Get error message "unrecognized arguments: rocm" when running mlperf inference on ubuntu with rocm

The command used to run mlperf inference for resnet50 model on ubuntu with rocm is below:
cm run script --tags=run-mlperf,inference
--model=resnet50
--implementation=reference
--framework=tensorflow
--category=edge
--scenario=Offline
--execution-mode=valid
--device=rocm
--quiet

The error message and log infrmation are below:
CM script::benchmark-program/run.sh

Run Directory: /disk1/jerry.zhao/CM/repos/local/cache/5cdd269f823046d5/inference/vision/classification_and_detection

CMD: ./run_local.sh onnxruntime resnet50 rocm --scenario Offline --mlperf_conf '/disk1/jerry.zhao/CM/repos/local/cache/5cdd269f823046d5/inference/mlperf.conf' --threads 16 --user_conf '/disk1/jerry.zhao/CM/repos/mlcommons@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/a40cae1d70c649feac756b3543fc8808.conf' --use_preprocessed_dataset --cache_dir /disk1/jerry.zhao/CM/repos/local/cache/3f75b8874c5d4ed1 --dataset-list /disk1/jerry.zhao/CM/repos/local/cache/66248d197b4c4232/data/val.txt 2>&1 | tee /disk1/jerry.zhao/CM/valid_results/yz_adm5-reference-rocm-onnxruntime-vdefault-default_config/resnet50/offline/performance/run_1/console.out

     ! cd /disk1/jerry.zhao/CM
     ! call /disk1/jerry.zhao/CM/repos/mlcommons@cm4mlops/script/benchmark-program/run-ubuntu.sh from tmp-run.sh

python3 python/main.py --profile resnet50-onnxruntime --mlperf_conf ../../mlperf.conf --model "/disk1/jerry.zhao/CM/repos/local/cache/71e2a9b6a8504033/resnet50_v1.onnx" --dataset-path /disk1/jerry.zhao/CM/repos/local/cache/3f75b8874c5d4ed1 --output "/disk1/jerry.zhao/CM/valid_results/yz_adm5-reference-rocm-onnxruntime-vdefault-default_config/resnet50/offline/performance/run_1" rocm --scenario Offline --mlperf_conf /disk1/jerry.zhao/CM/repos/local/cache/5cdd269f823046d5/inference/mlperf.conf --threads 16 --user_conf /disk1/jerry.zhao/CM/repos/mlcommons@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/a40cae1d70c649feac756b3543fc8808.conf --use_preprocessed_dataset --cache_dir /disk1/jerry.zhao/CM/repos/local/cache/3f75b8874c5d4ed1 --dataset-list /disk1/jerry.zhao/CM/repos/local/cache/66248d197b4c4232/data/val.txt
usage: main.py [-h]
[--dataset {imagenet,imagenet_mobilenet,imagenet_pytorch,coco-300,coco-300-pt,openimages-300-retinanet,openimages-800-retinanet,openimages-1200-retinanet,openimages-800-retinanet-onnx,coco-1200,coco-1200-onnx,coco-1200-pt,coco-1200-tf}]
--dataset-path DATASET_PATH [--dataset-list DATASET_LIST]
[--data-format {NCHW,NHWC}]
[--profile {defaults,resnet50-tf,resnet50-pytorch,resnet50-onnxruntime,resnet50-ncnn,mobilenet-tf,mobilenet-onnxruntime,ssd-mobilenet-tf,ssd-mobilenet-pytorch,ssd-mobilenet-onnxruntime,ssd-resnet34-tf,ssd-resnet34-pytorch,ssd-resnet34-onnxruntime,ssd-resnet34-onnxruntime-tf,retinanet-pytorch,retinanet-onnxruntime}]
[--scenario SCENARIO] [--max-batchsize MAX_BATCHSIZE] --model
MODEL [--output OUTPUT] [--inputs INPUTS] [--outputs OUTPUTS]
[--backend BACKEND] [--model-name MODEL_NAME]
[--threads THREADS] [--qps QPS] [--cache CACHE]
[--cache_dir CACHE_DIR] [--preprocessed_dir PREPROCESSED_DIR]
[--use_preprocessed_dataset] [--accuracy]
[--find-peak-performance] [--debug] [--mlperf_conf MLPERF_CONF]
[--user_conf USER_CONF] [--audit_conf AUDIT_CONF] [--time TIME]
[--count COUNT]
[--performance-sample-count PERFORMANCE_SAMPLE_COUNT]
[--max-latency MAX_LATENCY]
[--samples-per-query SAMPLES_PER_QUERY]
main.py: error: unrecognized arguments: rocm
! call "postprocess" from /disk1/jerry.zhao/CM/repos/mlcommons@cm4mlops/script/benchmark-program/customize.py

Start with the generated command in benchmark-program/run.sh and the referenced python/main.py entry point, then trace how run_local.sh passes the device value. Re-run the provided MLPerf ResNet-50 command on Ubuntu with ROCm and confirm that the benchmark accepts the device without reporting "unrecognized arguments: rocm".