title: OpenVINO Convert TF Model to IR file Issue
body: <p>I'm trying to convert tensorflow model to OpenVINO IR files.
  I have downloaded a pre-trained model from the following address:</p>
  
  <blockquote>
    <p><a href="http://download.tensorflow.org/models/object_detection/mask_rcnn_inception_v2_coco_2018_01_28.tar.gz" rel="nofollow noreferrer">http://download.tensorflow.org/models/object_detection/mask_rcnn_inception_v2_coco_2018_01_28.tar.gz</a></p>
  </blockquote>
  
  <p>Then I extracted the file to get a .pb file named "frozen_inference_graph.pb"
  Then I used the conversion command in the OpenVINO folder </p>
  
  <blockquote>
    <p>"IntelSWTools\openvino_2019.2.275\deployment_tools\model_optimizer\"</p>
  </blockquote>
  
  <p>as following:</p>
  
  <pre><code>python mo_tf.py --input_model frozen_inference_graph.pb
  </code></pre>
  
  <p>but I got following error message.
  How can I modify anything to solve this issue?</p>
  
  <pre><code>Model Optimizer arguments:
  Common parameters:
      - Path to the Input Model:  &lt;my folder&gt;\frozen_inference_graph.pb
      - Path for generated IR:    &lt;my OpenVINO folder&gt;\IntelSWTools\openvino_2019.2.275\deployment_tools\model_optimizer\.
  - IR output name:   frozen_inference_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:    2019.2.0-436-gf5827d4
  
  C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python36_64\lib\site-packages\tensorflow\python\framework\dtypes.py:458: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
  
  [ ERROR ]  Shape [-1 -1 -1  3] is not fully defined for output 0 of "image_tensor". Use --input_shape with positive integers to override model input shapes.
  [ ERROR ]  Cannot infer shapes or values for node "image_tensor".
  [ ERROR ]  Not all output shapes were inferred or fully defined for node "image_tensor".  For more information please refer to Model Optimizer FAQ (https://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_Model_Optimizer_FAQ.html), question #40. 
  [ ERROR ]  
  [ ERROR ]  It can happen due to bug in custom shape infer function &lt;function Parameter.__init__.&lt;locals&gt;.&lt;lambda&gt; at 0x000002032A17D378&gt;.
  [ ERROR ]  Or because the node inputs have incorrect values/shapes.
  [ ERROR ]  Or because input shapes are incorrect (embedded to the model or passed via --input_shape).
  [ ERROR ]  Run Model Optimizer with --log_level=DEBUG for more information.
  [ ERROR ]  Exception occurred during running replacer "REPLACEMENT_ID" (&lt;class 'extensions.middle.PartialInfer.PartialInfer'&gt;): Stopped shape/value propagation at "image_tensor" node. 
  For more information please refer to Model Optimizer FAQ (https://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_Model_Optimizer_FAQ.html), question #38. 
  
  Process finished with exit code 1
  </code></pre>
  
  <p>I have tried many other tensorflow models but all have the same issue.
  I used different tensorflow version from <strong>1.2.0</strong> to <strong>1.14.0</strong> but the same.</p>
  
  <p>The key word about the shape seems to be the main cause. but how can I add something to avoid this issue?</p>
  
  <pre><code>Shape [-1 -1 -1  3] is not fully defined for output 0 of "image_tensor". Use --input_shape with positive integers to override model input shapes.
  </code></pre>
  
  <p>I hope the IR file can be generated correctly.</p>