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#!/bin/bash -e
# Source: Tools in action by Samuel Antao (AMD)
# Contribution: M. Jaros (IT4Innovations)
wd=$(pwd)
#
# Example assume allocation was created, e.g.:
# N=1 ; salloc -p standard-g --threads-per-core 1 --exclusive -N $N --gpus $((N*8)) -t 4:00:00 --mem 0
#
module purge
module load CrayEnv
module load PrgEnv-cray/8.3.3
module load craype-accel-amd-gfx90a
# Default ROCm – more recent versions are preferable (e.g. ROCm 5.6.0).
module load rocm/5.2.3.lua
set -x
# check dependencies
if [ ! -d $wd/miniconda3/envs/pytorch-from-source ] ; then
echo "use 04-install-source-torch1.13.1-rocm5.2.3.sh"
exit 1
else
source $wd/miniconda3/bin/activate pytorch-from-source
fi
# Make sure conda libs can be loaded.
export LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH
python -c 'import torch; print("I have this many devices:", torch.cuda.device_count())'