docstr: This class is used for building "full-space" formulations of
  neural network models composed of relu activations using
  a complementarity formulation (smooth represenation)
  
  Parameters
  ----------
  network_structure : NetworkDefinition
     the neural network definition
docstr_tok: ["This","class","is","used","for","building","``","full-space","''","formulations","of","neural","network","models","composed","of","relu","activations","using","a","complementarity","formulation","(","smooth","represenation",")","Parameters","--","--","--","--","--","network_structure",":","NetworkDefinition","the","neural","network","definition"]
code: def __init__(self, network_structure):
      """
      This class is used for building "full-space" formulations of
      neural network models composed of relu activations using
      a complementarity formulation (smooth represenation)
  
      Parameters
      ----------
      network_structure : NetworkDefinition
         the neural network definition
      """
      super().__init__(network_structure)
  
imports: import numpy
  import pyomo.environ
  from omlt.formulation import _PyomoFormulation, _setup_scaled_inputs_outputs
  from omlt.neuralnet.activations import ACTIVATION_FUNCTION_MAP
  from omlt.neuralnet.activations import ComplementarityReLUActivation, bigm_relu_activation_constraint, linear_activation_constraint, linear_activation_function, sigmoid_activation_constraint, sigmoid_activation_function, softplus_activation_constraint, softplus_activation_function, tanh_activation_constraint, tanh_activation_function
  from omlt.neuralnet.layer import ConvLayer2D, DenseLayer, InputLayer, PoolingLayer2D
  from omlt.neuralnet.layers.full_space import full_space_conv2d_layer, full_space_dense_layer, full_space_maxpool2d_layer
  from omlt.neuralnet.layers.partition_based import default_partition_split_func, partition_based_dense_relu_layer
  from omlt.neuralnet.layers.reduced_space import reduced_space_dense_layer
label_desc: Use image node_id 1 to create a new ReluComplementarityFormulation object from inherited base classes: FullSpaceNNFormulation with example: obj = ReluComplementarityFormulation(network_structure)