Tutoriel Apprentissage machine

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This article is a draft

This is not a complete article: This is a draft, a work in progress that is intended to be published into an article, which may or may not be ready for inclusion in the main wiki. It should not necessarily be considered factual or authoritative.




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Archivage d'un ensemble de données

Préparation de l'environnement

  • Créez et activez un environnement virtuel de test dans votre home
  • Tentez d'exécuter votre script
  • Installez les packages manquants s'il y a lieu
  • pip freeze > requirements.txt

Si vous avez absolument besoin de GPU pour lancer le script, effectuez les points ci-haut dans une [Running_jobs/fr#T.C3.A2ches_interactivestâche interactive].


Préparation du script de soumission

File : ml-test.sh

#!/bin/bash
#SBATCH --gres=gpu:1       # Request GPU "generic resources"
#SBATCH --cpus-per-task=6  # Cores proportional to GPUs: 6 on Cedar, 16 on Graham.
#SBATCH --mem=32000M       # Memory proportional to GPUs: 32000 Cedar, 64000 Graham.
#SBATCH --time=0-03:00
#SBATCH --output=%N-%j.out

SOURCEDIR=~/scratch/ml-test

module load python/3.6
virtualenv --no-download $SLURM_TMPDIR/env
source $SLURM_TMPDIR/env/bin/activate
pip install --no-index -r $SOURCEDIR/requirements.txt

python $SOURCEDIR/test.py