code: def _test_formulation_added_extra_input(network_formulation):
      """
      network_formulation can be:
      'FullSpace',
      'ReducedSpace'
      'relu'
      """
      net, y = two_node_network("linear", -2.0)
      extra_input = InputLayer([1])
      if network_formulation == "FullSpace":
          formulation = FullSpaceNNFormulation(net)
      elif network_formulation == "ReducedSpace":
          formulation = ReducedSpaceNNFormulation(net)
      elif network_formulation == "relu":
          formulation = ReluPartitionFormulation(net)
      net.add_layer(extra_input)
      with pytest.raises(ValueError) as excinfo:
          formulation.input_indexes
      expected_msg = (
          "Multiple input layers are not currently supported."
      )
      assert str(excinfo.value) == expected_msg
  
imports: import numpy
  import pyomo.environ
  import pytest
  from pyomo.contrib.fbbt import interval
  from omlt import OmltBlock
  from omlt.neuralnet import FullSpaceNNFormulation, FullSpaceSmoothNNFormulation, NetworkDefinition, ReducedSpaceNNFormulation, ReducedSpaceSmoothNNFormulation, ReluPartitionFormulation
  from omlt.neuralnet.layer import ConvLayer2D, DenseLayer, IndexMapper, InputLayer, PoolingLayer2D
  from omlt.neuralnet.layers.full_space import full_space_maxpool2d_layer, _input_layer_and_block
  from omlt.neuralnet.layers.partition_based import partition_based_dense_relu_layer, default_partition_split_func
  from omlt.neuralnet.layers.reduced_space import reduced_space_dense_layer
label_desc: Use image node_id 17 for calling a global function with example usage: _test_formulation_added_extra_input(network_formulation) without return types