class_docstr: This class is the entry-point to build gradient-boosted trees formulations.
  
  This class iterates over all trees in the ensemble and generates
  constraints to enforce splitting rules according to:
  
  References
  ----------
   * Misic, V. "Optimization of tree ensembles."
     Operations Research 68.5 (2020): 1605-1624.
   * Mistry, M., et al. "Mixed-integer convex nonlinear optimization with gradient-boosted trees embedded."
     INFORMS Journal on Computing (2020).
  
  Parameters
  ----------
  tree_ensemble_structure : GradientBoostedTreeModel
      the tree ensemble definition
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docstr: This method is called by the OmltBlock to build the corresponding
  mathematical formulation on the Pyomo block.
docstr_tok: ["This","method","is","called","by","the","OmltBlock","to","build","the","corresponding","mathematical","formulation","on","the","Pyomo","block","."]
code: def _build_formulation(self):
      """This method is called by the OmltBlock to build the corresponding
      mathematical formulation on the Pyomo block.
      """
      _setup_scaled_inputs_outputs(
          self.block,
          self.model_definition.scaling_object,
          self.model_definition.scaled_input_bounds,
      )
  
      add_formulation_to_block(
          block=self.block,
          model_definition=self.model_definition,
          input_vars=self.block.scaled_inputs,
          output_vars=self.block.scaled_outputs,
      )
  
file_path: OMLT/src/omlt/gbt/gbt_formulation.py
imports: import collections
  import numpy
  import pyomo.environ
  from omlt.formulation import _PyomoFormulation, _setup_scaled_inputs_outputs
  from omlt.gbt.model import GradientBoostedTreeModel
label_desc: Use image node_id 4 for calling the GBTBigMFormulation obj's underlying member method code with example usage: obj._build_formulation() without return types