code: def load_tensors(filename, return_dgl_ndarray=False):
      """
      load dict of tensors from file
  
      Parameters
      ----------
      filename : str
          File name to load dict of tensors.
      return_dgl_ndarray: bool
          Whether return dict of dgl NDArrays or backend tensors
  
      Returns
      ---------
      tensor_dict : dict
          dict of tensor or ndarray based on return_dgl_ndarray flag
      """
      nd_dict = _CAPI_LoadNDArrayDict(filename)
      tensor_dict = {}
      for key, value in nd_dict.items():
          if return_dgl_ndarray:
              tensor_dict[key] = value
          else:
              tensor_dict[key] = F.zerocopy_from_dgl_ndarray(value)
      return tensor_dict
  
imports: from __future__ import absolute_import
  from ..None import backend
  from .._ffi.function import _init_api
  from ..ndarray import NDArray
label_desc: Use image node_id 2 for calling a global function with example usage: load_tensors(filename, return_dgl_ndarray) and returns: tensor_dict