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Hi @Andrey Ignatov, In quantization case, we base on the same ckpt to generate the "model.tflite" and "model_none.tflite". But we use the "noise data" and "mediatek_raw" as representative_dataset for "model.tflite" and "model_none.tflite", respectively. Is such a result acceptable? thanks

So, the output range of FP model must be 0~255 and the data type could be float32 ?? Which one is your requirement ? 1. tensor * 255.0 2. floor( tensor*255.0 + 0.5)

Thanks for your answer, I want to clarify my question 1).Does the submitted tflite should be produce the INT8 value for fidelity scores computeing? 2).The round processing( [0~1]=>[0~255] ) will also be included in the runtime measurement.

Will the organizer provide the test scripts or reference code for RGB img. producing? We want to make sure that the output results are consistent.

Thanks. @Andrey Ignatov About the message shows that: "with an output tensor of size [1, 1088, 1920, 3] producing the final reconstructed RGB images. ......... no additional scripts are accepted." Are there any constraint for range of the model output? Now my output range is the 0~1, i need...

Hi @Andrey Ignatov The same questions for me. What's the structure of our submission for uploading at testing phase?

Hi @Andrey Ignatov Regarding the above discussion. If we summit the image base on fp tflite for evaluating the quality, but generate the quantized tflite for latency measurement. Is such a result acceptable?