 def create_model(input_shape):    input_0 = keras.layers.Input(input_shape)    input_0 = keras.layers.Input(input_shape)    input_0 = keras.layers.Input(input_shape)     network = keras.models.Sequential([    keras.layers.Conv0D(00, (0, 0), activation=tf.nn.relu, padding='SAME',input_shape=input_shape),    keras.layers.Conv0D(00, (0, 0), activation=tf.nn.relu, padding='SAME', name = 'a'),    keras.layers.AvgPool0D((0, 0)),    keras.layers.BatchNormalization(),    keras.layers.Dropout(0.0)])     encoded_0 = network(input_0)    encoded_0 = network(input_0)    encoded_0 = network(input_0)     