title: keras (tensorflow backend) run on a cluster using slurm
body: <p>I have the opportunity to run my Tensorflow training on a cluster computer with slurm workload manager (the cluster contains nearly 400000 cores, 40000 GB of RAM, Performance is Rmax=500 TFlop/s and Rpeak=1000 TFlop/s, AMD GPUs). </p>
  
  <p>I work on image processing projects using deep learning algorithms.</p>
  
  <p>My question is how to scale my keras deep learning to run on this cluster using slurm as workload manager ?</p>