code: def test_w_const():
      estimator = utils.StatsmodelsSklearnLikeWrapper(
          sm.GLS, dict(init=dict(fit_intercept=True))
      )
      _, __, estimator = utils.get_regression_model_trainer()(estimator)
  
      assembler = assemblers.StatsmodelsModelAssemblerSelector(
          estimator
      )
      actual = assembler.assemble()
  
      feature_weight_mul = [
          ast.BinNumExpr(
              ast.FeatureRef(0),
              ast.NumVal(-0.1086131135490779),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(1),
              ast.NumVal(0.046461486329934965),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(2),
              ast.NumVal(0.027432259970185422),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(3),
              ast.NumVal(2.6160671309537693),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(4),
              ast.NumVal(-17.51793656329748),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(5),
              ast.NumVal(3.7674418196771957),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(6),
              ast.NumVal(-2.1581753172923886e-05),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(7),
              ast.NumVal(-1.4711768622633619),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(8),
              ast.NumVal(0.29567671400629103),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(9),
              ast.NumVal(-0.012233831527258853),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(10),
              ast.NumVal(-0.9220356453705244),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(11),
              ast.NumVal(0.009038220462695548),
              ast.BinNumOpType.MUL,
          ),
          ast.BinNumExpr(
              ast.FeatureRef(12),
              ast.NumVal(-0.5425830337142312),
              ast.BinNumOpType.MUL,
          ),
      ]
  
      expected = assemblers.utils.apply_op_to_expressions(
          ast.BinNumOpType.ADD,
          ast.NumVal(36.36708074657767),
          *feature_weight_mul,
      )
  
      assert utils.cmp_exprs(actual, expected)
  
imports: import numpy
  import pytest
  import statsmodels.api
  from statsmodels.regression.process_regression import ProcessMLE
  from m2cgen import assemblers, ast
  from tests import utils
label_desc: Use image node_id 2 for calling a global function with example usage: test_w_const() without return types