code: def _pre_execution(self, model, calib_dataloader=None, metric=None):
      if isinstance(model, torch.nn.Module):
          self.original_model = model
      return model, calib_dataloader, metric
  
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 2 for calling the PytorchQuantization obj's underlying member method code with example usage: obj._pre_execution(model, calib_dataloader, metric) and returns: model,  calib_dataloader,  metric