A docker deep learning environment setup for my workstation.

dlkit-torch.dockerfile

# docker build -t dlkit -f dlkit.dockerfile .
# docker run -itd --gpus all -p 8888:8888 -p 6006:6006 --ipc host -v ~/workspace/dlkit1:/workspace --name dlkit1 dlkit

FROM pytorch/pytorch:2.2.1-cuda12.1-cudnn8-runtime

ENV SHELL=/bin/bash

WORKDIR /workspace

RUN pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
RUN sed -i 's/archive.ubuntu.com/mirrors.ustc.edu.cn/g' /etc/apt/sources.list
RUN sed -i 's/security.ubuntu.com/mirrors.ustc.edu.cn/g' /etc/apt/sources.list

RUN ln -s /usr/bin/python3 /usr/bin/python

RUN apt-get update && apt-get install -y \
    vim \
    git

RUN pip install jupyterlab tensorboard

COPY entrypoint.sh /entrypoint.sh
RUN chmod +x /entrypoint.sh

EXPOSE 8888
EXPOSE 6006

ENTRYPOINT ["/entrypoint.sh"]

entrypoint.sh

#!/bin/bash

jupyter lab --ip=0.0.0.0 --port=8888 --allow-root --no-browser &

tensorboard --logdir /workspace/tf-logs --bind_all &

wait -n

exit $?