FBGEMM
QConfig(activation=functools.partial(<class 'torch.ao.quantization.fake_quantize.FusedMovingAvgObsFakeQuantize'>, observer=<class 'torch.ao.quantization.observer.MovingAverageMinMaxObserver'>, quant_min=0, quant_max=255, reduce_range=True){'factory_kwargs': <function add_module_to_qconfig_obs_ctr.<locals>.get_factory_kwargs_based_on_module_device at 0x7f89352b3b90>}, weight=functools.partial(<class 'torch.ao.quantization.fake_quantize.FusedMovingAvgObsFakeQuantize'>, observer=<class 'torch.ao.quantization.observer.MovingAveragePerChannelMinMaxObserver'>, quant_min=-128, quant_max=127, dtype=torch.qint8, qscheme=torch.per_channel_symmetric){'factory_kwargs': <function add_module_to_qconfig_obs_ctr.<locals>.get_factory_kwargs_based_on_module_device at 0x7f89352b3b90>})
qnnpack
QConfig(activation=functools.partial(<class 'torch.ao.quantization.fake_quantize.FusedMovingAvgObsFakeQuantize'>, observer=<class 'torch.ao.quantization.observer.MovingAverageMinMaxObserver'>, quant_min=0, quant_max=255, reduce_range=False){'factory_kwargs': <function add_module_to_qconfig_obs_ctr.<locals>.get_factory_kwargs_based_on_module_device at 0x7f706669b9e0>}, weight=functools.partial(<class 'torch.ao.quantization.fake_quantize.FusedMovingAvgObsFakeQuantize'>, observer=<class 'torch.ao.quantization.observer.MovingAverageMinMaxObserver'>, quant_min=-128, quant_max=127, dtype=torch.qint8, qscheme=torch.per_tensor_symmetric){'factory_kwargs': <function add_module_to_qconfig_obs_ctr.<locals>.get_factory_kwargs_based_on_module_device at 0x7f706669b9e0>})
The default quantizer for fbgemm has reduce_range set to True. Why is it set only for the fbgemm backend?
Also, only fbgemm backend’s default qconfig has per channel quantization for weights. Why is this the case?
Thank you!