The order of object detection output tensors in TF2 TFLITE model is different from TF1 and from description in export_tflite_graph_tf2.py

Prerequisites

Please answer the following questions for yourself before submitting an issue.

[+] I am using the latest TensorFlow Model Garden release and TensorFlow 2.
[+] I am reporting the issue to the correct repository. (Model Garden official or research directory)
[+] I checked to make sure that this issue has not already been filed.

1. The entire URL of the file you are using

https://github.com/tensorflow/models/blob/master/research/object_detection/export_tflite_graph_tf2.py

2. Describe the bug

According to the comments in export_tflite_graph_tf2.py, it should generate 4 output tensors in the following order:

detection_boxes: a float32 tensor of shape [1, num_boxes, 4] with box locations
detection_classes: a float32 tensor of shape [1, num_boxes] with class indices
detection_scores: a float32 tensor of shape [1, num_boxes] with class scores
num_boxes: a float32 tensor of size 1 containing the number of detected boxes

This was, in fact, the order of outputs produced by export_tflite_ssd_graph.py in TF1.

However, export_tflite_graph_tf2.py, followed by execution of tflite_convert.py in TF2, produces output tensors in this order:
detection_scores
detection_boxes
num_boxes
detection_classes

Which creates incompatibility between TF1 and TF2 for run-time inferencing at the edge.

3. Steps to reproduce

*) Train an object detection model (I am using ssd_mobilenet_v2_128x128_coco17_tpu-8)

*) Export TF2 TFLITE saved_model:
python object_detection/export_tflite_graph_tf2.py --pipeline_config_path=${CONFIG_FILE} --trained_checkpoint_dir=${MODEL_DIR} --output_directory=${OUTPUT_DIR}

*) Convert to TFLITE format:
python tflite_convert.py --output_file=${TFLITE_FILE} --saved_model_dir=${TFLITE_SAVED_MODEL_DIR}

*) Run inference in Python and examine interpreter's output details:
output_details = interpreter.get_output_details()

4. Expected behavior

Expected order of output tensors should be as described in export_tflite_graph_tf2.py, which should be identical to the order of output tensors produced in TF1 TFLITE.

5. Additional context

N/A

6. System information

• TensorFlow 2.10.0
• Python version 3.8