code: def _to_compatible_data_dicts(data_dicts):
      """Converts the content of `data_dicts` to arrays of the right type.
  
      All fields are converted to numpy arrays. The index fields (`SENDERS` and
      `RECEIVERS`) and number fields (`N_NODE`, `N_EDGE`) are cast to `np.int32`.
  
      Args:
        data_dicts: An iterable of dictionaries with keys `ALL_KEYS` and values
          either `None`s, or quantities that can be converted to numpy arrays.
  
      Returns:
        A list of dictionaries containing numpy arrays or `None`s.
      """
      results = []
      for data_dict in data_dicts:
          result = {}
          for k, v in data_dict.items():
              if v is None:
                  result[k] = None
              else:
                  dtype = (
                      np.int32
                      if k in [SENDERS, RECEIVERS, N_NODE, N_EDGE]
                      else None
                  )
                  result[k] = np.asarray(v, dtype)
          results.append(result)
      return results
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from graph_nets import graphs
  import networkx
  import numpy
  from six.moves import range
  from six.moves import zip
label_desc: Use image node_id 13 for calling a global function with example usage: _to_compatible_data_dicts(data_dicts) and returns: results