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tiny yolov2 doesn't work on raspberry pi zero #89
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hey ho, thanks for reporting this. make clean
make TRACE_LEVEL=1 connxr
./build/connxr test/tiny_yolov2/Model.onnx test/tiny_yolov2/test_data_set_0/input_0.pb 2>&1 | tee tiny_yolov2.log and post the |
pi@raspberrypi:~/cONNXr-master $ ./build/connxr test/tiny_yolov2/Model.onnx test/tiny_yolov2/test_data_set_0/input_0.pb |
thanks! now we know the problem lies in CONNXR_TRACE_FUNCTION="prepare_operator__ai_onnx__mul__7:9" ./build/connxr test/tiny_yolov2/Model.onnx test/tiny_yolov2/test_data_set_0/input_0.pb |
pi@raspberrypi:~/cONNXr-master $ CONNXR_TRACE_FUNCTION="prepare_operator__ai_onnx__mul__7:9" ./build/connxr test/tiny_yolov2/Model.onnx test/tiny_yolov2/test_data_set_0/input_0.pb |
wow, not even as far as before :D you could also try to produce a core dump by running will test this on my raspberry pi 1 (which has the same chipset as the zero). |
One simple thing this could be is a failing malloc without error handling. There are still quite few in the codebase and tiny yolo is not as tiny as the name suggests :D |
This was exactly was I was thinking when I read raspberry pi. Tiny yolo is quite big and computation intensive. But really nice that @iamfaith you are trying cONNXr in a RPI. Have you tried the other models we have? |
I hate this ui x.x |
One problem is, that the allocated memory of the tensors is not freed when they are not needed anymore. |
pi@raspberrypi:~/cONNXr-master $ build/connxr test/tiny_yolov2/Model.onnx test/tiny_yolov2/test_data_set_0/input_0.pb
Loading model test/tiny_yolov2/Model.onnx...ok!
Loading input test/tiny_yolov2/test_data_set_0/input_0.pb...ok!
values = 1
Resolving model...
Running inference on Example Model model...
Killed
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