code: def _pre_execution(self, model, calib_dataset=None, metric=None):
      if calib_dataset:
          x, y = calib_dataset
          calib_dataset = KerasNumpyDataset(x, y, model.dtype)
  
      if isinstance(model, KerasONNXRuntimeModel):
          model = model.onnx_model
  
      return model, calib_dataset, metric
  
file_path: BigDL/python/nano/src/bigdl/nano/deps/neural_compressor/onnx/tensorflow/quantization.py
imports: import numpy
  import tensorflow
  from bigdl.nano.utils.tf import tensors_to_numpy
  from bigdl.nano.deps.onnxruntime.tensorflow.model import KerasONNXRuntimeModel
  from ..quantization import BaseONNXRuntimeQuantization
  from .metric import KerasONNXRuntimeINCMetic
label_desc: Use image node_id 2 for calling the KerasONNXRuntimeQuantization obj's underlying member method code with example usage: obj._pre_execution(model, calib_dataset, metric) and returns: model,  calib_dataset,  metric