54 lines
1.2 KiB
YAML
54 lines
1.2 KiB
YAML
# Configurations for hardware-accelerated machine learning
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# If using Unraid or another platform that doesn't allow multiple Compose files,
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# you can inline the config for a backend by copying its contents
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# into the immich-machine-learning service in the docker-compose.yml file.
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# See https://immich.app/docs/features/ml-hardware-acceleration for info on usage.
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services:
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# armnn:
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# devices:
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# - /dev/mali0:/dev/mali0
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# volumes:
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# - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro
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# - /usr/lib/libmali.so:/usr/lib/libmali.so:ro
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# cpu: {}
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# cuda:
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# deploy:
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# resources:
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# reservations:
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# devices:
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# - driver: nvidia
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# count: 1
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# capabilities:
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# - gpu
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openvino:
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# device_cgroup_rules:
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# - 'c 189:* rmw'
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# devices:
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# - /dev/dri:/dev/dri
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volumes:
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- /dev/bus/usb:/dev/bus/usb
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- /dev/dri:/dev/dri
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hostname: immich-ml
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networks:
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- traefik_backend
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# openvino-wsl:
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# devices:
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# - /dev/dri:/dev/dri
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# - /dev/dxg:/dev/dxg
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# volumes:
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# - /dev/bus/usb:/dev/bus/usb
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# - /usr/lib/wsl:/usr/lib/wsl
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networks:
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postgresql_db-backend:
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external: true
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traefik_backend:
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external: true
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