Jetson Nano error when "INT64. Attempting to cast down to INT32"

• Hardware Platform (Jetson / GPU): Jetson
• DeepStream Version: 6.0.1
• JetPack Version (valid for Jetson only): 4.6.6

I refer this GitHub - marcoslucianops/DeepStream-Yolo-Seg: NVIDIA DeepStream SDK 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 implementation for YOLO-Segmentation models for running yolo-seg but meet an issue when converting onnx to tensorRT:

WARNING: [TRT]: onnx2trt_utils.cpp:366: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
ERROR: [TRT]: ModelImporter.cpp:773: While parsing node number 313 [Range -> "/0/model.22/Range_output_0"]:
ERROR: [TRT]: ModelImporter.cpp:774: --- Begin node ---
ERROR: [TRT]: ModelImporter.cpp:775: input: "/0/model.22/Constant_23_output_0"
input: "/0/model.22/Cast_output_0"
input: "/0/model.22/Constant_24_output_0"
output: "/0/model.22/Range_output_0"
name: "/0/model.22/Range"
op_type: "Range"

I tried exporting .pt to .onnx by GoogleColab, Jetson Nano … After that, I used onnx for my app, but it still had errors. However, I tried it on DS7.1 with dGPU, it works correctly when downscasting INT32 and run for my app. Can you help me?

This error is caused by the Range operator not supporting dynamic batch size, so when exporting the onnx model, specify the batch size

 python3 export_yoloV8_seg.py -w yolov8s-seg.pt --batch 32 --simplify

But there will be another error,This problem is caused by the low version of TensorRT. The RoiAlign operator is not supported by TensorRT-8.0.

[01/13/2025-09:23:07] [E] [TRT] 3: getPluginCreator could not find plugin: RoiAlign version: 1
[01/13/2025-09:23:07] [E] [TRT] ModelImporter.cpp:720: While parsing node number 290 [RoiAlign -> "/1/RoiAlign_output_0"]:
[01/13/2025-09:23:07] [E] [TRT] ModelImporter.cpp:721: --- Begin node ---
[01/13/2025-09:23:07] [E] [TRT] ModelImporter.cpp:722: input: "/0/model.22/proto/cv3/act/Mul_output_0"

You can try to port the operator.

Jetson nano cannot be upgraded to a higher version of JetPack, which would be a complicated migration process

This repository is not officially supported. You can consult the author on GitHub.

Thanks for your support!

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