looks like it depends on the qconfig i.e. backend you are working on:
  
      github.com
  
  
    pytorch/pytorch/blob/master/torch/quantization/qconfig.py#L96-L105

def get_default_qconfig(backend='fbgemm'):
    if backend == 'fbgemm':
        qconfig = QConfig(activation=HistogramObserver.with_args(reduce_range=True),
                          weight=default_per_channel_weight_observer)
    elif backend == 'qnnpack':
        qconfig = QConfig(activation=HistogramObserver.with_args(reduce_range=False),
                          weight=default_weight_observer)
    else:
        qconfig = default_qconfig
    return qconfig



  
  
    
    
  
  


in this case its not a MinMax observer, but reduce_range is set to true