TensorRT Error on Jetson Nano when converting a frozen graph to trt graph.

Hey all fairly new to Tensorflow and TensorRT, I am having trouble converting an existing frozen graph to a tensorRT graph.

Code snippet for optimizing loading the frozen graph and for converting to TensorRT graph:

def load_object_detection_model(self):
        # Load TensorFlow object detection model

        gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=.5)

        EXPORTED_OBJECT_DETECTION_MODEL = 'frozen_model_x.pb'
        self.graph_obj = tf.Graph()
        with self.graph_obj.as_default():
            od_graph_def = tf.GraphDef()
            with tf.gfile.GFile(EXPORTED_OBJECT_DETECTION_MODEL, 'rb') as fid:
                serialized_graph = fid.read()
                tf.import_graph_def(od_graph_def, name='')

         # Optimize Graph with TensorRT

        trt_graph = trt.create_inference_graph(
            outputs=['num_detections', 'detection_boxes', 'detection_scores', 'detection_classes'],

        print('reading graph')

        output_node = tf.import_graph_def(
            return_elements=['num_detections', 'detection_boxes', 'detection_scores', 'detection_classes'])

        self.graph_obj = output_node # Replace frozen graph with optimized graph 

        print('converted graph')

This runs without any errors, however I think I am doing something wrong for line 30 above. Is that the right way of replacing the old graph with the new graph?

# get handles to objects in object detection graph
        ops = self.graph_obj.get_operations()
        all_tensor_names = {output.name for op in ops for output in op.outputs}
        self.tensor_dict = {}
        for key in [
            'num_detections', 'detection_boxes', 'detection_scores',
            'detection_classes', 'detection_masks'
            tensor_name = key + ':0'
            if tensor_name in all_tensor_names:
                self.tensor_dict[key] = self.graph_obj.get_tensor_by_name(tensor_name)

        self.obj_image_tensor = self.graph_obj.get_tensor_by_name('image_tensor:0')
        self.logger.debug('created object detection model graph from {}'.format(EXPORTED_OBJECT_DETECTION_MODEL))

        # create session for object detection
        self.sess_obj = tf.Session(graph=self.graph_obj)
        self.logger.debug('created object detection model session')

The error output I get is:

in load_object_detection_model
    ops = self.graph_obj.get_operations()
AttributeError: 'list' object has no attribute 'get_operations'

Which is from line 2, in the second snippet. This is being run on a Jetson Nano. (The code runs perfectly fine without the TensorRT conversion.)

Running Ubuntu 18.04, Python 3.6.8, TensorFlow 1.13.1. TensorRT details below:

ii  graphsurgeon-tf                            5.0.6-1+cuda10.0                                arm64        GraphSurgeon for TensorRT package
ii  libnvinfer-dev                             5.0.6-1+cuda10.0                                arm64        TensorRT development libraries and headers
ii  libnvinfer-samples                         5.0.6-1+cuda10.0                                all          TensorRT samples and documentation
ii  libnvinfer5                                5.0.6-1+cuda10.0                                arm64        TensorRT runtime libraries
ii  python-libnvinfer                          5.0.6-1+cuda10.0                                arm64        Python bindings for TensorRT
ii  python-libnvinfer-dev                      5.0.6-1+cuda10.0                                arm64        Python development package for TensorRT
ii  python3-libnvinfer                         5.0.6-1+cuda10.0                                arm64        Python 3 bindings for TensorRT
ii  python3-libnvinfer-dev                     5.0.6-1+cuda10.0                                arm64        Python 3 development package for TensorRT
ii  tensorrt                                                       arm64        Meta package of TensorRT
ii  uff-converter-tf                           5.0.6-1+cuda10.0                                arm64        UFF converter for TensorRT package