Docker step fails in object_detection benchmark #619
Comments
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Same Problem. This works for me. According to this issue of Pytorch cuda does not install. I change Dockerfile WORKDIR /workspace/object_detection
COPY . .
RUN cd pytorch \
&& rm -rf build/ \
&& TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;6.1;7.0;7.5;8.0;8.6+PTX" python setup.py clean build develop --userYou need to check you cuda version, Choose you own TORCH_CUDA_ARCH_LIST, According to this script: CUDA_VERSION=$(/usr/local/cuda/bin/nvcc --version | sed -n 's/^.*release \([0-9]\+\.[0-9]\+\).*$/\1/p')
if [[ ${CUDA_VERSION} == 9.0* ]]; then
export TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;7.0+PTX"
elif [[ ${CUDA_VERSION} == 9.2* ]]; then
export TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;6.1;7.0+PTX"
elif [[ ${CUDA_VERSION} == 10.* ]]; then
export TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;6.1;7.0;7.5+PTX"
elif [[ ${CUDA_VERSION} == 11.0* ]]; then
export TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;6.1;7.0;7.5;8.0+PTX"
elif [[ ${CUDA_VERSION} == 11.* ]]; then
export TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;6.1;7.0;7.5;8.0;8.6+PTX"
else
echo "unsupported cuda version."
exit 1
fi |
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Works fine. Thank you. |
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Apparently, the object_detection fails at the docker step. Although I have CUDA-11.6 on the host machine, it says no CUDA found, too.
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