Open jingyanwangms opened 1 month ago
I think you can export the onnx, then use
import onnxruntime as ort
# set providers to ['TensorrtExecutionProvider', 'CUDAExecutionProvider'] with TensorrtExecutionProvider having the higher priority.
sess = ort.InferenceSession('model.onnx', providers=['TensorrtExecutionProvider', 'CUDAExecutionProvider'])
See more ref https://onnxruntime.ai/docs/execution-providers/
Description
Environment
TensorRT Version: 10.4.0.26-1+cuda12.6 (upgrading from 10.3)
NVIDIA GPU: V100
NVIDIA Driver Version:
CUDA Version: Cuda compilation tools, release 12.5, V12.5.82 CUDNN Version: 9
Operating System:
Python Version (if applicable):
Tensorflow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if so, version): nvidia/cuda:12.5.1-cudnn-devel-ubuntu20.04
Relevant Files
Model link:
Steps To Reproduce
Build onnxruntime
Commands or scripts: In built directory python onnxruntime_test_python_nested_control_flow_op.py
Have you tried the latest release?:
Can this model run on other frameworks? For example run ONNX model with ONNXRuntime (
polygraphy run <model.onnx> --onnxrt
):