deepvats/docker/docker-compose.yml at 4ea262580562f6f7c99075c5c1d4a46d2bb3ffa2 · vrodriguezf/deepvats · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
services:
  jupyter:
    build:
      args:
        - username=${USER_NAME}
        - uid=${USER_ID}
        - gid=${GROUP_ID}
        - CUDA_VERSION=12.2.0-devel-ubuntu20.04
        - JUPYTER_TOKEN=${JUPYTER_TOKEN}
      context: ../
      labels:
        - username=${USER_NAME}
      dockerfile: docker/Dockerfile.jupyter
    image: dvats-jupyter:${USER_NAME}
    ports:
      - "${JUPYTER_PORT}:8888"
    environment:
      - WANDB_ENTITY=${WANDB_ENTITY}
      - WANDB_PROJECT=${WANDB_PROJECT}
      - WANDB_API_KEY=${WANDB_API_KEY}
      - GH_TOKEN=${GH_TOKEN}
      - CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES}
      - WANDB_DIR=/home/${USER_NAME}/work
      - JUPYTER_TOKEN=${JUPYTER_TOKEN}
    volumes:
      - ../:/home/${USER_NAME}/work
      - ${LOCAL_DATA_PATH}:/home/${USER_NAME}/data/
      - conda-env:/usr/local/share/miniconda3/envs/env
      - miniconda:/usr/local/share/miniconda3
    init: true
    stdin_open: true
    tty: true
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]

  rstudio-server:
      build:
          context: ../
          dockerfile: docker/Dockerfile.rstudio
          args:
              - WANDB_API_KEY=${WANDB_API_KEY} #
              - RETICULATE_PYTHON_ENV=/home/env
              - RETICULATE_MINICONDA_PATH=/home/miniconda3
              - USER=${USER_NAME} #*
              - UID=${USER_ID} #*
              - GID=${GROUP_ID} #*
      image: dvats-rstudio:${USER_NAME}
      ports:
          - "${RSTUDIO_PORT}:8787" #*
      environment:
          - WANDB_ENTITY=${WANDB_ENTITY}
          - WANDB_API_KEY=${WANDB_API_KEY}
          - WANDB_PROJECT=${WANDB_PROJECT}
          - USER=${USER_NAME} #*
          - USERID=${USER_ID} #*
          - GROUPID=${GROUP_ID} #*
          - PASSWORD=${RSTUDIO_PASSWD} #*
          - ROOT=FALSE
          - CUDA_VISIBLE_DEVICES=0,1,2
          #- CUDA_VISIBLE_DEVICES=1
            #          - CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES}
          - GH_TOKEN=${GH_TOKEN} #*
          # TODO (28/03/2023): I don't know why it is not working without this
          - ENV_VARS=WANDB_ENTITY,WANDB_API_KEY,WANDB_PROJECT,USER,USERID,GROUPID,PASSWORD,ROOT,CUDA_VISIBLE_DEVICES
      volumes:
         - ../r_shiny_app:/home/${USER_NAME}/app
         - ${LOCAL_DATA_PATH}:/home/${USER_NAME}/data/
         - ../dvats:/home/${USER_NAME}/dvats
         - conda-env:/usr/local/share/miniconda3/envs/env
         - miniconda:/home/user/local/share/miniconda3
         # arreglar bien el error: /home/macu/work/nbs/mplot: No such file or directory
         #- ../nbs/mplot/:/home/${USER_NAME}/work/nbs/mplot
         ####
      deploy:
        resources:
          #limits:
            #cpus: '0.75'
          reservations:
            devices:
              - driver: nvidia
                count: all
                capabilities: [gpu]

volumes:
  conda-env:
  miniconda:
  lib: