Updated

NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/benchmark.txt

@@ -20,6 +20,9 @@ apptainer exec --nv -B ${WORK_DIR}/data:/data -B ${WORK_DIR}/results:/results --
 
 apptainer exec --nv -B ${WORK_DIR}/data:/data -B ${WORK_DIR}/results:/results --pwd /workspace/nnunet_pyt $CONTAINER_DIR python scripts/benchmark.py --mode predict --gpus 1 --dim 2 --batch_size 256 --amp
 
+
+
+
 ################# Issues #################
 # Known issue https://github.com/NVIDIA/DeepLearningExamples/issues/1113
 ImportError: cannot import name 'get_num_classes' from 'torchmetrics.utilities.data' (/opt/conda/lib/python3.8/site-packages/torchmetrics/utilities/data.py)

NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh

@@ -23,7 +23,7 @@ EOT
 if [ "${6}" = "thin" ]; then
     cat <<EOT >>  $SBATCH_DIR
 #SBATCH -C "thin"    
-##SBATCH --reservation=devel
+#SBATCH --reservation=nodeimage
 EOT
 else
     cat <<EOT >>  $SBATCH_DIR

NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh

 #!/bin/bash
 set -e
 
-WORK_DIR=/proj/nsc_testing/xuan/berzelius-benchmarks/PyTorch/Segmentation/nnUNet
+WORK_DIR=/proj/nsc_testing/xuan/berzelius-benchmarks/NVIDIA/DeepLearningExamples/PyTorch/Segmentation/nnUNet
 benchmark_modes=("train" "predict")
 node_types=("thin" "fat")
 
 dim=2
 for nodes in {1..1}; do
-    for gpus in {1,8}; do
+    for gpus in {1..8}; do
         for benchmark_mode in "${benchmark_modes[@]}"; do
             for node_type in "${node_types[@]}"; do