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Docker image #65
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I've created Dockerfile and it seems to work properly on K80 instance. Here it's: FROM tobycheese/cuda:9.0-cudnn7-devel-ubuntu18.04
RUN apt-get update && apt-get install -y software-properties-common
RUN add-apt-repository ppa:deadsnakes/ppa -y
RUN apt-get update && apt-get install -y --no-install-recommends \
git \
tmux \
nano \
apt-utils \
python3.6 \
python3.6-dev \
python3-pip \
python3-setuptools \
g++-6 \
libsm6 \
libxrender1 \
libxtst6 \
&& \
rm -rf /var/lib/apt/lists/* && \
apt-get update
RUN update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-6 10 && \
update-alternatives --set g++ /usr/bin/g++-6
RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-6 10 && \
update-alternatives --set gcc /usr/bin/gcc-6
RUN git clone https://github.com/NVlabs/planercnn.git
RUN cd planercnn && pip3 install -r requirements.txt && pip3 install h5py torch==0.4.0 -f https://download.pytorch.org/whl/cu92/torch_stable.html
RUN gcc -v && cat /usr/local/cuda/version.txt
RUN ls /usr/local | grep cuda
RUN cd planercnn && \
cd nms/src/cuda/ && \
nvcc -c -o nms_kernel.cu.o nms_kernel.cu -I /usr/local/cuda/include -x cu -Xcompiler -fPIC -arch=sm_37
RUN export LD_LIBRARY_PATH="/usr/local/cuda/include:$LD_LIBRARY_PATH" && \
cd planercnn/nms && \
sed -i 's|extra_objects=extra_objects|extra_objects=extra_objects,\n include_dirs=["/usr/local/cuda/include"]|' build.py && \
python3 build.py
RUN cd planercnn/roialign/roi_align/src/cuda && \
nvcc -c -o crop_and_resize_kernel.cu.o crop_and_resize_kernel.cu -I /usr/local/cuda/include -x cu -Xcompiler -fPIC -arch=sm_37
RUN cd planercnn/roialign/roi_align && \
export LD_LIBRARY_PATH="/usr/local/cuda-9.2/include:$LD_LIBRARY_PATH" && \
sed -i 's|extra_compile_args=extra_compile_args|extra_compile_args=extra_compile_args,\n include_dirs=["/usr/local/cuda/include"]|' build.py && \
python3 build.py
RUN pip3 install torch==0.4.1 -f https://download.pytorch.org/whl/cu92/torch_stable.html However, when you're inside docker you'll have to rerun compilation and build of nms and roi_align as GPU is not visible to the while building docker. So, just run:
|
Hi @oOXpycTOo, I am using dockerfile created by you for "planercnn" project. I am having a system with 4 GPU's with Cuda 11.4. W: GPG error: https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC I have tried a lot of experimentation but could not resolve it. Kindly help me to get out of it. |
Hi developers,
Can you please provide a docker image with the right version of CUDA and gcc?
I have an RTX 2080 GPU and CUDA 11.2 and gcc 7.5.0.
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