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 typing import Sequence
  from absl import app
  from absl import flags
  from flax import linen
  from flax import optim
  import jax
  import jax.numpy
  import jraph
  from jraph.ogb_examples import data_utils
label_desc: Use image node_id 4 for calling a global function with example usage: pad_graph_to_nearest_power_of_two(graphs_tuple) and returns: jraph