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44 lines
1.2 KiB
YAML
Executable File
44 lines
1.2 KiB
YAML
Executable File
# 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 # Mali firmware for your chipset (not always required depending on the driver)
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- /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)
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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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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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