Incorrect quantized SSD mobiledet DSP model after quantization aware training

Prerequisites

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

• 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/tree/master/research/object_detection

2. Describe the bug

I trained SSD+Mobiledet DSP model on a custom dataset, and did quantization aware training for 17K steps. However, when I exported the model to frozen graph using export_tflite_ssd_graph.py, the FakeQuantWithMinMaxVars that comes from ReLU6 have min and max range larger than 0-6.

https://github.com/tensorflow/models/issues/6112 this issue describes the similar issue, but it's not answered.

3. Steps to reproduce

1. train SSD+mobiledet DSP, with pretrained weights stored in this link as fine-tune checkpoint:http://download.tensorflow.org/models/object_detection/ssdlite_mobiledet_dsp_320x320_coco_2020_05_19.tar.gz.
2. perform quantization aware training with the trained SSD+mobiledet DSP model as fine-tune checkpoint.
3. export the tflite graph using export_tflite_ssd_graph.py.

4. Expected behavior

The tflite graph would contain FakeQuantWithMinMaxVars that comes from ReLU6 that have min and max range larger than 0-6.

5. Additional context

6. System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
• Mobile device name if the issue happens on a mobile device:
• TensorFlow installed from (source or binary): pip install
• TensorFlow version (use command below): 1.15
• Python version: 3.7
• Bazel version (if compiling from source):
• GCC/Compiler version (if compiling from source):
• CUDA/cuDNN version: 10.0.130
• GPU model and memory: Nvdia GeForce RTX 2080