def METHOD_NAME(self):
    input_size = 224
    output_size = 5
    batch_size = DEFAULT_BATCH_SIZE
    base = bases.MobileNetV2Base(image_size=input_size)
    head = heads.SoftmaxClassifierHead(
        batch_size, base.bottleneck_shape(), output_size
    )
    optimizer = optimizers.Adam()
    converter = tflite_transfer_converter.TFLiteTransferConverter(
        output_size, base, head, optimizer, batch_size
    )
    models = converter._convert()
    param_shapes = [(7 * 7 * 1280, output_size), (output_size,)]
    self.assertSignatureEqual(
        models["optimizer"],
        param_shapes + param_shapes + param_shapes + param_shapes + [()],
        param_shapes + param_shapes + param_shapes + [()],
    )