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Upstream: https://github.com/michaelgillett/mjlab Upstream-Commit: c19f713c415a699a79d71cd96aa13c3104a05047 Upstream-Branch: main
38 lines
1.3 KiB
Bash
38 lines
1.3 KiB
Bash
#!/usr/bin/env sh
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#
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# Injects useful arguments for running mjlab in docker.
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# See docs/source/installation.rst for usage.
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#
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# Patterned after the uv-in-docker example:
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# https://github.com/astral-sh/uv-docker-example/blob/5748835918ec293d547bbe0e42df34e140aca1eb/run.sh
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#
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# Key arguments:
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# --rm Remove the container after exiting
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# --runtime=nvidia Use NVIDIA Container runtime to give GPU access
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# --gpus all Expose all GPUs by default
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# -v .:/app Mount current directory to /app (code changes don't require rebuild)
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# -v /app/.venv Mount venv separately (keeps developer's environment out of container)
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# -p 8080:8080 Publish port 8080 for viewing mjlab web interface on the host
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# -it (conditional) Launch in interactive mode if running in a terminal
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# (Note: if running training, there's a blocking wandb prompt before training begins)
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# docker build Build and launch the image (tag matches the Makefile)
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# "$@" Forward all arguments to the docker image
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if [ -t 1 ]; then
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INTERACTIVE="-it"
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else
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INTERACTIVE=""
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fi
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docker run \
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--rm \
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--runtime=nvidia \
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--gpus all \
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--volume .:/app \
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--volume /app/.venv \
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--publish 8080:8080 \
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$INTERACTIVE \
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$(docker build -qt mjlab .) \
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"$@"
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