I wasn’t able to get good results from QNNPACK compatible per tensor quantization qconfig. Target metric value relative to fp32 model:
get_default_qconfig('fbgemm') -> 99.8%
get_default_qconfig('qnnpack') -> 58.5%
default_qconfig -> 54.4%
Is there any way to reduce that gap without changing architecture?