ensor is returned as output of quantization, which wouldn’t be
possible in TorchScript. Additionally, it has to make sure a quantizer is re-initialized any time it is necessary.</p>
<p>For example, when performing <cite>ScalingImplType.PARAMETER_FROM_STATS</cite> scaling on a weight tensor,
statistics of the weight tensor are computed at dependency-injection time and used to initialize a
learned parameter. However, it’s not possible to know a-priori whether a pretrained floating-point state-dict
will be