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version: "3"
services:
model-cuda:
env_file:
- .env
user: "${UID}:${GID}"
build:
context: .
dockerfile: DockerfileCUDA
tty: true
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
volumes:
- ./logs/:/usr/src/app/logs:z
- ./data/:/usr/src/app/data:z
command: sh -c "python train.py logger=tensorboard trainer.gpus=1"
model:
env_file:
- .env
user: "${UID}:${GID}"
build:
context: .
dockerfile: Dockerfile
tty: true
volumes:
- ./logs/:/usr/src/app/logs:z
- ./data/:/usr/src/app/data:z
command: sh -c "python train.py logger=tensorboard trainer.gpus=0"
tensorboard:
image: tensorflow/tensorflow
volumes:
- ./logs:/logs:z
command: sh -c "tensorboard --logdir /logs --bind_all"
ports:
- 8008:6006
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