code: def test_simple_sigmoid_output_transform():
      estimator = lgb.LGBMRegressor(
          n_estimators=2,
          random_state=1,
          max_depth=1,
          objective="cross_entropy",
      )
      utils.get_bounded_regression_model_trainer()(estimator)
  
      assembler = LightGBMModelAssembler(estimator)
      actual = assembler.assemble()
  
      expected = ast.SigmoidExpr(
          ast.BinNumExpr(
              ast.IfExpr(
                  ast.CompExpr(
                      ast.FeatureRef(12),
                      ast.NumVal(19.23),
                      ast.CompOpType.GT,
                  ),
                  ast.NumVal(4.002437528537838),
                  ast.NumVal(4.090096709787509),
              ),
              ast.IfExpr(
                  ast.CompExpr(
                      ast.FeatureRef(12),
                      ast.NumVal(14.895),
                      ast.CompOpType.GT,
                  ),
                  ast.NumVal(-0.0417499606641773),
                  ast.NumVal(0.02069953712454655),
              ),
              ast.BinNumOpType.ADD,
          )
      )
  
      assert utils.cmp_exprs(actual, expected)
  
file_path: m2cgen/tests/assemblers/test_boosting_lightgbm.py
imports: import lightgbm
  import numpy
  import pytest
  from m2cgen import ast
  from m2cgen.assemblers import LightGBMModelAssembler
  from tests import utils
label_desc: Use image node_id 6 for calling a global function with example usage: test_simple_sigmoid_output_transform() without return types