88 lines
1.9 KiB
Markdown
88 lines
1.9 KiB
Markdown
# Docker4ML
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Useful docker scripts for ML developement.
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[https://github.com/SimonLeeGit/Docker4ML](https://github.com/SimonLeeGit/Docker4ML)
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## Build Docker Image
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```bash
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bash docker_build.sh
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```
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## Run Docker Container as Development Envirnoment
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```bash
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bash docker_run.sh
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```
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## Custom Docker Config
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### Config [setup_env.sh](./setup_env.sh)
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You can modify this file to custom your settings.
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```bash
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TAG=ml:dev
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BASE_TAG=nvcr.io/nvidia/pytorch:23.12-py3
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```
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#### TAG
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Your built docker image tag, you can set it as what you what.
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#### BASE_TAG
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The base docker image tag for your built docker image, here we use nvidia pytorch images.
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You can check it from [https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch/tags](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch/tags)
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Also, you can use other docker image as base, such as: [ubuntu](https://hub.docker.com/_/ubuntu/tags)
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### USER_NAME
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Your user name used in docker container.
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### USER_PASSWD
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Your user password used in docker container.
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### Config [requriements.txt](./requirements.txt)
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You can add your default installed python libraries here.
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```txt
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transformers==4.27.1
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```
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By default, it has some libs installed, you can check it from [https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-24-01.html](https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-24-01.html)
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### Config [packages.txt](./packages.txt)
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You can add your default apt-get installed packages here.
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```txt
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wget
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curl
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git
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```
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### Config [ports.txt](./ports.txt)
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You can add some ports enabled for docker container here.
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```txt
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-p 6006:6006
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-p 8080:8080
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```
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### Config [postinstallscript.sh](./postinstallscript.sh)
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You can add your custom script to run when build docker image.
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## Q&A
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If you have any use problems, please contact to <simonlee235@gmail.com>.
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