How to use representative_dataset_gen()

[tu1258]

I used tf 2.3 and met segmentation fault (core dumped) error when using representative_dataset_gen().
Code

    def representative_dataset_gen():
      for audio in validation_fingerprints:
        yield [audio]
    converter = tf.lite.TFLiteConverter.from_saved_model(flags.train_dir + '/last_model')
    converter.optimizations = [tf.lite.Optimize.DEFAULT]
    converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS]
    converter.allow_custom_ops = True
    converter.inference_input_type = tf.uint8
    converter.inference_output_type = tf.uint8
    # converter.representative_dataset = representative_dataset_gen
    quant_model = converter.convert()
    with open(flags.train_dir + '/quant_last_model.tflite', 'wb') as w:
      w.write(quant_model)

Above code can run without error but if I use converter.representative_dataset = representative_dataset_gen, it fail.

The type and shape of data are at below. The input layer size is [Batch, 16384]

type(validation_fingerprints): <class 'numpy.ndarray'>
shape(validation_fingerprints): (3093, 16384)

Any suggestion?