Pytorch yolov5 is failing on A100 GPU

Description

Hello,

running the next code:

python detect.py --weights yolov5s.pt --img 640 --conf 0.25 --source data/images/

on A100 GPU is giving the next error: "RunTimeError: CUDA error: no kernel is availible for execution on the drive.

the running the same conda environment & the same python command & the same OS on RTX 5000 GPU is succesfull.

What is the reson for failure in A100?

Thank you.
Inga

Environment

TensorRT Version:
GPU Type: A100-PCIE-40GB
Nvidia Driver Version: 450.51.06
CUDA Version: 11.0
CUDNN Version:
Operating System + Version: Red Hat Enterprise Linux release 8.3
Python Version (if applicable): 3.9.1
TensorFlow Version (if applicable): N/A
PyTorch Version (if applicable): torch → 1.8.1, torchvision → 0.9.1
Baremetal or Container (if container which image + tag): N/A

Relevant Files

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Steps To Reproduce

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  • Exact steps/commands to build your repro
  • Exact steps/commands to run your repro
  • Full traceback of errors encountered

Hi ,
We recommend you to check the supported features from the below link.
https://docs.nvidia.com/deeplearning/tensorrt/support-matrix/index.html
You can refer below link for all the supported operators list.
For unsupported operators, you need to create a custom plugin to support the operation

Thanks!

Hi @paster,

This forum talks more about updates and issues related to TensorRT. We request you to post your concern on pytorch related platform to get better help.

May be this will help you.

Thank you.