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job.sh
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job.sh
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#!/bin/bash
#
#
### comment lines start with ## or #+space
### slurm option lines start with #SBATCH
#SBATCH --job-name=baseline ## job name
#SBATCH --time=2-00:00:00 ## days-hours:minutes:seconds
#SBATCH --mem=8000M ## 3GB ram (hardware ratio is < 4GB/core)
### SBATCH --output=$1/train.log ## standard out file
#SBATCH --ntasks=1 ## Ntasks. default is 1.
#SBATCH --cpus-per-task=1 ## Ncores per task. Use greater than 1 for multi-threaded jobs. default is 1.
###SBATCH --partition=generic ## can specify partition here, but it is pre-empted by what module is loaded
###SBATCH --account=your_tenant_name ## only need to specify if you belong to multiple tenants on ScienceCluster
#SBATCH --gres gpu:1
###SBATCH --gres gpu:Tesla-V100-32GB:1
module load cudnn/7.6.5.32-10.2
module load anaconda3
source activate audio_clf
# pip install torch==1.12.1+cu102 torchvision==0.13.1+cu102 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu102
# pip install scikit-learn
# pip install tensorboard
# pip install pandas
CUBLAS_WORKSPACE_CONFIG=:4096:8 stdbuf -o0 -e0 srun --unbuffered python model.py -c $1