딥러닝
mmaction의 Dockerfile설정하는 방법(docker-compose도)
jennyiscoding
2024. 12. 11. 16:52
Dockerfile
ARG PYTORCH="1.8.1"
ARG CUDA="10.2"
ARG CUDNN="7"
#부터
FROM nvcr.io/nvidia/ai-workbench/python-cuda120:1.0.3
# Python 패키지 업데이트 및 PyTorch 설치
RUN pip install pip --upgrade
RUN pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
#까지
ENV TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0+PTX"
ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
ENV PYTHONPATH=/workspace:$PYTHONPATH
RUN apt-get -y install wget
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub 32
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
RUN apt-get update && apt-get install -y git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 ffmpeg \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
RUN pip install openmim
RUN pip install mmengine==0.9.0
RUN pip install mmcv==2.1.0
docker-compose.yml
version: '3.7'
services:
test:
build: ./docker
container_name: mmaction_test
image: mmaction_test_image
volumes:
- ./:/workspace
environment:
TZ: "Asia/Seoul"
working_dir: /workspace
command: tail -F /dev/null
# 명령어: 프로세스가 지속적으로 실행됨!!