text: ### tf-nightly==2.3.0-dev20200527
  
  import tensorflow as tf
  
  # Weight Quantization - Input/Output=float32
  graph_def_file="tflite_graph_with_postprocess.pb"
  input_arrays=["normalized_input_image_tensor"]
  output_arrays=['TFLite_Detection_PostProcess','TFLite_Detection_PostProcess:1','TFLite_Detection_PostProcess:2','TFLite_Detection_PostProcess:3']
  input_tensor={"normalized_input_image_tensor":[1,320,320,3]}
  converter = tf.compat.v1.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor)
  converter.allow_custom_ops=True
  converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]
  tflite_quant_model = converter.convert()
  with open('ssdlite_mobiledet_edgetpu_320x320_coco_weight_quant.tflite', 'wb') as w:
      w.write(tflite_quant_model)
  print("Weight Quantization complete! - ssdlite_mobiledet_edgetpu_320x320_coco_weight_quant.tflite")