Skip to content
Snippets Groups Projects
Commit 69c599b0 authored by erow's avatar erow
Browse files

init

parent e6b3e658
No related branches found
No related tags found
No related merge requests found
# This file is a template, and might need editing before it works on your project.
# To contribute improvements to CI/CD templates, please follow the Development guide at:
# https://docs.gitlab.com/ee/development/cicd/templates.html
# This specific template is located at:
# https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/Docker.gitlab-ci.yml
# Build a Docker image with CI/CD and push to the GitLab registry.
# Docker-in-Docker documentation: https://docs.gitlab.com/ee/ci/docker/using_docker_build.html
#
# This template uses one generic job with conditional builds
# for the default branch and all other (MR) branches.
docker-build:
# Use the official docker image.
image: aisurrey:latest
stage: build
services:
- docker:dind
before_script:
- docker login -u "$CI_REGISTRY_USER" -p "$CI_REGISTRY_PASSWORD" $CI_REGISTRY
# Default branch leaves tag empty (= latest tag)
# All other branches are tagged with the escaped branch name (commit ref slug)
script:
- |
if [[ "$CI_COMMIT_BRANCH" == "$CI_DEFAULT_BRANCH" ]]; then
tag=""
echo "Running on default branch '$CI_DEFAULT_BRANCH': tag = 'latest'"
else
tag=":$CI_COMMIT_REF_SLUG"
echo "Running on branch '$CI_COMMIT_BRANCH': tag = $tag"
fi
- docker build --pull -t "$CI_REGISTRY_IMAGE${tag}" .
- docker push "$CI_REGISTRY_IMAGE${tag}"
# Run this job in a branch where a Dockerfile exists
rules:
- if: $CI_COMMIT_BRANCH
exists:
- Dockerfile
ARG PYTORCH="2.1.1"
ARG CUDA="12.1"
ARG CUDNN="8"
# FROM pytorch/pytorch:1.13.1-cuda11.6-cudnn8-runtime
FROM docker.io/pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-runtime
# To fix GPG key error when running apt-get update
# RUN rm /etc/apt/sources.list.d/cuda.list \
# && rm /etc/apt/sources.list.d/nvidia-ml.list \
# && apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub \
# && apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
# Install system dependencies for opencv-python
RUN apt update && apt install -y libgl1 libglib2.0-0 \
&& apt clean
# && rm -rf /var/lib/apt/lists/*
RUN pip install mmcv==2.1.0 -f https://download.openmmlab.com/mmcv/dist/cu121/torch2.1/index.html \
&& pip cache purge
# Verify the installation
RUN python -c 'import mmcv;print(mmcv.__version__)'
# Install FFCV
RUN conda install cupy pkg-config libjpeg-turbo opencv cudatoolkit=${CUDA} numba -c pytorch -c conda-forge
RUN pip install ffcv \
&& pip cache purge
# useful tools
RUN pip install timm wandb imageio pandas gin-config tqdm\
&& pip cache purge
0% Loading or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment