TensorRT
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i have some problems about my work, when i use tensorRT to convert file pt to file.wts and this step $ sudo ./yolov7 -s yolov7-tiny.wts yolov7-tiny.engine t, i meet this problems, can i help me, please....
jetson@duongphiv5-desktop:~/JetsonYOLOv7-TensorRT/yolov7/build$ sudo ./yolov7 -s yolov7-tiny.engine t Using engine, please wait for a while... weights: yolov7-tiny.wts ... [02/24/2023-13:22:21] [E] [TRT] (Unnamed Layer* 187) [Convolution]: kernel weights has count 648 but 5760 was expected [02/24/2023-13:22:21] [E] [TRT] (Unnamed Layer* 187) [Convolution]: count of 32640 weights in kernel, but kernel dimensions (1,1) with 128 input channels, 45 output channels and 1 groups were specified. weights count is 128 * 45 * 1 * 1 = 5760 ... [02/24/2023-13:22:21] [E] [TRT] Network must have at least one output [02/24/2023-13:22:21] [E] [TRT] Network validation failed. /home/duongphiv5/JetsonYOLOv7-TensorRT/yolov7/main.cpp:38: void serialize_engine(): Assertion `engine' failed. Aborted
This my all versions in Jetson Nano: CUDA: 10.2.300 cuDNN: 8.2.1.32 TensorRT: 8.2.1.8 VPI: 1.2.3 Vulkan: 1.2.70 OpenCV: 4.5.1 with CUDA: YES Module: NVIDIA Jetson Nano (4 GB ram) SoC: tegra210 CUDA Arch BIN: 5.3 Codename: Porg L4T: 32.7.4 Jetpack: 4.6.4
### Tasks
[02/24/2023-13:22:21] [E] [TRT] (Unnamed Layer* 187) [Convolution]: kernel weights has count 648 but 5760 was expected [02/24/2023-13:22:21] [E] [TRT] (Unnamed Layer* 187) [Convolution]: count of 32640 weights in kernel, but kernel dimensions (1,1) with 128 input channels, 45 output channels and 1 groups were specified. weights count is 128 * 45 * 1 * 1 = 5760
Looks like incompatible input/weight shapes. Does it work with onnxruntime?
can you give me some tutorial about onnxruntime?, i just trained dataset on gg colab and get last.pt , then i want to convert it to wts and build engine file , but these error appeared , i have gotten stuck in this problem for a long time
How about just export the model to onnx and use our onnx parser?
closing since no activity for more than 3 weeks, pls reopen if you still have question. Thanks!