code: def data_dicts_to_graphs_tuple(data_dicts):
      """Constructs a `graphs.GraphsTuple` from an iterable of data dicts.
  
      The graphs represented by the `data_dicts` argument are batched to form a
      single instance of `graphs.GraphsTuple` containing numpy arrays.
  
      Args:
        data_dicts: An iterable of dictionaries with keys `GRAPH_DATA_FIELDS`, plus,
          potentially, a subset of `GRAPH_NUMBER_FIELDS`. The NODES and EDGES fields
          should be numpy arrays of rank at least 2, while the RECEIVERS, SENDERS
          are numpy arrays of rank 1 and same dimension as the EDGES field first
          dimension. The GLOBALS field is a numpy array of rank at least 1.
  
      Returns:
        An instance of `graphs.GraphsTuple` containing numpy arrays. The
        `RECEIVERS`, `SENDERS`, `N_NODE` and `N_EDGE` fields are cast to `np.int32`
        type.
      """
      data_dicts = [dict(d) for d in data_dicts]
      for key in graphs.GRAPH_DATA_FIELDS:
          for data_dict in data_dicts:
              data_dict.setdefault(key, None)
      _check_valid_sets_of_keys(data_dicts)
      data_dicts = _to_compatible_data_dicts(data_dicts)
      return graphs.GraphsTuple(**_concatenate_data_dicts(data_dicts))
  
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 11 for calling a global function with example usage: data_dicts_to_graphs_tuple(data_dicts) and returns: graphs