code: def _batcher(lst):
      if F.is_tensor(lst[0]):
          return F.cat([F.unsqueeze(x, 0) for x in lst], dim=0)
  
      if isinstance(lst[0], np.ndarray):
          return F.tensor(np.array(lst))
  
      return F.tensor(lst)
  
imports: from collections import defaultdict
  from collections.abc import Mapping
  import networkx
  import numpy
  from scipy.sparse import spmatrix
  from .None import backend, graph_index, heterograph_index, utils
  from .base import DGLError, EID, ETYPE, NID, NTYPE
  from .heterograph import combine_frames, DGLBlock, DGLGraph
label_desc: Use image node_id 10 for calling a global function with example usage: _batcher(lst) and returns: F, F, F