prepare
class torch.quantization.prepare(model, inplace=False, allow_list=None, observer_non_leaf_module_list=None, prepare_custom_config_dict=None)
Prepares a copy of the model for quantization calibration or
   quantization-aware training.
Quantization configuration should be assigned preemptively to
   individual submodules in .qconfig attribute.
The model will be attached with observer or fake quant modules, and
   qconfig will be propagated.
Parameters:
      * model -- input model to be modified in-place
  * **inplace** -- carry out model transformations in-place, the
    original module is mutated

  * **allow_list** -- list of quantizable modules

  * **observer_non_leaf_module_list** -- list of non-leaf modules
    we want to add observer

  * **prepare_custom_config_dict** -- customization configuration
    dictionary for prepare function

  # Example of prepare_custom_config_dict:
  prepare_custom_config_dict = {
