OpenVino Model Optimizer Error when converting TensorFlow model

I have created a custom image classification .pb model file using the python scripts in the TensorFlow for Poets 2 repo (https://github.com/googlecodelabs/tensorflow-for-poets-2).

I tried converting it to Intermediate Representation using the OpenVino Model Optimizer using the below scripts:

python mo_tf.py --input_model retrained_graph.pb

python mo_tf.py --input_model retrained_graph.pb --mean_values [127.5,127.5,127.5] --input Mul

In both cases this is what happened:

Model Optimizer arguments:
Common parameters:
        - Path to the Input Model:      C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\retrained_graph.pb
        - Path for generated IR:        C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\.
        - IR output name:       retrained_graph
        - Log level:    ERROR
        - Batch:        Not specified, inherited from the model
        - Input layers:         Not specified, inherited from the model
        - Output layers:        Not specified, inherited from the model
        - Input shapes:         Not specified, inherited from the model
        - Mean values:  Not specified
        - Scale values:         Not specified
        - Scale factor:         Not specified
        - Precision of IR:      FP32
        - Enable fusing:        True
        - Enable grouped convolutions fusing:   True
        - Move mean values to preprocess section:       False
        - Reverse input channels:       False
TensorFlow specific parameters:
        - Input model in text protobuf format:  False
        - Path to model dump for TensorBoard:   None
        - List of shared libraries with TensorFlow custom layers implementation:        None
        - Update the configuration file with input/output node names:   None
        - Use configuration file used to generate the model with Object Detection API:  None
        - Operations to offload:        None
        - Patterns to offload:  None
        - Use the config file:  None
Model Optimizer version:        2019.3.0-408-gac8584cb7
[ ERROR ]  -------------------------------------------------
[ ERROR ]  ----------------- INTERNAL ERROR ----------------
[ ERROR ]  Unexpected exception happened.
[ ERROR ]  Please contact Model Optimizer developers and forward the following information:
[ ERROR ]  local variable 'new_attrs' referenced before assignment
[ ERROR ]  Traceback (most recent call last):
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\front\extractor.py", line 608, in extract_node_attrs
    supported, new_attrs = extractor(Node(graph, node))
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\pipeline\tf.py", line 132, in <lambda>
    extract_node_attrs(graph, lambda node: tf_op_extractor(node, check_for_duplicates(tf_op_extractors)))
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\front\tf\extractor.py", line 109, in tf_op_extractor
    attrs = tf_op_extractors[op](node)
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\front\tf\extractor.py", line 65, in <lambda>
    return lambda node: pb_extractor(node.pb)
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\front\tf\extractors\const.py", line 31, in tf_const_ext
    result['value'] = tf_tensor_content(pb_tensor.dtype, result['shape'], pb_tensor)
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\front\tf\extractors\utils.py", line 76, in tf_tensor_content
    dtype=type_helper[0]),
UnicodeDecodeError: 'ascii' codec can't decode byte 0xff in position 0: ordinal not in range(128)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\main.py", line 298, in main
    return driver(argv)
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\main.py", line 247, in driver
    is_binary=not argv.input_model_is_text)
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\pipeline\tf.py", line 132, in tf2nx
    extract_node_attrs(graph, lambda node: tf_op_extractor(node, check_for_duplicates(tf_op_extractors)))
  File "C:\Program Files (x86)\IntelSWTools\openvino_2019.3.379\deployment_tools\model_optimizer\mo\front\extractor.py", line 614, in extract_node_attrs
    new_attrs['name'] if 'name' in new_attrs else '<UNKNOWN>',
UnboundLocalError: local variable 'new_attrs' referenced before assignment

[ ERROR ]  ---------------- END OF BUG REPORT --------------
[ ERROR ]  ------------------------------------------------- 

Does anyone know how to fix it?

Eventually I found a solution that worked for me.

I checked the OpenVino Toolkit documentation and found this (02/03/2020)

Under 'Supported Topologies' there is a list with the topologies that work with the OpenVino model optimizer. When you create a model using TensorFlow for Poets 2, you need make sure you choose an architecture that is supported by the model optimizer.