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I load the save onnx model via C++ TensorRT and print the information for each layer.
TensorRT 8.6 loaded a model with 21060 layers and TensorRT 10.4 loaded a model with 37921 layers, why is the difference in the number of layers so large?
Description
I inference the groundingDino model using C++ TensorRT.
For the same model and the same image, TensorRT 8.6 can gets the correct detection boxes.
But when I update TensorRT to 10.4, can't get detection boxes.
Possible model result error caused by TensorRT 10.4, How can I analyze this issue?
By the way, I've tried multiple versions other than 8.6 (eg 9.3, 10.0, 10.1), None of them get detection boxes.
Environment
TensorRT Version: 8.6.1.6 / 10.4.0.26
NVIDIA GPU: GeForce RTX 3090
NVIDIA Driver Version: 535.183.06
CUDA Version: 12.2
Relevant Files
Model link: https://drive.google.com/file/d/1VRHKT7cswtDVXNUUmebbPmBSAOyd-fJN/view?usp=drive_link
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