code: def _supported_default_activation_constraints(self):
      return {
          "linear": linear_activation_constraint,
          "relu": bigm_relu_activation_constraint,
      }
  
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 2 for calling the ReluBigMFormulation obj's underlying member method code with example usage: obj._supported_default_activation_constraints() and returns: dict