self.graph = tf.get_default_graph()

with self.graph.as_default():

    self.model = Sequential()
    self.model.add(Conv2D(32, (2, 2), input_shape=(self.num_sample, 26, 1), padding='same', activation='relu'))
    self.model.add(Conv2D(32, (2, 2), padding='same', activation='relu'))
    self.model.add(MaxPool2D(pool_size=(2, 2)))

    self.model.add(Conv2D(32, (2, 2), padding = 'same', activation='relu'))
    self.model.add(Conv2D(32, (2, 2), padding = 'same', activation='relu'))
    self.model.add(Flatten())
    self.model.add(Dense(1024, activation='relu'))
    # TODO(raise ValueError: Tensor("dense_2/Softmax:0", shape=(?, 5), dtype=float32) is not an element of this graph.)
    self.model.add(Dense(len(self.EMOTIONS), activation='softmax'))

    # 모델 학습과정
    self.model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])