code: def test_dense_for_sparse_get_feature_type(
      layer_name: Text, expected_feature_type: Union[Text, None]
  ):
      layer = DenseForSparse(name=layer_name, units=10)
      assert layer.get_feature_type() == expected_feature_type
  
imports: from typing import Text, List, Tuple, Union, Optional
  import pytest
  from _pytest.monkeypatch import MonkeyPatch
  import numpy
  import tensorflow
  from rasa.utils.tensorflow.layers import DotProductLoss, MultiLabelDotProductLoss, RandomlyConnectedDense, DenseForSparse
  from rasa.utils.tensorflow.constants import INNER, SOFTMAX, LABEL, LABEL_PAD_ID
  import rasa.utils.tensorflow.layers_utils
  from rasa.shared.nlu.constants import TEXT, INTENT, ACTION_NAME, ACTION_TEXT, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
  from rasa.core.constants import DIALOGUE
label_desc: Use image node_id 13 for calling a global function with example usage: test_dense_for_sparse_get_feature_type(layer_name, expected_feature_type) without return types