forked from lkrsnik/classla-api
Docker + GPUs.
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Dockerfile.gpu
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11
Dockerfile.gpu
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FROM pytorch/pytorch:1.7.1-cuda11.0-cudnn8-runtime
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ENV PYTHONDONTWRITEBYTECODE 1
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ENV PYTHONUNBUFFERED 1
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ADD . /classla-api
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WORKDIR /classla-api
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RUN pip install $(grep -ivE "torch" requirements.txt)
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CMD [ "python3", "-m" , "flask", "run", "--host=0.0.0.0"]
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version: "3.8"
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version: "3.7"
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services:
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services:
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app:
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app:
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build: .
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build: .
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command: python -m flask run --host=0.0.0.0
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command: python -m flask run --host=0.0.0.0
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deploy:
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runtime: nvidia
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resources:
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environment:
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reservations:
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- NVIDIA_VISIBLE_DEVICES=all
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devices:
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- NVIDIA_DRIVER_CAPABILITIES=all
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- driver: nvidia
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- CUDA_VISIBLE_DEVICES=1
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count: all
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capabilities: [ gpu ]
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ports:
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ports:
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- "5000:5000"
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- "5000:5000"
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volumes:
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volumes:
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