I am transferring my onnx model to trt model on agx. I successfully dis that on jp4.4 trt 7 with the following command. ./trtexec --onnx=xxx1.onnx --saveEngine=xxx.trt --minShapes=input_1:0:1x224x224x1 --optShapes=input_1:0:2x224x224x1 --maxShapes=input_1:0:2x224x224x1 --workspace=4096 --verbose -…

Hi, Please check below for a sample that has two output tensors. https://github.com/NVIDIA/TensorRT/blob/release/8.2/samples/sampleSSD/sampleSSD.cpp#L336 ... const float* detectionOut = static_cast<const float*>(buffers.getHostBuffer("detection_out")); const int* keepCount = static_ca…

Hi, We have tested your model with JetPack 5.0.2 GA on Xavier. It can work correctly so this should be a known issue and is fixed in the TensorRT 8.4. $ /usr/src/tensorrt/bin/trtexec --onnx=test_nvidia.onnx --saveEngine=test_nvidia.trt --minShapes=input_1:0:1x224x224x1 --optShapes=input_1:0:2x224…

Have you tested on trt 8.2 and reproduced this error? And would you please explain more on why this happened and any solution to work around this error on trt 8.2?

Hi, We can reproduce the same error on TensorRT 8.2. Do you have dependencies on JetPack 4.6.x? If not, it’s recommended to upgrade the software to the latest for the solution. Thanks.

Any more details? We just upgrade the whole project to jp4.6 trt 8.2, keep upgrading in such a short period is not possible.

Hi, There are some issues when handling the concatenate layer generated from PyTorch frameworks. Since the concat layer is at the end of your model, you can just set the tensors right before the layer as output. For example, TensorRT 8.2 can infer your model after the following updates: 1. Insta…

Actually, my ONNX model was generated from TensorFlow. After testing i found that you just removed the last layer (concatenate layer) from the original network, in another word, changing the original one output to two outputs. Though this is not what I am expecting, let me try if it works, and do y…

Hi, You can find a python sample below: https://elinux.org/Jetson/L4T/TRT_Customized_Example#OpenCV_with_PLAN_model Thanks.

[E] Error[1]: [genericReformat.cu::executeMemcpy::1334] Error Code 1: Cuda Runtime (invalid argument)

Robotics & Edge Computing Jetson Systems Jetson AGX Xavier

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TensorRT-8.2 triggers MMU fault on a specific ONNX model Jetson Nano tensorrt	17	370	July 30, 2024
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Skipping tactic 0x0000000000000000 due to Myelin error: Platform (Cuda) error Jetson Orin NX tensorrt	24	2841	January 2, 2023

[E] Error[1]: [genericReformat.cu::executeMemcpy::1334] Error Code 1: Cuda Runtime (invalid argument)

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