The model is using custom ops written in c++ via Tensorflow’s tf.load_op_library()
I have seen the tutorials on TensorRT like: NVIDIA-AI-IOT/tf_to_trt_image_classification but most of them are for well-known image models, not sure if this approach will work with point cloud model that I mentioned?
Pure TensorRT can give you a much better performance on Jetson.
However, all the layers used in the model need to be supported on the TensorRT:
Or you will need to implement it manually with plugin API.
If there are some non-supported layers, you can try TF-TRT since it can leverage the implementation from the TensorFlow side.