code: def _bilstm_harness(name, **kwargs):
      model = bilstm_classifier.TextClassifier(
          # TODO(marcvanzee): This fails when
          # `embedding_size != hidden_size`. I suppose some arrays are
          # concatenated with incompatible shapes, which could mean
          # something is going wrong in the translation.
          embedding_size=3,
          hidden_size=1,
          vocab_size=13,
          output_size=1,
          dropout_rate=0.0,
          word_dropout_rate=0.0,
      )
      x = np.array([[2, 4, 3], [2, 6, 3]], np.int32)
      lengths = np.array([2, 3], np.int32)
      variables = model.init(
          random.PRNGKey(0), x, lengths, deterministic=True
      )
      apply = functools.partial(model.apply, deterministic=True)
      return ModelHarness(
          name, apply, variables, [x, lengths], **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 3 for calling a global function with example usage: _bilstm_harness(name) and returns: ModelHarness