code: def _get_external_data_paths(
      src_paths: List[Path], dst_paths: List[Path]
  ) -> Tuple[List[Path], List[str]]:
      """
      Gets external data paths from the model and add them to the list of files to copy.
      """
      model_paths = src_paths.copy()
      for idx, model_path in enumerate(model_paths):
          model = onnx.load(str(model_path), load_external_data=False)
          model_tensors = _get_initializer_tensors(model)
          # filter out tensors that are not external data
          model_tensors_ext = [
              ExternalDataInfo(tensor).location
              for tensor in model_tensors
              if tensor.HasField("data_location")
              and tensor.data_location == onnx.TensorProto.EXTERNAL
          ]
          if len(set(model_tensors_ext)) == 1:
              # if external data was saved in a single file
              src_paths.append(model_path.parent / model_tensors_ext[0])
              dst_paths.append(
                  dst_paths[idx].parent / model_tensors_ext[0]
              )
          else:
              # if external data doesnt exist or was saved in multiple files
              src_paths.extend(
                  [
                      model_path.parent / tensor_name
                      for tensor_name in model_tensors_ext
                  ]
              )
              dst_paths.extend(
                  dst_paths[idx].parent / tensor_name
                  for tensor_name in model_tensors_ext
              )
      return src_paths, dst_paths
  
file_path: optimum/optimum/onnx/utils.py
imports: from pathlib import Path
  from typing import List, Tuple, Union
  import onnx
  from onnx.external_data_helper import ExternalDataInfo, _get_initializer_tensors
label_desc: Use image node_id 2 for calling a global function with example usage: _get_external_data_paths(src_paths, dst_paths) and returns: src_paths,  dst_paths