code: def _quantize_dynamic(model: tf.Module):
      converter = tf.lite.TFLiteConverter.from_keras_model(model)
      converter.optimizations = [tf.lite.Optimize.DEFAULT]
      tflite_quant_model = converter.convert()
      return tflite_quant_model
  
imports: from typing import List, Tuple
  from nebullvm.core.models import QuantizationType
  from nebullvm.optional_modules.tensorflow import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: _quantize_dynamic(model) and returns: tflite_quant_model