Configuration file

# If true, makes remi's output more explicit
verbose: false

# Name for your project
project_name: PROJECT_NAME


# Inria username
username: INRIA_USERNAME


# Location of the project on the remote computer
project_remote_path: /scratch/INRIA_DESKTOP_HOSTNAME/INRIA_USERNAME/.remi_projects/PROJECT_NAME


desktop:
  # Name of your Inria workstation
  hostname: INRIA_DESKTOP_HOSTNAME

  ip_adress: INRIA_DESKTOP_HOSTNAME.inrialpes.fr

  # Whether to use the singularity container when running jobs on the workstations.
  use_container: true

  # Desktop background jobs
  background:
    # Which backend to use (`screen` or `tmux`)
    backend: screen

    # Whether to keep the session alive after the job has ended.
    # It lets you attach to the session to see the program output.
    # If 'false', the session will be closed when the job is over and stdout/stderr will be
    # lost.
    # CAUTION: If true, you will have to manually re-attach and close the session.
    keep_session_alive: false


# Bastion used to ssh into Inria resources
bastion:
  enable: true
  hostname: bastion.inrialpes.fr
  username: INRIA_USERNAME


# Singularity container options
singularity:
  # The name of the 'recipe' file (`.def`) to build the singularity container.
  def_file_name: container.def

  # The name of the singularity image.
  output_sif_name: container.sif

  # A dictionnary of binds for the singularity container.
  # If the value is empty (''), the mount point is the same as the path on the host.
  # By default, the project folder is bound within the singularity container: This configuration
  # then allows you to add extra locations.
  # Example:
  #     /path_on_host/my_data: /path_in_container/my_data
  bindings:

  # Whether to bind beegfs. (It will be available as `/beegfs/` in the container).
  bind_beegfs: false

  # A dictionnary of environment variables to pass to the container.
  # Example:
  #     FOO: bar
  #     TERM: xterm
  #     LONG: "This is a long sentence"
  #     NUMBER_OF_NEURONS: 56
  #     EMPTY:
  env_variables:

  # The HOMEDIR is mounted by default by singularity.
  # If you want to disable this behavior, set the following option to true.
  # Learn more: https://docs.sylabs.io/guides/3.1/user-guide/bind_paths_and_mounts.html#using-no-home-and-containall-flags
  no_home: false


# Oarsub options (for more details on `oarsub`, please refer to
# https://oar.imag.fr/docs/latest/user/commands/oarsub.html).
oarsub:

  # Job name
  job_name: PROJECT_NAME

  # Number of hosts requested.
  num_hosts: 1

  # Number of cpu cores requested.
  # If the value is 0, all the cores for the requested cpus will be used.
  num_cpu_cores: 0

  # Number of GPUs requested.
  # If the value is 0, no GPU will be requested (CPU only).
  num_gpus: 1

  # The maximum allowed duration for your job.
  walltime: '72:00:00'

  # The name of the requested cluster (perception, mistis, thoth...)
  cluster_name: perception

  # Optionnaly specify the id of a specific node (gpu3, node2...)
  host_id:

  # If the options above are too restricive for your use-case, you may
  # directly provide a property list that will be provided to `oarsub` with the
  # `-p` flag.
  custom_property_query:

  # Whether to schedule the job in the besteffort queue.
  besteffort: true

  # Whether to set the job as idempotent (see oarsub documentation for more details).
  idempotent: false

  # Template name for the log files.
  # By default the log files are named: YYYY-MM-DD_hh-mm-ss.JOB_ID.JOB_NAME.std[out, err]
  # Ex: 2022-06-12_14-47-52.7502202.bce_type2_EaConv1d.stdout
  #
  # You can use '%jobid%' and '%jobname%' to reference the job id and name.
  # '.stdout' and '.stdout' is appended at the end automatically.
  #
  # Example:
  #     log_file_name: 'oar_log_%jobid%_%jobname%'
  log_file_name:


gricad:
  username: PERSEUS_USERNAME

  # The Gricad cluster (bigfoot, dahu, luke, froggy)
  prefered_cluster: bigfoot

  # The Gricad project you are a member of
  # see: https://gricad-doc.univ-grenoble-alpes.fr/en/services/perseus-ng/3_project/
  project_name: pr-ml3ri

  # Location of the project on the remote computer
  project_remote_path: /bettik/PERSEUS_USERNAME/.remi_projects/PROJECT_NAME

  # Whether to use the singularity container when running jobs on Gricad
  use_container: true

  # The name of the singularity image.
  singularity_image: container.sif

  oarsub:

    # Job name
    job_name: PROJECT_NAME

    # Number of nodes requested.
    num_nodes: 1

    # Number of cpus requested (per requested node).
    # If the value is 0, all the cpus for the requested node will be used.
    num_cpus: 0

    # Number of cpu cores requested.
    # If the value is 0, all the cores for the requested cpus will be used.
    num_cpu_cores: 0

    # Number of GPUs requested.
    # If the value is 0, no GPU will be requested (CPU only).
    num_gpus: 1

    # GPU model (leave blank if you have no preference)
    # Possible values: 'A100', 'V100', 'T4'
    gpu_model: V100

    # The maximum allowed duration for your job.
    walltime: '48:00:00'

    # Template name for the log files.
    # By default the log files are named: YYYY-MM-DD_hh-mm-ss.JOB_ID.JOB_NAME.std[out, err]
    # Ex: 2022-06-12_14-47-52.7502202.bce_type2_EaConv1d.stdout
    #
    # You can use '%jobid%' and '%jobname%' to reference the job id and name.
    # '.stdout' and '.stdout' is appended at the end automatically.
    #
    # Example:
    #     log_file_name: 'oar_log_%jobid%_%jobname%'
    log_file_name:


# Remote servers
# Remote servers are applications that run on a remote computer and can be accessed from your local
# browser thanks to remi.
#
# Two such servers are supported right now:
# - Jupyter notebook
# - TensorBoard
remote_servers:
  # The command to run for opening the local browser (`<browser_cmd> <url>`)
  browser_cmd: firefox

  # Jupyter notebook
  jupyter:
    # The port (local and remote) for the server
    port: 8080

    # If true, automatically open the jupyter notebook in the local browser.
    open_browser: true

  # TensorBoard
  tensorboard:
    # The port (local and remote) for TensorBoard
    port: 9090

    # Directory from where to run tensorboard.
    logdir: 'output/'

    # If true, automatically open TensorBoard in the local browser.
    open_browser: true