QConfig
class torch.quantization.qconfig.QConfig(activation, weight)
Describes how to quantize a layer or a part of the network by
   providing settings (observer classes) for activations and weights
   respectively.
Note that QConfig needs to contain observer classes (like
   MinMaxObserver) or a callable that returns instances on invocation,
   not the concrete observer instances themselves. Quantization
   preparation function will instantiate observers multiple times for
   each of the layers.
Observer classes have usually reasonable default arguments, but
   they can be overwritten with with_args method (that behaves like
   functools.partial):
  my_qconfig = QConfig(
      activation=MinMaxObserver.with_args(dtype=torch.qint8),
      weight=default_observer.with_args(dtype=torch.qint8))
