quantize
class torch.quantization.quantize(model, run_fn, run_args, mapping=None, inplace=False)
Quantize the input float model with post training static
   quantization.
First it will prepare the model for calibration, then it calls
   run_fn which will run the calibration step, after that we will
   convert the model to a quantized model.
Parameters:
      * model -- input float model
  * **run_fn** -- a calibration function for calibrating the
    prepared model

  * **run_args** -- positional arguments for *run_fn*

  * **inplace** -- carry out model transformations in-place, the
    original module is mutated

  * **mapping** -- correspondence between original module types
    and quantized counterparts

Returns:
      Quantized model.