code: def test_log1p_exp_output_transform():
      estimator = lgb.LGBMRegressor(
          n_estimators=2,
          random_state=1,
          max_depth=1,
          objective="cross_entropy_lambda",
      )
      utils.get_bounded_regression_model_trainer()(estimator)
  
      assembler = LightGBMModelAssembler(estimator)
      actual = assembler.assemble()
  
      expected = ast.Log1pExpr(
          ast.ExpExpr(
              ast.BinNumExpr(
                  ast.IfExpr(
                      ast.CompExpr(
                          ast.FeatureRef(12),
                          ast.NumVal(19.23),
                          ast.CompOpType.GT,
                      ),
                      ast.NumVal(0.6622623010380544),
                      ast.NumVal(0.6684065452877841),
                  ),
                  ast.IfExpr(
                      ast.CompExpr(
                          ast.FeatureRef(12),
                          ast.NumVal(15.145),
                          ast.CompOpType.GT,
                      ),
                      ast.NumVal(0.1404975120475147),
                      ast.NumVal(0.14535916856709272),
                  ),
                  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 7 for calling a global function with example usage: test_log1p_exp_output_transform() without return types