code: def test_sigmoid_kernel():
      estimator = SVC(kernel="sigmoid", random_state=1, gamma=2.0)
  
      estimator.fit([[1], [2]], [1, 2])
  
      assembler = SklearnSVMModelAssembler(estimator)
      actual = assembler.assemble()
  
      def kernel_ast(sup_vec_value):
          return ast.TanhExpr(
              ast.BinNumExpr(
                  ast.BinNumExpr(
                      ast.NumVal(estimator.gamma),
                      ast.BinNumExpr(
                          ast.NumVal(sup_vec_value),
                          ast.FeatureRef(0),
                          ast.BinNumOpType.MUL,
                      ),
                      ast.BinNumOpType.MUL,
                  ),
                  ast.NumVal(0.0),
                  ast.BinNumOpType.ADD,
              )
          )
  
      expected = utils._create_expected_svm_single_output_ast(
          estimator.dual_coef_,
          estimator.intercept_,
          [kernel_ast(1.0), kernel_ast(2.0)],
      )
  
      assert cmp_exprs(actual, expected)
  
file_path: m2cgen/tests/assemblers/test_svm_sklearn.py
imports: import numpy
  import pytest
  from sklearn.svm import SVC
  from m2cgen import ast
  from m2cgen.assemblers import SklearnSVMModelAssembler
  from tests.assemblers import utils
  from tests.utils import cmp_exprs
label_desc: Use image node_id 3 for calling a global function with example usage: test_sigmoid_kernel() and returns: ast