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export.py - TensorFlow Lite export failure due to EndVector() #10202
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@HripsimeS 👋 Hello! Thanks for asking about YOLOv5 🚀 benchmarks. YOLOv5 inference is officially supported in 11 formats, and all formats are benchmarked for identical accuracy and to compare speed every 24 hours by the YOLOv5 CI. Due to these daily benchmarks we can tell that TFLite export is operating correctly and there are no errors there. 💡 ProTip: Export to ONNX or OpenVINO for up to 3x CPU speedup. See CPU Benchmarks.
BenchmarksBenchmarks below run on a Colab Pro with the YOLOv5 tutorial notebook . To reproduce: python utils/benchmarks.py --weights yolov5s.pt --imgsz 640 --device 0 Colab Pro V100 GPU
Colab Pro CPU
Good luck 🍀 and let us know if you have any other questions! |
@glenn-jocher thanks for your quick reply, I could fix it with this command line, I will close this issue! |
Oh that's strange. We used to install a fixed version of flatbuffers like this but it caused problems with newer versions of TF I think. |
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@glenn-jocher Hello. I need to convert yolov5s.pt weight to yolov5s.tflite and save tflite in some folder. I saw that export.py is normally doing that action, but I did not receive the outcome model as tflite format. I run this command:
python export.py --weights yolov5s.pt --include tflite
In weights folder it saved best_saved_model folder with
Tha last line after running the command above are these
TensorFlow Lite: export failure 58.0s: EndVector() takes 1 positional argument but 2 were given
So the export was failed due to EndVector(), which I could not find in export.py file. Could you please help me to figure out what is the issue and how to fix it in order to get an outcome yolov5s.tflite file. Look forward to hearing soon!
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