code: def test_tflite(
      keras_model: tf.keras.Model,
      tflite_model: bytearray,
      size: Union[int, List[int]],
      high: float = 1,
      atol: float = 1e-04,
  ) -> bool:
      """Verifies if the output of TFLite model and TF Keras model are identical.
  
      Args:
        keras_model: Input TensorFlow Keras model.
        tflite_model: Input TFLite model flatbuffer.
        size: Size of the input tesnor.
        high: Higher boundary of the values in input tensors.
        atol: Absolute tolerance of the difference between the outputs of Keras
          model and TFLite model.
  
      Returns:
        True if the output of TFLite model and TF Keras model are identical.
        Otherwise, False.
      """
      random_input = create_random_sample(size=size, high=high)
      random_input = tf.convert_to_tensor(random_input)
  
      return is_same_output(
          tflite_model=tflite_model,
          keras_model=keras_model,
          input_tensors=random_input,
          atol=atol,
      )
  
file_path: mediapipe/mediapipe/model_maker/python/core/utils/test_util.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Sequence
  from typing import Dict, List, Union
  import numpy
  import tensorflow
  from mediapipe.model_maker.python.core.data import dataset
  from mediapipe.model_maker.python.core.utils import model_util
label_desc: Use image node_id 6 for calling a global function with example usage: test_tflite(keras_model, tflite_model, size, high, atol) and returns: is_same_output