code: def model_loader(filename: str) -> lite.TFLiteConverter:
      """TF 1.x and 2.x tflite converter loading function
  
      Args:
          filename (str): Keras model file
  
      Returns:
          lite.TFLiteConverter: TFLite converter to be used
      """
      if __version__[0] == "2":
          model = keras.models.load_model(filename)
          return lite.TFLiteConverter.from_keras_model(model)
      return lite.TFLiteConverter.from_keras_model_file(filename)
  
file_path: auptimizer/src/aup/dlconvert/pytorch_to_tflite.py
imports: import tf2onnx
  from pytorch2keras import pytorch_to_keras
  from tensorflow import lite, keras, __version__
  from typing import List
  from os import path, remove
  import torch
  from absl import flags, app
  from .utils import reset_flag
  from .utils import load_package
  from .to_tflite import create_converter
label_desc: Use image node_id 1 for calling a global function with example usage: model_loader(filename) and returns: lite, lite