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##############################################
# Dask GPU build and test script for CI #
##############################################
set -e
NUMARGS=$#
ARGS=$*
# Arg parsing function
function hasArg {
(( ${NUMARGS} != 0 )) && (echo " ${ARGS} " | grep -q " $1 ")
}
# Set path and build parallel level
export PATH=/opt/conda/bin:/usr/local/cuda/bin:$PATH
export PARALLEL_LEVEL=${PARALLEL_LEVEL:-4}
# Set home to the job's workspace
export HOME="$WORKSPACE"
# Switch to project root; also root of repo checkout
cd "$WORKSPACE"
# Determine CUDA release version
export CUDA_REL=${CUDA_VERSION%.*}
################################################################################
# SETUP - Check environment
################################################################################
gpuci_logger "Check environment variables"
env
gpuci_logger "Check GPU usage"
nvidia-smi
gpuci_logger "Activate conda env"
. /opt/conda/etc/profile.d/conda.sh
conda activate dask
gpuci_logger "Install dask"
python -m pip install git+https://github.com/dask/dask
gpuci_logger "Install distributed"
python -m pip install -e .
gpuci_logger "Check Python versions"
python --version
gpuci_logger "Check conda environment"
conda info
conda config --show-sources
conda list --show-channel-urls
gpuci_logger "Python py.test for distributed"
py.test distributed -v -m gpu --runslow --junitxml="$WORKSPACE/junit-distributed.xml"
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