class_docstr: Compatibility tests that use TF.
  
  Uses tf.Graph to serialize and run the functions; expects that `func`
  contains a `jax2tf.call_tf` and uses `jax2tf.convert` to generate a
  `tf.Graph` containing a XlaCallModule with the actual MLIR module.
class_docstr_tok: ["Compatibility","tests","that","use","TF",".","Uses","tf.Graph","to","serialize","and","run","the","functions",";","expects","that","`","func","`","contains","a","`","jax2tf.call_tf","`","and","uses","`","jax2tf.convert","`","to","generate","a","`","tf.Graph","`","containing","a","XlaCallModule","with","the","actual","MLIR","module","."]
code: def run_current(self, func: Callable, data: bctu.CompatTestData):
      # Here we use tf.saved_model and provide  string serialize/deserialize methods
      # for the whole directory.
      @tf.function(autograph=False, jit_compile=True)
      def tf_func(
          the_input,
      ):  # Use recognizable names for input and result
          res = jax2tf.convert(func, native_serialization=True)(
              the_input
          )
          return tf.identity(res, name="the_result")
  
      self.tf_func = tf_func
      return tf_func(*data.inputs)
  
imports: from __future__ import annotations
  import base64
  from collections.abc import Sequence
  import io
  import os
  import tarfile
  from typing import Callable, Optional
  from absl.testing import absltest
  from jax import config
  from jax._src import test_util
  from jax._src.internal_test_util import export_back_compat_test_util
  from jax._src.lib import xla_extension
  from jax.experimental import jax2tf
  from jax.experimental.jax2tf.tests.back_compat_testdata import tf_call_tf_function
  import jax.numpy
  import tensorflow
label_desc: Use image node_id 1 for calling the CompatTensoflowTest obj's underlying member method code with example usage: obj.run_current(func, data) and returns: tf_func, tf