code: def test_randomly_connected_dense_all_inputs_connected():
      layer = RandomlyConnectedDense(
          density=0.0, units=2, use_bias=False
      )
      # Create a unit vector [1, 0, 0, 0, ...]
      x = np.zeros(10)
      x[0] = 1.0
      # For every standard basis vector
      for _ in range(10):
          x = np.roll(x, 1)
          y = layer(np.expand_dims(x, 0))
          assert tf.reduce_sum(y).numpy() != 0.0
  
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 12 for calling a global function with example usage: test_randomly_connected_dense_all_inputs_connected() without return types