code: def test_concat_sparse_dense_correct_output_for_dense_input() -> None:
      layer = ConcatenateSparseDenseFeatures(
          attribute=attribute_name,
          feature_type=SEQUENCE,
          feature_type_signature=[
              realistic_feature_signature_dense_1,
              realistic_feature_signature_dense_2,
          ],
          config=dict(
              model_config_basic,
              # also activate all dropout to check that it has no effect on dense features
              **{SPARSE_INPUT_DROPOUT: True, DENSE_INPUT_DROPOUT: True},
          ),
      )
      outputs_expected = [
          [[10.0, 1.0, 2.0], [20.0, 3.0, 4.0], [30.0, 5.0, 6.0]],
          [[40.0, 1.5, 2.5], [50.0, 3.5, 4.5], [0.0, 0.0, 0.0]],
      ]
      inputs = (
          [
              realistic_feature_dense_seq_1,
              realistic_feature_dense_seq_2,
          ],
      )
      train_outputs = layer(inputs, training=True)
      assert (train_outputs.numpy() == outputs_expected).all()
      test_outputs = layer(inputs, training=False)
      assert (test_outputs.numpy() == outputs_expected).all()
  
imports: import pytest
  import tensorflow
  import numpy
  from typing import Text, Union, Any, Dict, List, Type
  from rasa.shared.nlu.constants import TEXT, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
  from rasa.utils.tensorflow import layers
  from rasa.utils.tensorflow.rasa_layers import ConcatenateSparseDenseFeatures, RasaFeatureCombiningLayer, RasaSequenceLayer, RasaCustomLayer
  from rasa.utils.tensorflow.constants import DENSE_INPUT_DROPOUT, SPARSE_INPUT_DROPOUT, DROP_RATE, DENSE_DIMENSION, REGULARIZATION_CONSTANT, CONCAT_DIMENSION, CONNECTION_DENSITY, DROP_RATE_ATTENTION, KEY_RELATIVE_ATTENTION, VALUE_RELATIVE_ATTENTION, MAX_RELATIVE_POSITION, UNIDIRECTIONAL_ENCODER, HIDDEN_LAYERS_SIZES, NUM_TRANSFORMER_LAYERS, TRANSFORMER_SIZE, NUM_HEADS, SENTENCE, SEQUENCE, MASKED_LM, LABEL
  from rasa.utils.tensorflow.exceptions import TFLayerConfigException
  from rasa.utils.tensorflow.model_data import FeatureSignature
label_desc: Use image node_id 5 for calling a global function with example usage: test_concat_sparse_dense_correct_output_for_dense_input() without return types