def define_multiclass_nn(self, n_neurons, m, class_num):
    classifier = Sequential()
    layer0 = Dense(n_neurons, input_dim=m, activation='relu')
    classifier.add(layer0)
    layer1 = Dense(class_num, activation='softmax')
    classifier.add(layer1)
    classifier.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy'])
    return classifier
def define_multiclass_nn(self, n_neurons, m, class_num):
    classifier = Sequential()
    layer0 = Dense(n_neurons, input_dim=m, activation='relu')
    classifier.add(layer0)
    layer1 = Dense(class_num, activation='softmax')
    classifier.add(layer1)
    classifier.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy'])
    return classifier