tflite 转换；遇到未解决的自定义操作：TensorArrayV3.Node

Question

[编辑相关性]

使用此配置编译此模型后：

converter = tf.lite.TFLiteConverter.from_frozen_graph(
        path/to/graph.pb,
        input_arrays=["Cast"],
        output_arrays=["features"],
        input_shapes={"Cast":[1, 128, 64, 3]}) 
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,
        tf.lite.OpsSet.SELECT_TF_OPS]
converter.allow_custom_ops = True
converter.experimental_new_converter = True
converter.optimizations = [tf.lite.Optimize.DEFAULT]
tflite_model = converter.convert()

tflite生成了模型，但调用解释allocate_tensors器会导致此错误：

RuntimeError: Regular TensorFlow ops are not supported by this interpreter. 
              Make sure you apply/link the Flex delegate before 
              inference.Node number 0 (FlexTensorArrayV3) failed to prepare.

所以看来我已经构建了tflite_convert对张量流操作的支持......