code: import tensorflow as tf
  
  tf.compat.v1.enable_eager_execution()
  
  # Weight Quantization - Input/Output=float32
  converter = tf.lite.TFLiteConverter.from_saved_model('./saved_model')
  converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]
  tflite_quant_model = converter.convert()
  with open('./mobilenet_v3_large_224_dm07_weight_quant.tflite', 'wb') as w:
      w.write(tflite_quant_model)
  print("Weight Quantization complete! - mobilenet_v3_large_224_dm07_weight_quant.tflite")
  
  
apis: tensorflow.compat.v1.enable_eager_execution tensorflow.lite.TFLiteConverter.from_saved_model