code: def test_glm_identity_link_func():
      estimator = linear_model.TweedieRegressor(
          power=0, link="identity", max_iter=10
      )
      estimator = estimator.fit([[1], [2]], [0.1, 0.2])
  
      assembler = assemblers.SklearnGLMModelAssembler(estimator)
      actual = assembler.assemble()
  
      expected = ast.BinNumExpr(
          ast.NumVal(0.12),
          ast.BinNumExpr(
              ast.FeatureRef(0), ast.NumVal(0.02), ast.BinNumOpType.MUL
          ),
          ast.BinNumOpType.ADD,
      )
  
      assert cmp_exprs(actual, expected)
  
file_path: m2cgen/tests/assemblers/test_linear_sklearn.py
imports: import numpy
  import pytest
  from sklearn import linear_model
  from m2cgen import assemblers, ast
  from tests.utils import cmp_exprs
label_desc: Use image node_id 5 for calling a global function with example usage: test_glm_identity_link_func() without return types