code: def _post_execution(self, q_model):
      quantized_model = PytorchQuantizedModel(q_model, self.thread_num)
      if hasattr(self, "original_model"):
          # patch original model's attr to current new model
          patch_attrs_from_model_to_object(
              self.original_model, quantized_model
          )
          del self.original_model
      return quantized_model
  
file_path: BigDL/python/nano/src/bigdl/nano/deps/neural_compressor/pytorch/quantization.py
imports: from typing import Callable
  from collections.abc import Iterable
  from bigdl.nano.utils.common import invalidInputError
  from ..core import BaseQuantization
  from .utils import _check_loader
  from .metric import PytorchINCMetric
  from .quantized_model import PytorchQuantizedModel
  from torchmetrics import Metric
  import torch
  from bigdl.nano.utils.pytorch import patch_attrs_from_model_to_object
label_desc: Use image node_id 3 for calling the PytorchQuantization obj's underlying member method code with example usage: obj._post_execution(q_model) and returns: quantized_model