code: def test_if_sparse_feature_sizes_have_increased(
      new_sparse_feature_sizes: Dict[Text, Dict[Text, List[int]]],
      old_sparse_feature_sizes: Dict[Text, Dict[Text, List[int]]],
      expected_output: bool,
  ):
      """Tests if any of the sparse feature sizes has increased."""
      output = (
          TransformerRasaModel._sparse_feature_sizes_have_increased(
              new_sparse_feature_sizes=new_sparse_feature_sizes,
              old_sparse_feature_sizes=old_sparse_feature_sizes,
          )
      )
      assert output == expected_output
  
file_path: rasa/tests/utils/tensorflow/test_models.py
imports: import pytest
  from typing import Dict, Text, Union, Tuple, List
  import numpy
  import tensorflow
  from rasa.utils.tensorflow.models import RasaModel, TransformerRasaModel
  from rasa.utils.tensorflow.model_data import RasaModelData
  from rasa.utils.tensorflow.model_data import FeatureArray
  from rasa.utils.tensorflow.constants import LABEL, IDS, SENTENCE
  from rasa.shared.nlu.constants import TEXT, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
label_desc: Use image node_id 4 for calling a global function with example usage: test_if_sparse_feature_sizes_have_increased(new_sparse_feature_sizes, old_sparse_feature_sizes, expected_output) without return types