code: def pad_graph_to_nearest_power_of_two(
      graphs_tuple: jraph.GraphsTuple,
  ) -> jraph.GraphsTuple:
      """Pads a batched `GraphsTuple` to the nearest power of two.
  
      For example, if a `GraphsTuple` has 7 nodes, 5 edges and 3 graphs, this method
      would pad the `GraphsTuple` nodes and edges:
        7 nodes --> 8 nodes (2^3)
        5 edges --> 8 edges (2^3)
  
      And since padding is accomplished using `jraph.pad_with_graphs`, an extra
      graph and node is added:
        8 nodes --> 9 nodes
        3 graphs --> 4 graphs
  
      Args:
        graphs_tuple: a batched `GraphsTuple` (can be batch size 1).
  
      Returns:
        A graphs_tuple batched to the nearest power of two.
      """
      # Add 1 since we need at least one padding node for pad_with_graphs.
      pad_nodes_to = (
          _nearest_bigger_power_of_two(jnp.sum(graphs_tuple.n_node)) + 1
      )
      pad_edges_to = _nearest_bigger_power_of_two(
          jnp.sum(graphs_tuple.n_edge)
      )
      # Add 1 since we need at least one padding graph for pad_with_graphs.
      # We do not pad to nearest power of two because the batch size is fixed.
      pad_graphs_to = graphs_tuple.n_node.shape[0] + 1
      return jraph.pad_with_graphs(
          graphs_tuple, pad_nodes_to, pad_edges_to, pad_graphs_to
      )
  
imports: import functools
  import logging
  import pathlib
  import pickle
  from absl import app
  from absl import flags
  import haiku
  import jax
  import jax.numpy
  import jraph
  from jraph.ogb_examples import data_utils
  import optax
label_desc: Use image node_id 6 for calling a global function with example usage: pad_graph_to_nearest_power_of_two(graphs_tuple) and returns: jraph