quantize_dynamic
class torch.quantization.quantize_dynamic(model, qconfig_spec=None, dtype=torch.qint8, mapping=None, inplace=False)
Converts a float model to dynamic (i.e. weights-only) quantized
   model.
Replaces specified modules with dynamic weight-only quantized
   versions and output the quantized model.
For simplest usage provide dtype argument that can be float16 or
   qint8. Weight-only quantization by default is performed for layers
   with large weights size - i.e. Linear and RNN variants.
Fine grained control is possible with qconfig and mapping that
   act similarly to quantize(). If qconfig is provided, the
   dtype argument is ignored.
Parameters:
      * model -- input model
  * **qconfig_spec** --

    Either:

    * A dictionary that maps from name or type of submodule to
      quantization configuration, qconfig applies to all
      submodules of a given module unless qconfig for the
