class_docstr: Implementation of a Graph Network.
  
  See https://arxiv.org/abs/1806.01261 for more details.
docstr: Connects the GraphNetwork.
  
  Args:
    graph: A `graphs.GraphsTuple` containing `Tensor`s. Depending on the block
      options, `graph` may contain `None` fields; but with the default
      configuration, no `None` field is allowed. Moreover, when using the
      default configuration, the features of each nodes, edges and globals of
      `graph` should be concatenable on the last dimension.
    edge_model_kwargs: Optional keyword arguments to pass to
      the edge block model.
    node_model_kwargs: Optional keyword arguments to pass to
      the node block model.
    global_model_kwargs: Optional keyword arguments to pass to
      the global block model.
  
  Returns:
    An output `graphs.GraphsTuple` with updated edges, nodes and globals.
code: def _build(
      self,
      graph,
      edge_model_kwargs=None,
      node_model_kwargs=None,
      global_model_kwargs=None,
  ):
      """Connects the GraphNetwork.
  
      Args:
        graph: A `graphs.GraphsTuple` containing `Tensor`s. Depending on the block
          options, `graph` may contain `None` fields; but with the default
          configuration, no `None` field is allowed. Moreover, when using the
          default configuration, the features of each nodes, edges and globals of
          `graph` should be concatenable on the last dimension.
        edge_model_kwargs: Optional keyword arguments to pass to
          the edge block model.
        node_model_kwargs: Optional keyword arguments to pass to
          the node block model.
        global_model_kwargs: Optional keyword arguments to pass to
          the global block model.
  
      Returns:
        An output `graphs.GraphsTuple` with updated edges, nodes and globals.
      """
      node_input = self._edge_block(graph, edge_model_kwargs)
      global_input = self._node_block(node_input, node_model_kwargs)
      return self._global_block(global_input, global_model_kwargs)
  
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 GraphNetwork obj's underlying member method code with example usage: obj._build(graph, edge_model_kwargs, node_model_kwargs, global_model_kwargs) and returns: self