code: def broadcast_receiver_nodes_to_edges(
      graph, name="broadcast_receiver_nodes_to_edges"
  ):
      """Broadcasts the node features to the edges they are receiving from.
  
      Args:
        graph: A `graphs.GraphsTuple` containing `Tensor`s, with nodes features of
          shape `[n_nodes] + node_shape`, and receivers of shape `[n_edges]`.
        name: (string, optional) A name for the operation.
  
      Returns:
        A tensor of shape `[n_edges] + node_shape`, where
        `n_edges = sum(graph.n_edge)`. The i-th element is given by
        `graph.nodes[graph.receivers[i]]`.
  
      Raises:
        ValueError: If either `graph.nodes` or `graph.receivers` is `None`.
      """
      _validate_broadcasted_graph(graph, NODES, RECEIVERS)
      with tf.name_scope(name):
          return tf.gather(graph.nodes, graph.receivers)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from graph_nets import _base
  from graph_nets import graphs
  from graph_nets import utils_tf
  import tensorflow
label_desc: Use image node_id 8 for calling a global function with example usage: broadcast_receiver_nodes_to_edges(graph, name) and returns: tf