code: def test_multi_class_rbf_kernel():
      estimator = KernelSVC(kernel="rbf", random_state=1, gamma=2.0)
  
      estimator.fit(np.array([[1], [2], [3]]), np.array([1, 2, 3]))
  
      assembler = LightningSVMModelAssembler(estimator)
      actual = assembler.assemble()
  
      kernels = [
          utils._svm_rbf_kernel_ast(estimator, float(i))
          for i in range(1, 4)
      ]
  
      expected = ast.VectorVal(
          [
              ast.BinNumExpr(
                  ast.BinNumExpr(
                      ast.BinNumExpr(
                          ast.NumVal(0.0),
                          ast.BinNumExpr(
                              kernels[0],
                              ast.NumVal(0.5342246289),
                              ast.BinNumOpType.MUL,
                          ),
                          ast.BinNumOpType.ADD,
                      ),
                      ast.BinNumExpr(
                          kernels[1],
                          ast.NumVal(-0.5046204480),
                          ast.BinNumOpType.MUL,
                      ),
                      ast.BinNumOpType.ADD,
                  ),
                  ast.BinNumExpr(
                      kernels[2],
                      ast.NumVal(-0.4659431306),
                      ast.BinNumOpType.MUL,
                  ),
                  ast.BinNumOpType.ADD,
              ),
              ast.BinNumExpr(
                  ast.BinNumExpr(
                      ast.BinNumExpr(
                          ast.NumVal(0.0),
                          ast.BinNumExpr(
                              kernels[0],
                              ast.NumVal(-0.5386765707),
                              ast.BinNumOpType.MUL,
                          ),
                          ast.BinNumOpType.ADD,
                      ),
                      ast.BinNumExpr(
                          kernels[1],
                          ast.NumVal(0.5729019463),
                          ast.BinNumOpType.MUL,
                      ),
                      ast.BinNumOpType.ADD,
                  ),
                  ast.BinNumExpr(
                      kernels[2],
                      ast.NumVal(-0.5386765707),
                      ast.BinNumOpType.MUL,
                  ),
                  ast.BinNumOpType.ADD,
              ),
              ast.BinNumExpr(
                  ast.BinNumExpr(
                      ast.BinNumExpr(
                          ast.NumVal(0.0),
                          ast.BinNumExpr(
                              kernels[0],
                              ast.NumVal(-0.4659431306),
                              ast.BinNumOpType.MUL,
                          ),
                          ast.BinNumOpType.ADD,
                      ),
                      ast.BinNumExpr(
                          kernels[1],
                          ast.NumVal(-0.5046204480),
                          ast.BinNumOpType.MUL,
                      ),
                      ast.BinNumOpType.ADD,
                  ),
                  ast.BinNumExpr(
                      kernels[2],
                      ast.NumVal(0.5342246289),
                      ast.BinNumOpType.MUL,
                  ),
                  ast.BinNumOpType.ADD,
              ),
          ]
      )
  
      assert cmp_exprs(actual, expected)
  
file_path: m2cgen/tests/assemblers/test_svm_lightning.py
imports: import numpy
  from lightning.classification import KernelSVC
  from m2cgen import ast
  from m2cgen.assemblers import LightningSVMModelAssembler
  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_multi_class_rbf_kernel() without return types