Cupy config shows no cuda device - docker

Question

I built a docker contaiener to be deployed on HPC+GPU via singularity. when i run
cp.show_config()
OS: Linux-5.4.0-135-generic-x86_64-with-glibc2.31
Python Version: 3.9.12
CuPy Version: 9.6.0
CuPy Platform: NVIDIA CUDA
NumPy Version: 1.21.5
SciPy Version: 1.6.0
Cython Build Version: 0.29.24
Cython Runtime Version: 0.29.28
CUDA Root: /opt/conda/envs/rapids
nvcc PATH: None
CUDA Build Version: 11020
CUDA Driver Version: 11060
CUDA Runtime Version: CUDARuntimeError('cudaErrorNoDevice: no
CUDA-capable device is detected')
cuBLAS Version: (available)
cuFFT Version: 10400
cuRAND Version: 10203
cuSOLVER Version: (11, 3, 4)
cuSPARSE Version: (available)
NVRTC Version: (11, 2)
Thrust Version: 101000
CUB Build Version: 101000
Jitify Build Version: 65946d2
cuDNN Build Version: None
cuDNN Version: None
NCCL Build Version: 21104
NCCL Runtime Version: 21210
cuTENSOR Version: None
cuSPARSELt Build Version: None
this is my dockerfile
# Pulls the basic Image from NVIDIA repository
FROM rapidsai/rapidsai:22.04-cuda11.2-runtime-ubuntu20.04-py3.9
# OS install cuda toolkit
RUN apt-get update
RUN apt-get install -y cuda-toolkit-11.2
# Pulls the basic Image from NVIDIA repository
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
--fix-missing git python3-setuptools python3-pip build-essential libcurl4-gnutls-dev \
zlib1g-dev rsync vim cmake tabix && \
apt-get clean
# Conda install on base env cudnn
RUN conda install --yes -c conda-forge cudnn=8.0.5.39
# Adding env directory to path and activate rapids env
ENV PATH /opt/conda/envs/rapids/bin:$PATH
RUN /bin/bash -c "source activate rapids"
# Install libraries needed in the examples
RUN pip install \
scanpy==1.9.1 wget pytabix dash-daq \
dash-html-components dash-bootstrap-components dash-core-components \
pytest utils tensorflow
RUN pip install --upgrade tensorflow-gpu
WORKDIR /workspace
ENV HOME /workspace
RUN mkdir -p /.singularity.d/env
RUN echo "#!/usr/bin/env bash" > /.singularity.d/env/99-custom_prompt.sh
RUN echo 'PS1="[${SINGULARITY_NAME%.*}]\u#\h:\w\$ "' >> /.singularity.d/env/99-custom_prompt.sh
RUN conda install batchspawner

Answer 1

I hope this could help other members
# Pulls the basic Image from NVIDIA repository
FROM rapidsai/rapidsai:22.04-cuda11.2-runtime-ubuntu20.04-py3.9
# OS install cuda toolkit
RUN apt-get update
RUN apt-get install -y software-properties-common \
cuda-toolkit-11.2 \
python3-setuptools
# Add Nvidia cudnn repository
ENV OS=ubuntu2004
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
RUN mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/7fa2af80.pub
RUN add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/ /"
RUN apt-get update
# Fix Cuda and Cudnn version
ENV cudnn_version=8.1.1.33
ENV cuda_version=cuda11.2
# Install CUDNN
RUN apt-get install -y libcudnn8=${cudnn_version}-1+${cuda_version}
RUN apt-get install -y libcudnn8-dev=${cudnn_version}-1+${cuda_version}
# Adding env directory to path and activate rapids env
ENV PATH /opt/conda/envs/rapids/bin:$PATH
RUN /bin/bash -c "source activate rapids"
# Install libraries needed in the examples
RUN pip install \
scanpy==1.9.1 \
pytabix \
dash-daq \
dash-html-components \
dash-bootstrap-components \
dash-core-components \
pytest \
utils tensorflow
#
WORKDIR /workspace
ENV HOME /workspace
#