Problem converting Tenserflow model to CoreML

## 🐞Describing the bug
- Make sure to only create an issue here for bugs in the coremltools Python package. If this is a bug with the Core ML Framework or Xcode, please submit your bug here: https://developer.apple.com/bug-reporting/
- Provide a clear and consise description of the bug.

When trying to convert @yoeo's Guesslang model, I received a `ValueError: Failed to import metagraph, check error log for more info.`
## Stack Trace
- If applicable, please paste the complete stack trace.
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
in ()
10 model = tf.saved_model.load("./savedmodel")
11 mfunc = model.signatures['serving_default']
---> 12 ctmodel = ct.convert([mfunc], "tensorflow")
13 ctmodel.save("ctmodel")

12 frames
/usr/local/lib/python3.10/dist-packages/coremltools/converters/_converters_entry.py in convert(model, source, inputs, outputs, classifier_config, minimum_deployment_target, convert_to, compute_precision, skip_model_load, compute_units, package_dir, debug, pass_pipeline)
490 specification_version = _set_default_specification_version(exact_target)
491
--> 492 mlmodel = mil_convert(
493 model,
494 convert_from=exact_source,

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/converter.py in mil_convert(model, convert_from, convert_to, compute_units, **kwargs)
186 See `coremltools.converters.convert`
187 """
--> 188 return _mil_convert(model, convert_from, convert_to, ConverterRegistry, MLModel, compute_units, **kwargs)
189
190

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/converter.py in _mil_convert(model, convert_from, convert_to, registry, modelClass, compute_units, **kwargs)
210 kwargs["weights_dir"] = weights_dir.name
211
--> 212 proto, mil_program = mil_convert_to_proto(
213 model,
214 convert_from,

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/converter.py in mil_convert_to_proto(model, convert_from, convert_to, converter_registry, main_pipeline, **kwargs)
283
284 frontend_converter = frontend_converter_type()
--> 285 prog = frontend_converter(model, **kwargs)
286 PipelineManager.apply_pipeline(prog, frontend_pipeline)
287

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/converter.py in __call__(self, *args, **kwargs)
96
97 tf2_loader = TF2Loader(*args, **kwargs)
---> 98 return tf2_loader.load()
99
100

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/frontend/tensorflow/load.py in load(self)
59 outputs = self.kwargs.get("outputs", None)
60 output_names = get_output_names(outputs)
---> 61 self._graph_def = self._graph_def_from_model(output_names)
62
63 if self._graph_def is not None and len(self._graph_def.node) == 0:

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/frontend/tensorflow2/load.py in _graph_def_from_model(self, output_names)
131 def _graph_def_from_model(self, output_names=None):
132 """Overwrites TFLoader._graph_def_from_model()"""
--> 133 cfs, graph_def = self._get_concrete_functions_and_graph_def()
134 if isinstance(self.model, _tf.keras.Model) and self.kwargs.get("outputs", None) is None:
135 # For the keras model, check if the outputs is provided by the user.

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/frontend/tensorflow2/load.py in _get_concrete_functions_and_graph_def(self)
125 raise NotImplementedError(msg.format(self.model))
126
--> 127 graph_def = self._graph_def_from_concrete_fn(cfs)
128
129 return cfs, graph_def

/usr/local/lib/python3.10/dist-packages/coremltools/converters/mil/frontend/tensorflow2/load.py in _graph_def_from_concrete_fn(self, cfs)
326
327 if _get_version(_tf.__version__) >= _StrictVersion("2.2.0"):
--> 328 frozen_fn = _convert_variables_to_constants_v2(cfs[0], lower_control_flow=False, aggressive_inlining=True)
329 else:
330 frozen_fn = _convert_variables_to_constants_v2(cfs[0], lower_control_flow=False)

/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/convert_to_constants.py in convert_variables_to_constants_v2(func, lower_control_flow, aggressive_inlining)
1168 """
1169
-> 1170 converter_data = _FunctionConverterDataInEager(
1171 func=func,
1172 lower_control_flow=lower_control_flow,

/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/convert_to_constants.py in __init__(self, func, lower_control_flow, aggressive_inlining, variable_names_allowlist, variable_names_denylist)
831 self._func = func
832 # Inline the graph in order to remove functions when possible.
--> 833 graph_def = _run_inline_graph_optimization(func, lower_control_flow,
834 aggressive_inlining)
835 super(_FunctionConverterData, self).__init__(

/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/convert_to_constants.py in _run_inline_graph_optimization(func, lower_control_flow, aggressive_inlining)
1066 rewrite_options.function_optimization =\
1067 rewriter_config_pb2.RewriterConfig.AGGRESSIVE
-> 1068 return tf_optimizer.OptimizeGraph(config, meta_graph)
1069
1070

/usr/local/lib/python3.10/dist-packages/tensorflow/python/grappler/tf_optimizer.py in OptimizeGraph(config_proto, metagraph, verbose, graph_id, cluster, strip_default_attributes)
63 cluster = gcluster.Cluster()
64 try:
---> 65 out_graph = tf_opt.TF_OptimizeGraph(cluster.tf_cluster,
66 config_proto.SerializeToString(),
67 metagraph.SerializeToString(),

ValueError: Failed to import metagraph, check error log for more info.
```
## To Reproduce
- Please add a minimal code example that can reproduce the error when running it.
```
# Paste Python code snippet here, complete with any required import statements.
import tensorflow as tf
import coremltools as ct

model = tf.saved_model.load("./savedmodel")
mfunc = model.signatures['serving_default']
ctmodel = ct.convert([mfunc], "tensorflow")
ctmodel.save("ctmodel")
```

- If the model conversion succeeds, but there is a numerical mismatch in predictions, please include the code used for comparisons.

## System environment (please complete the following information):
- coremltools version: 6.3.0
- OS (e.g. MacOS version or Linux type): macOS Ventura (also tested on Google Colab (Debian Linux))
- Any other relevant version information (e.g. PyTorch or TensorFlow version): 2.12.0

## Additional context
As per #1794, which concerned the same model, I tried converting only a single concrete function.

Start with the TensorFlow 2 loader at converters/mil/frontend/tensorflow2/load.py and the convert_to_constants.py frame shown in the traceback. Reproduce the supplied saved-model and single-concrete-function conversions using coremltools 6.3.0 and TensorFlow 2.12.0; done means the Guesslang conversion no longer fails with the metagraph ValueError.

Written by the indexing model from the issue text.