Hi, I am using the onnx_tensorrt library to convert onnx model to tensorrt model on runtime. But since it is building the tensorrt engine on runtime it takes more than 4minutes to complete. So i want to use direct tensorrt engine file directly without building on runtime. For this, i have converted…

Hi, The error is caused by the host_inputs parameter. It seems that you don’t allocate the buffer for host_inputs, cuda_inputs, host_outputs, cuda_outputs. Please check the sample code and add it to your source. Thanks.

Hi, You can find an example to deploy an ONNX model with TensorRT API directly below: [image] Custom ResNet Jetson Xavier Jetson Xavier NX Hi, The error comes from dynamic shape usage. If you don’t need to reshape the model at the runtime, please set EXPLICIT_BATCH to u…

Getting following error. File “trt.py”, line 42, in Inference np.copyto(host_inputs[0], image.ravel()) IndexError: list index out of range Source code: import cv2 import time import numpy as np import tensorrt as trt import pycuda.autoinit import pycuda.driver as cuda import os EXPLICIT_…

How to load tensorrt engine directly with building on runtime

Robotics & Edge Computing Jetson Systems Jetson Nano

AastaLLL July 19, 2021, 3:59am 3

Hi,

You can find an example to deploy an ONNX model with TensorRT API directly below:

Thanks.

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How to load tensorrt engine directly with building on runtime

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