i 've downloaded a ddd_3dop.pth model trained by pytorch , i am sure it used a DCNv2 operation when trained, i 've converted it into onnx formats, and converted its plugins into DCNv2 “names” in order to be compatible with my own plugins written in C++ programs, my enviroment is jetson agx xavier, and tensorrt tool is 7.1.3.0, and pytorch version is 1.6.0 and cuda is available as well, here is my details of Xavier:
i 've already done initLibNvInferPlugins some registeration operations in my program, and the program can recognise my “dcnV2” plugins as i assumed, however, the errors occurred when i tried to convert “onnx” model to “.engine” model.
[08/10/2022-16:56:49] [E] [TRT] Add_139: elementwise inputs must have same dimensions or follow broadcast rules (input dimensions were [1,256,2,2] and [1,256,24,80]).
[08/10/2022-16:56:49] [E] [TRT] Add_139: elementwise inputs must have same dimensions or follow broadcast rules (input dimensions were [1,256,2,2] and [1,256,24,80]).
[08/10/2022-16:56:49] [E] [TRT] Add_139: elementwise inputs must have same dimensions or follow broadcast rules (input dimensions were [1,256,2,2] and [1,256,24,80]).
i have no idea why this happened ! i applied the same program in my serve computer which installed tensorrt8.2GA, and pytorch is 1.7.0 cuda version, and it can be successfully transferred into ".engine"model, it is weired…
here are details logs:
[08/10/2022-16:56:49] [E] [TRT] Add_139: elementwise inputs must have same dimensions or follow broadcast rules (input dimensions were [1,256,2,2] and [1,256,24,80]).
[08/10/2022-16:56:49] [E] [TRT] Add_139: elementwise inputs must have same dimensions or follow broadcast rules (input dimensions were [1,256,2,2] and [1,256,24,80]).
[08/10/2022-16:56:49] [E] [TRT] Add_139: elementwise inputs must have same dimensions or follow broadcast rules (input dimensions were [1,256,2,2] and [1,256,24,80]).