code: def _combine_dfs(left, right, operators):
      def _make_branch(branch):
          if branch == "input_matrix":
              return "FunctionTransformer(copy)"
          elif branch[0] == "CombineDFs":
              return _combine_dfs(branch[1], branch[2], operators)
          elif branch[1] == "input_matrix":  # If depth of branch == 1
              tpot_op = get_by_name(branch[0], operators)
  
              if tpot_op.root:
                  return "StackingEstimator(estimator={})".format(
                      _process_operator(branch, operators)[0]
                  )
              else:
                  return _process_operator(branch, operators)[0]
          else:  # We're going to have to make a pipeline
              tpot_op = get_by_name(branch[0], operators)
  
              if tpot_op.root:
                  return "StackingEstimator(estimator={})".format(
                      generate_pipeline_code(branch, operators)
                  )
              else:
                  return generate_pipeline_code(branch, operators)
  
      return "make_union(\n{},\n{}\n)".format(
          _indent(_make_branch(left), 4),
          _indent(_make_branch(right), 4),
      )
  
file_path: tpot/tpot/export_utils.py
imports: import deap
label_desc: Use image node_id 11 for calling a global function with example usage: _combine_dfs(left, right, operators) and returns: str, str, _combine_dfs, str, _process_operator, str, generate_pipeline_code