Bob123Yang
Bob123Yang
Fail to run the 3d-unet-99 with error "No matching distribution found for nvidia-nvcomp-cu12" after my mlc upgrade. mlcr run-mlperf,inference,_find-performance,_full,_r5.0-dev \ --model=3d-unet-99 \ --implementation=nvidia \ --framework=tensorrt \ --category=edge \ --scenario=Offline \...
Hi @arjunsuresh, it's successful to build the docker container by running the be below command but still report the errors. mlcr run-mlperf,inference,_find-performance,_full,_r5.0-dev \ --model=retinanet \ --implementation=nvidia \ --framework=tensorrt \ --category=edge...
I failed to run the mlc command on Ubuntu 22.04: mlcr run-mlperf,inference,_find-performance,_full,_r4.1-dev \ --model=resnet50 \ --implementation=nvidia \ --framework=tensorrt \ --category=edge \ --scenario=Offline \ --execution_mode=test \ --device=cuda \ --docker --quiet \...
Hi @arjunsuresh I have encountered one issue for the docker migration. I run the below command in the system A to build the docker successfully and run the Resnet50 inference...
Hi @arjunsuresh When I was running the below command to build the docker for GPT-J: cm run script --tags=run-mlperf,inference,_find-performance,_full,_r5.0-dev \ --model=gptj-99 \ --implementation=nvidia \ --framework=tensorrt \ --category=edge \ --scenario=Offline \...
Run Resnet50 without the precision parameter in the docker successfully and get the result (measurements.json) that displays data type is int8. Then run Resnet50 again with the precision=float16 as below...
Hi @arjunsuresh **I am running the Resnet50 benchmark with the command:** cm run script --tags=run-mlperf,inference,_find-performance,_full,_r4.1-dev \ --model=resnet50 \ --implementation=nvidia \ --framework=tensorrt \ --category=edge \ --scenario=Offline \ --execution_mode=test \ --device=cuda \...
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