class_docstr: Implementation of a Relation Network.
  
  See https://arxiv.org/abs/1706.01427 for more details.
  
  The global and edges features of the input graph are not used, and are
  allowed to be `None` (the receivers and senders properties must be present).
  The output graph has updated, non-`None`, globals.
docstr: Connects the RelationNetwork.
  
  Args:
    graph: A `graphs.GraphsTuple` containing `Tensor`s, except for the edges
      and global properties which may be `None`.
    edge_model_kwargs: Optional keyword arguments to pass to
      the edge block model.
    global_model_kwargs: Optional keyword arguments to pass to
      the global block model.
  
  Returns:
    A `graphs.GraphsTuple` with updated globals.
  
  Raises:
    ValueError: If any of `graph.nodes`, `graph.receivers` or `graph.senders`
      is `None`.
code: def _build(
      self, graph, edge_model_kwargs=None, global_model_kwargs=None
  ):
      """Connects the RelationNetwork.
  
      Args:
        graph: A `graphs.GraphsTuple` containing `Tensor`s, except for the edges
          and global properties which may be `None`.
        edge_model_kwargs: Optional keyword arguments to pass to
          the edge block model.
        global_model_kwargs: Optional keyword arguments to pass to
          the global block model.
  
      Returns:
        A `graphs.GraphsTuple` with updated globals.
  
      Raises:
        ValueError: If any of `graph.nodes`, `graph.receivers` or `graph.senders`
          is `None`.
      """
      output_graph = self._global_block(
          self._edge_block(graph, edge_model_kwargs),
          global_model_kwargs,
      )
      return graph.replace(globals=output_graph.globals)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from graph_nets import _base
  from graph_nets import blocks
  import tensorflow
label_desc: Use image node_id 2 for calling the RelationNetwork obj's underlying member method code with example usage: obj._build(graph, edge_model_kwargs, global_model_kwargs) and returns: graph