Running dlrm cpu inference ends up using resnet50

[yuyantingzero]

Ran with cm run script "app mlperf reference inference _dlrm _cpu" --env.CM_RERUN.

From the attached log file, I saw pulling dlrm cm run script "get dlrm src", but when actually running the benchmark, it becames python3 python/main.py --profile resnet50-onnxruntime --mlperf_conf ../../mlperf.conf --model "/home/perfkit/CM/repos/local/cache/0f978e30da8a423a/resnet50_v1.onnx" ...

Any help is appreciated, thanks!

dlrm.txt

[arjunsuresh]

Can you please share the README link you are following here? Dlrm is replaced by dlrm_v2 in the MLPerf Inference and only dlrm_v2 is supported in CM. For dlrm_v2, the download of the criteo dataset should be done manually.

[yuyantingzero]

This is the repo/script I am looking at.

Upon checking, did use the wrong model name, changing to _dlrm_99 gets me a little bit further. But now i am running into

Traceback (most recent call last):
  File "/home/perfkit/CM/repos/local/cache/ae4e0392ff6d45b1/inference/recommendation/dlrm_v2/pytorch/python/main.py", line 20, in <module>
    import mlperf_loadgen as lg
ModuleNotFoundError: No module named 'mlperf_loadgen'

For data downloading, is there a page I can reference?
I tired cm run script --tags=get,ml-model,dlrm,raw,terabyte,criteo-terabyte,criteo,recommendation from get-ml-model-dlrm-terabyte which downloads a 90GB file tb00_40M.onnx.tar