diff --git a/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh b/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh index 59afff9db6ebb31a947cc972636d70e86ee3deb9..5a04b7afa4ead6799772d514a0f4de1f81e2a7a9 100644 --- a/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh +++ b/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh @@ -1,13 +1,8 @@ #!/bin/bash -MODULE_NAME=nnunet_for_pytorch -MODULE_VERSION=21.11.0 -WORK_DIR=/proj/nsc_testing/xuan/berzelius-benchmarks/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet -CONTAINER_DIR=/proj/nsc_testing/xuan/containers/${MODULE_NAME}_${MODULE_VERSION}.sif SBATCH_DIR=$WORK_DIR/sbatch_scripts/benchmark_${6}_${5}_dim${1}_nodes${2}_gpus${3}_batchsize_${4}.sbatch SBATCH_OUT_DIR=$WORK_DIR/sbatch_out/benchmark_${6}_${5}_dim${1}_nodes${2}_gpus${3}_batchsize_${4}.out LOG_DIR=benchmark_${6}_${5}_dim${1}_nodes${2}_gpus${3}_batchsize_${4}_amp.json -mkdir -p $WORK_DIR/sbatch_out $WORK_DIR/sbatch_scripts cat <<EOT > $SBATCH_DIR #!/bin/bash @@ -15,7 +10,7 @@ cat <<EOT > $SBATCH_DIR #SBATCH -A nsc #SBATCH --nodes=${2} #SBATCH --gpus=${3} -#SBATCH --time=0-0:10:00 +#SBATCH --time=0-0:20:00 #SBATCH --output=$SBATCH_OUT_DIR EOT diff --git a/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh b/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh index 09198942b5ad233ac61b576ecbaae0352f4213b6..729eba6c01b630f7f7b6335eec564e3763064032 100644 --- a/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh +++ b/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh @@ -1,7 +1,12 @@ #!/bin/bash set -e -WORK_DIR=/proj/nsc_testing/xuan/berzelius-benchmarks/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet +export MODULE_NAME=nnunet_for_pytorch +export MODULE_VERSION=21.11.0 +export WORK_DIR=/proj/nsc_testing/xuan/berzelius-benchmarks/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet +export CONTAINER_DIR=/proj/nsc_testing/xuan/containers/${MODULE_NAME}_${MODULE_VERSION}.sif +mkdir -p $WORK_DIR/sbatch_out $WORK_DIR/sbatch_scripts $WORK_DIR/results + benchmark_modes=("train" "predict") # node_types=("thin" "fat") node_types=("thin")