def METHOD_NAME(model_type="Sequential"):
    tf.keras.backend.clear_session()
    if model_type == "Sequential":
        return tf.keras.Sequential([
            tf.keras.layers.Conv2D(32, 3, strides=(2, 2), name='conv1', padding='same', input_shape=(28, 28, 3)),
            tf.keras.layers.Conv2D(64, 5, name='conv2', padding='same'),
            tf.keras.layers.Flatten(),
            tf.keras.layers.Dense(10, name='linear')
        ])
    elif model_type == "Functional":
        inp = tf.keras.Input((28, 28, 3))
        x = tf.keras.layers.Conv2D(32, 3, strides=(2, 2), name='conv1', padding='same')(inp)
        x = tf.keras.layers.Conv2D(64, 5, name='conv2', padding='same')(x)
        x = tf.keras.layers.Flatten()(x)
        out = tf.keras.layers.Dense(10, name = 'linear')(x)
        return tf.keras.Model(inp, out)