(self)
Avoid tensorflow errors for keras models by clearing the session and reloading from disk
        https://github.com/tensorflow/tensorflow/issues/14356
        https://stackoverflow.com/questions/40785224/tensorflow-cannot-interpret-feed-dict-key-as-tensor
Avoid tensorflow errors for keras models by clearing the session and reloading from disk
        https://github.com/tensorflow/tensorflow/issues/14356
        https://stackoverflow.com/questions/40785224/tensorflow-cannot-interpret-feed-dict-key-as-tensor
Avoid tensorflow errors for keras models by clearing the session and reloading from disk https : // github . com / tensorflow / tensorflow / issues / 14356 https : // stackoverflow . com / questions / 40785224 / tensorflow - cannot - interpret - feed - dict - key - as - tensor
def _keras_refresh(self):
        """
        Avoid tensorflow errors for keras models by clearing the session and reloading from disk
        https://github.com/tensorflow/tensorflow/issues/14356
        https://stackoverflow.com/questions/40785224/tensorflow-cannot-interpret-feed-dict-key-as-tensor
        """
        kerasbackend.clear_session()

        # Load the keras model architecture and weights from disk
        keras_model = keras.models.load_model(self.path + self.model.name + '.h5')
        keras_model._make_predict_function()
        # Point the model's estimator in the sklearn pipeline to the keras model architecture and weights 
        self.model.pipe.named_steps['estimator'].model = keras_model
def _keras_refresh ( self ) : kerasbackend . clear_session ( ) # Load the keras model architecture and weights from disk keras_model = keras . models . load_model ( self . path + self . model . name + '.h5' ) keras_model . _make_predict_function ( ) # Point the model's estimator in the sklearn pipeline to the keras model architecture and weights  self . model . pipe . named_steps [ 'estimator' ] . model = keras_model