

data -- input data used to run the prepared q_model

logger_cls -- type of logger to be used in shadow module
    to process the outputs of quantized module and its float
    shadow module



Return type:
      Dict[str, Dict]
torch.ao.ns._numeric_suite.get_matching_activations(float_module, q_module)
Find the matching activation between float and quantized modules.
Parameters:
      * float_module (Module) -- float module used to generate
        the q_module
  * **q_module** (*Module*) -- module quantized from float_module

Returns:
      dict with key corresponding to quantized module names and each
      entry being a dictionary with two keys 'float' and 'quantized',
      containing the matching float and quantized activations
Return type:
      act_dict
torch.ao.ns._numeric_suite.prepare_model_outputs(float_module, q_module, logger_cls=, allow_list=None)