code: def _get_gnn_graphs():
      n_node = np.arange(3, 11)
      n_edge = np.arange(4, 12)
      total_n_node = np.sum(n_node)
      total_n_edge = np.sum(n_edge)
      n_graph = n_node.shape[0]
      feature_dim = 10
      graphs = jraph.GraphsTuple(
          n_node=n_node,
          n_edge=n_edge,
          senders=np.zeros(total_n_edge, dtype=np.int32),
          receivers=np.ones(total_n_edge, dtype=np.int32),
          nodes=np.ones((total_n_node, feature_dim)),
          edges=np.zeros((total_n_edge, feature_dim)),
          globals=np.zeros((n_graph, feature_dim)),
      )
      return graphs
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  import dataclasses
  import functools
  from typing import Any, Callable, Optional, Union
  import re
  import numpy
  import jraph
  from jax.experimental.jax2tf.tests.flax_models import actor_critic
  from jax.experimental.jax2tf.tests.flax_models import bilstm_classifier
  from jax.experimental.jax2tf.tests.flax_models import cnn
  from jax.experimental.jax2tf.tests.flax_models import gnn
  from jax.experimental.jax2tf.tests.flax_models import resnet
  from jax.experimental.jax2tf.tests.flax_models import seq2seq_lstm
  from jax.experimental.jax2tf.tests.flax_models import transformer_lm1b
  from jax.experimental.jax2tf.tests.flax_models import transformer_nlp_seq
  from jax.experimental.jax2tf.tests.flax_models import transformer_wmt
  from jax.experimental.jax2tf.tests.flax_models import vae
  import jax
  from jax import random
  import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: _get_gnn_graphs() and returns: graphs