code: def test_randomly_connected_dense_shape(
      inputs: np.array,
      units: int,
      expected_output_shape: Tuple[int, ...],
  ):
      layer = RandomlyConnectedDense(units=units)
      y = layer(inputs)
      assert y.shape == expected_output_shape
  
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 10 for calling a global function with example usage: test_randomly_connected_dense_shape(inputs, units, expected_output_shape) without return types