SHAP: Сессия Tensorflow 2 пуста

Question

Я довольно новичок в питоне соотв. тензор поток 2.0 с керасом.

У меня есть обученная модель, и я хочу теперь интерпретировать ее с помощью SHAP. Но использование DeepExplainer не работает. Я получаю следующую ошибку

---------------------------------------------------------------------------

RuntimeError                              Traceback (most recent call last)

<ipython-input-19-38e59444e33c> in <module>
      2 
      3 data = x_train[:200]
----> 4 explainer = shap.DeepExplainer(model, data)
      5 

~/python/lib/python3.7/site-packages/shap/explainers/deep/__init__.py in __init__(self, model, data, session, learning_phase_flags)
     78 
     79         if framework == 'tensorflow':
---> 80             self.explainer = TFDeepExplainer(model, data, session, learning_phase_flags)
     81         elif framework == 'pytorch':
     82             self.explainer = PyTorchDeepExplainer(model, data)

~/python/lib/python3.7/site-packages/shap/explainers/deep/deep_tf.py in __init__(self, model, data, session, learning_phase_flags)
    139             if self.data[0].shape[0] > 5000:
    140                 warnings.warn("You have provided over 5k background samples! For better performance consider using smaller random sample.")
--> 141             self.expected_value = self.run(self.model_output, self.model_inputs, self.data).mean(0)
    142 
    143         # find all the operations in the graph between our inputs and outputs

~/python/lib/python3.7/site-packages/shap/explainers/deep/deep_tf.py in run(self, out, model_inputs, X)
    282         for t in self.learning_phase_flags:
    283             feed_dict[t] = False
--> 284         return self.session.run(out, feed_dict)
    285 
    286     def custom_grad(self, op, *grads):

~/python/lib/python3.7/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    948     try:
    949       result = self._run(None, fetches, feed_dict, options_ptr,
--> 950                          run_metadata_ptr)
    951       if run_metadata:
    952         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~/python/lib/python3.7/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1096       raise RuntimeError('Attempted to use a closed Session.')
   1097     if self.graph.version == 0:
-> 1098       raise RuntimeError('The Session graph is empty.  Add operations to the '
   1099                          'graph before calling run().')
   1100 

RuntimeError: The Session graph is empty.  Add operations to the graph before calling run().

Вот как выглядит моя модель:

model = keras.models.Sequential()


# Input size of VOCABULAR_SIZE with 50-neuron-layer
model.add(keras.layers.Dense(50, input_shape=(VOCABULAR_SIZE,), activation='relu'))

# Hidden layer
model.add(keras.layers.Dense(25, activation='relu'))

# Hidden layer in size of tags
# Sigmoid returns each output between 0 and 1

model.add(keras.layers.Dense(tags_count, activation='sigmoid'))
model.summary()

Я что-то пропустил? Не могли бы вы, ребята, помочь мне?