A simple Dockerfile to create the most basic containers containing cuda, conda and torch.

cuda_conda_Dockerfile

# docker build  -t zach/cuda_conda:cu118-torch21 . --network host
# sudo docker run --gpus all -it --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 --user root -v /mnt/:/mnt/ -v ~/workspace/:~/workspace/ --network host zach/cuda_conda:cu118-torch21


FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04


# Add some dependencies
RUN sed -i 's#http://archive.ubuntu.com/#http://mirrors.tuna.tsinghua.edu.cn/#' /etc/apt/sources.list

RUN apt-get update && \
    apt-get -y install curl unzip wget git tmux htop vim net-tools cmake

# Install Miniconda
RUN wget -c https://repo.anaconda.com/miniconda/Miniconda3-py310_24.1.2-0-Linux-x86_64.sh -O Miniconda.sh && \
    sh Miniconda.sh -b -p /opt/miniconda3 && \
    rm Miniconda.sh

# tells docker to use bash as shell and the -c tells bash to run the following command
SHELL ["/bin/bash", "-c"]

# pip and conda config
RUN source /opt/miniconda3/bin/activate && \
    pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 -i https://download.pytorch.org/whl/cu118 && \
    pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && \
    conda config --set show_channel_urls yes && \
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main && \
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r && \
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2


RUN /bin/bash && \
    source /opt/miniconda3/bin/activate