code: def _post_execution(self, q_model):
      if hasattr(self, "nano_model") and isinstance(
          self.nano_model, PytorchONNXRuntimeModel
      ):
          self.nano_model.__init__(
              q_model.model,
              onnxruntime_session_options=self.session_options,
          )
          return self.nano_model
      else:
          # below code will re-define a new object, and original attrs will be lost.
          return PytorchONNXRuntimeModel(
              q_model.model,
              onnxruntime_session_options=self.session_options,
          )
  
file_path: BigDL/python/nano/src/bigdl/nano/deps/neural_compressor/onnx/pytorch/quantization.py
imports: from copy import deepcopy
  from bigdl.nano.deps.onnxruntime.pytorch.pytorch_onnxruntime_model import PytorchONNXRuntimeModel
  from ..quantization import BaseONNXRuntimeQuantization
  from ...pytorch import PytorchQuantization
  from .metric import PytorchONNXRuntimeINCMetic
  import torch
label_desc: Use image node_id 3 for calling the PytorchONNXRuntimeQuantization obj's underlying member method code with example usage: obj._post_execution(q_model) and returns: self, PytorchONNXRuntimeModel