Keras
Accelerator Server
important
When you use a machine learning environment, please change the current directory to /work_da area and submit the job to CA_001g queue.
The job script is as follows.
#!/bin/sh #PBS -l select=1[:ncpus=number of CPU][:ngpus=number of GPU] #PBS -q CA_001g #PBS -N jobname #PBS -v DOCKER_IMAGE= conda3/mlenv:tag cd $PBS_O_WORKDIR python input file > output file 2> error file
(Example)
#!/bin/sh #PBS -l select=1 #PBS -q CA_001g #PBS -N Keras #PBS -v DOCKER_IMAGE=conda3/mlenv:cuda10.1-007 cd $PBS_O_WORKDIR python cifar100_resnet_multigpu.py > cifar100.out 2> cifar100.err
The command for interactive mode is as follows.
$ qsub -I -q CA_001g -v DOCKER_IMAGE=conda3/mlenv:tag
(Example)
$ qsub -I -q CA_001g -v DOCKER_IMAGE=conda3/mlenv:cuda10.1-007 qsub: waiting for job 26269.gpu1 to start qsub: job 26269.gpu1 ready bash-4.2$ cd $PBS_O_WORKDIR bash-4.2$ python cifar100_resnet_multigpu.py > cifar100.out 2> cifar100.err