def METHOD_NAME(model_type="functional"):
    if model_type == "functional":
        inp = layers.Input((32, 32, 3))
        x = layers.SeparableConv2D(filters=32, kernel_size=3)(inp)
        x = layers.ReLU()(x)
        x = layers.SeparableConv2D(filters=5, kernel_size=3, activation='relu')(x)
        x = layers.Flatten()(x)
        x = layers.Dense(units=10, activation="relu")(x)
        out = layers.Dense(units=2, activation="softmax")(x)
        return tf.keras.Model(inp, out)
    elif model_type == "sequential":
        model = tf.keras.Sequential()
        model.add(layers.SeparableConv2D(filters=32, kernel_size=2, input_shape=(32, 32, 3)))
        model.add(layers.ReLU())
        model.add(layers.SeparableConv2D(filters=5, kernel_size=2, activation="relu"))
        model.add(layers.Flatten())
        model.add(layers.Dense(units=10, activation="relu"))
        model.add(layers.Dense(units=2, activation="softmax"))
        return model
    raise ValueError("Unknown model type")