title: Keras 'InputLayer object has no attribute 'inbound_nodes' when converting to CoreML
body: <p>I get the error 'InputLayer object has no attribute 'inbound_nodes' when trying to convert my Keras model to CoreML model. </p>
  
  <p>Here is my code: </p>
  
  <pre><code>     loaded_model = load_model("diffinception.h5")
       coreml_model = coremltools.converters.keras.convert(loaded_model, 
           input_names="imageSculp", output_names="category")
       coreml_model.save("transfertestinception.mlmodel")
  </code></pre>
  
  <p>The "diffinception.h5" is an Inception model imported from Keras with additional layers that I trained for transfer learning. </p>
  
  <p>Here is my code for generating that model:</p>
  
  <pre><code>    model = applications.InceptionV3(weights = "imagenet", include_top=False,         
      input_shape = (img_width, img_height, 3), pooling = max)
  
      # Freeze layers
      for layer in model.layers:
          layer.trainable = False
  
      #Adding custom Layers
      x = model.output
      x = Flatten()(x)
      x = Dense(1024, activation="relu")(x)
      x = Dropout(0.5)(x)
      x = Dense(1024, activation="relu")(x)
      predictions = Dense(2, activation="softmax")(x)
  
      # creating the final model
      model_final = Model(inputs = model.input, outputs = predictions)
      # compile the model
      model_final.compile(loss = "categorical_crossentropy", optimizer =                                         
          optimizers.SGD(lr=0.001, momentum=0.9), metrics=["accuracy"])
  </code></pre>
  
  <p>I am up to date with the version of Keras. Using Python 2.7</p>