuildCUDA(args) {
echo "Build with CUDA ${args.cuda_version}"
def container_type = GetCUDABuildContainerType(args.cuda_version)
def docker_binary = "docker"
def docker_args = "--build-arg CUDA_VERSION=${args.cuda_version}"
def docker_args = "--build-arg CUDA_VERSION_ARG=${args.cuda_version}"
def arch_flag = ""
if (env.BRANCH_NAME != 'master' && !(env.BRANCH_NAME.startsWith('release'))) {
arch_flag = "-DGPU_COMPUTE_VER=75"
@ -228,7 +228,7 @@ def BuildCUDA(args) {
echo "Build with CUDA ${args.cuda_version} and RMM"
container_type = "rmm"
docker_binary = "docker"
docker_args = "--build-arg CUDA_VERSION=${args.cuda_version}"
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}
@ -250,7 +250,7 @@ def BuildJVMPackagesWithCUDA(args) {
echo "Build XGBoost4J-Spark with Spark ${args.spark_version}, CUDA ${args.cuda_version}"
def container_type = "jvm_gpu_build"
def docker_binary = "nvidia-docker"
def docker_args = "--build-arg CUDA_VERSION=${args.cuda_version}"
def docker_args = "--build-arg CUDA_VERSION_ARG=${args.cuda_version}"
def arch_flag = ""
if (env.BRANCH_NAME != 'master' && !(env.BRANCH_NAME.startsWith('release'))) {
arch_flag = "-DGPU_COMPUTE_VER=75"
@ -325,7 +325,7 @@ def TestPythonGPU(args) {
echo "Test Python GPU: CUDA ${args.host_cuda_version}"
def container_type = "gpu"
def docker_binary = "nvidia-docker"
def docker_args = "--build-arg CUDA_VERSION=${args.host_cuda_version}"
def docker_args = "--build-arg CUDA_VERSION_ARG=${args.host_cuda_version}"
def mgpu_indicator = (args.multi_gpu) ? 'mgpu' : 'gpu'
// Allocate extra space in /dev/shm to enable NCCL
def docker_extra_params = (args.multi_gpu) ? "CI_DOCKER_EXTRA_PARAMS_INIT='--shm-size=4g'" : ''
@ -363,7 +363,7 @@ def TestCppGPU(args) {
echo "Test C++, CUDA ${args.host_cuda_version}"
def container_type = "gpu"
def docker_binary = "nvidia-docker"
def docker_args = "--build-arg CUDA_VERSION=${args.host_cuda_version}"
def docker_args = "--build-arg CUDA_VERSION_ARG=${args.host_cuda_version}"
sh "${dockerRun} ${container_type} ${docker_binary} ${docker_args} build/testxgboost"
if (args.test_rmm) {
sh "rm -rfv build/"
@ -371,7 +371,7 @@ def TestCppGPU(args) {
echo "Test C++, CUDA ${args.host_cuda_version} with RMM"
container_type = "rmm"
docker_binary = "nvidia-docker"
docker_args = "--build-arg CUDA_VERSION=${args.host_cuda_version}"
docker_args = "--build-arg CUDA_VERSION_ARG=${args.host_cuda_version}"
sh """
${dockerRun} ${container_type} ${docker_binary} ${docker_args} bash -c "source activate gpu_test && build/testxgboost --use-rmm-pool --gtest_filter=-*DeathTest.*"
"""
@ -392,7 +392,7 @@ def CrossTestJVMwithJDKGPU(args) {
}
def container_type = "gpu_jvm"
def docker_binary = "nvidia-docker"
def docker_args = "--build-arg CUDA_VERSION=${args.host_cuda_version}"
def docker_args = "--build-arg CUDA_VERSION_ARG=${args.host_cuda_version}"
sh "${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/test_jvm_gpu_cross.sh"
deleteDir()
}
@ -444,7 +444,7 @@ def DeployJVMPackages(args) {
${dockerRun} jvm docker tests/ci_build/deploy_jvm_packages.sh ${args.spark_version} 0
"""
sh """
${dockerRun} jvm_gpu_build docker --build-arg CUDA_VERSION=10.0 tests/ci_build/deploy_jvm_packages.sh ${args.spark_version} 1
${dockerRun} jvm_gpu_build docker --build-arg CUDA_VERSION_ARG=10.0 tests/ci_build/deploy_jvm_packages.sh ${args.spark_version} 1
"""
}
deleteDir()

5
tests/ci_build/Dockerfile.clang_tidy
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@ -1,5 +1,6 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-ubuntu18.04
ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-ubuntu18.04
ARG CUDA_VERSION_ARG
# Environment
ENV DEBIAN_FRONTEND noninteractive

7
tests/ci_build/Dockerfile.gpu
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@ -1,5 +1,6 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-runtime-ubuntu18.04
ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-runtime-ubuntu18.04
ARG CUDA_VERSION_ARG
# Environment
ENV DEBIAN_FRONTEND noninteractive
@ -18,7 +19,7 @@ ENV PATH=/opt/python/bin:$PATH
# Create new Conda environment with cuDF, Dask, and cuPy
RUN \
conda create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
python=3.7 cudf=0.16* rmm=0.16* cudatoolkit=$CUDA_VERSION dask dask-cuda dask-cudf cupy \
python=3.7 cudf=0.16* rmm=0.16* cudatoolkit=$CUDA_VERSION_ARG dask dask-cuda dask-cudf cupy \
numpy pytest scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz hypothesis
ENV GOSU_VERSION 1.10

8
tests/ci_build/Dockerfile.gpu_build
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@ -1,6 +1,6 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-ubuntu16.04
ARG CUDA_VERSION
ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-ubuntu16.04
ARG CUDA_VERSION_ARG
# Environment
ENV DEBIAN_FRONTEND noninteractive
@ -19,7 +19,7 @@ RUN \
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \
export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
export CUDA_SHORT=`echo $CUDA_VERSION_ARG | egrep -o '[0-9]+\.[0-9]'` && \
export NCCL_VERSION=2.7.5-1 && \
apt-get update && \
apt-get install -y --allow-downgrades --allow-change-held-packages libnccl2=${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-dev=${NCCL_VERSION}+cuda${CUDA_SHORT}

8
tests/ci_build/Dockerfile.gpu_build_centos6
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@ -1,6 +1,6 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-centos6
ARG CUDA_VERSION
ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-centos6
ARG CUDA_VERSION_ARG
# Environment
ENV DEBIAN_FRONTEND noninteractive
@ -33,7 +33,7 @@ RUN \
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \
export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
export CUDA_SHORT=`echo $CUDA_VERSION_ARG | egrep -o '[0-9]+\.[0-9]'` && \
export NCCL_VERSION=2.4.8-1 && \
wget https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \

5
tests/ci_build/Dockerfile.gpu_jvm
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@ -1,5 +1,6 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-runtime-ubuntu16.04
ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-runtime-ubuntu16.04
ARG CUDA_VERSION_ARG
ARG JDK_VERSION=8
ARG SPARK_VERSION=3.0.0

8
tests/ci_build/Dockerfile.jvm_gpu_build
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@ -1,6 +1,6 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-centos6
ARG CUDA_VERSION
ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-centos6
ARG CUDA_VERSION_ARG
# Environment
ENV DEBIAN_FRONTEND noninteractive
@ -30,7 +30,7 @@ RUN \
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \
export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
export CUDA_SHORT=`echo $CUDA_VERSION_ARG | egrep -o '[0-9]+\.[0-9]'` && \
export NCCL_VERSION=2.4.8-1 && \
wget https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \

10
tests/ci_build/Dockerfile.rmm
View File

@ -1,6 +1,6 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-ubuntu18.04
ARG CUDA_VERSION
ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-ubuntu18.04
ARG CUDA_VERSION_ARG
# Environment
ENV DEBIAN_FRONTEND noninteractive
@ -19,7 +19,7 @@ RUN \
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \
export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
export CUDA_SHORT=`echo $CUDA_VERSION_ARG | egrep -o '[0-9]+\.[0-9]'` && \
export NCCL_VERSION=2.7.5-1 && \
apt-get update && \
apt-get install -y --allow-downgrades --allow-change-held-packages libnccl2=${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-dev=${NCCL_VERSION}+cuda${CUDA_SHORT}
@ -29,7 +29,7 @@ ENV PATH=/opt/python/bin:$PATH
# Create new Conda environment with RMM
RUN \
conda create -n gpu_test -c nvidia -c rapidsai-nightly -c rapidsai -c conda-forge -c defaults \
python=3.7 rmm=0.16* cudatoolkit=$CUDA_VERSION
python=3.7 rmm=0.16* cudatoolkit=$CUDA_VERSION_ARG
ENV GOSU_VERSION 1.10