text: ### tensorflow==2.3.0
  
  import tensorflow.compat.v1 as tf
  
  # Float16 Quantization - Input/Output=float32
  graph_def_file="simpleHTR_freeze_graph_opt.pb"
  input_arrays=["input"]
  output_arrays=['CTCGreedyDecoder','CTCGreedyDecoder:1','CTCGreedyDecoder:2','CTCGreedyDecoder:3']
  input_tensor={"input":[1,128,32,1]}
  converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor)
  converter.optimizations = [tf.lite.Optimize.DEFAULT]
  converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS]
  converter.target_spec.supported_types = [tf.float16]
  tflite_quant_model = converter.convert()
  with open('simpleHTR_128x32_float16_quant.tflite', 'wb') as w:
      w.write(tflite_quant_model)
  print("Float16 Quantization complete! - simpleHTR_128x32_float16_quant.tflite")
  