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#!/bin/sh
#To be used before srun so that interactive sessions are run with gpu support
#SBATCH -N 1 # nodes requested
#SBATCH -n 1 # tasks requested
#SBATCH --gres=gpu:1
#SBATCH --mem=16000 # memory in Mb
#SBATCH -o gpu_outfile # send stdout to sample_experiment_outfile
#SBATCH -e gpu_errfile # send stderr to sample_experiment_errfile
#SBATCH -t 8:00:00 # time requested in hour:minute:second
export CUDA_HOME=/opt/cuda-8.0.44
export CUDNN_HOME=/opt/cuDNN-6.0_8.0
export STUDENT_ID=$(whoami)
export LD_LIBRARY_PATH=${CUDNN_HOME}/lib64:${CUDA_HOME}/lib64:$LD_LIBRARY_PATH
export LIBRARY_PATH=${CUDNN_HOME}/lib64:$LIBRARY_PATH
export CPATH=${CUDNN_HOME}/include:$CPATH
export PATH=${CUDA_HOME}/bin:${PATH}
export PYTHON_PATH=$PATH
mkdir -p /disk/scratch/${STUDENT_ID}
export TMPDIR=/disk/scratch/${STUDENT_ID}/
export TMP=/disk/scratch/${STUDENT_ID}/
# Activate the relevant virtual environment:
# source /home/${STUDENT_ID}/miniconda3/bin/activate tf_py2
source venv/bin/activate
CUDA_VISIBLE_DEVICES=0 ./char30.sh
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