code: def _gnn_conv_harness(name, **kwargs):
      # Setting taken from flax/examples/ogbg_molpcba/models_test.py.
      rngs = {
          "params": random.PRNGKey(0),
          "dropout": random.PRNGKey(1),
      }
      graphs = _get_gnn_graphs()
      model = gnn.GraphConvNet(
          latent_size=5,
          num_mlp_layers=2,
          message_passing_steps=2,
          output_globals_size=5,
      )
      variables = model.init(rngs, graphs)
      return ModelHarness(
          name, model.apply, variables, [graphs], **kwargs
      )
  
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 7 for calling a global function with example usage: _gnn_conv_harness(name) and returns: ModelHarness