ssd_mobilenet_edgetpu_coco always reports 50% score for positive classifications on training (Object detection)

System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
  No
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
  Debian 9.9 (Google Cloud Platform)
• Mobile device (e.g., Pixel 4, Samsung Galaxy 10) if the issue happens on mobile device:
  no
• TensorFlow installed from (source or binary):
  Binary
• TensorFlow version (use command below):
  1.14
• Python version:
  3.5.3
• Bazel version (if compiling from source):
  0.28.0
• GCC/Compiler version (if compiling from source):
• CUDA/cuDNN version:
  10
• GPU model and memory:
  P100 (15gb)

Please provide the entire URL of the model you are using?

t
https://storage.cloud.google.com/mobilenet_edgetpu/checkpoints/ssdlite_mobilenet_edgetpu_coco_quant.tar.gz

Describe the current behavior
The model always provides 50 % as the output score for positive classfications in training. In inference on Coral EdgeTPU it is providing a larger range of scores.

Describe the expected behavior

Code to reproduce the issue

Other info / logs