code: def test_svm_regressor_linear_one_class(self):
      x = (np.arange(9).reshape((-1, 3)) - 5).astype(np.float32) / 5
      expected_post = {
          "NONE": (
              np.array(
                  [[1.0], [1.0], [1.0]],
                  dtype=np.float32,
              ),
          ),
      }
      for post, expected in expected_post.items():
          with self.subTest(post_transform=post):
              onx = self._get_test_svm_regressor_linear(
                  post, one_class=1
              )
              self._check_ort(onx, {"X": x}, rev=True, atol=1e-5)
              sess = ReferenceEvaluator(onx)
              got = sess.run(None, {"X": x})
              assert_allclose(expected[0], got[0], atol=1e-6)
  
imports: import unittest
  from functools import wraps
  from os import getenv
  import numpy
  from numpy.testing import assert_allclose
  from parameterized import parameterized
  from onnx import ONNX_ML, TensorProto, TypeProto, ValueInfoProto
  from onnx.checker import check_model
  from onnx.defs import onnx_opset_version
  from onnx.helper import make_graph, make_model_gen_version, make_node, make_opsetid, make_tensor, make_tensor_value_info
  from onnx.reference import ReferenceEvaluator
label_desc: Use image node_id 42 for calling the TestReferenceEvaluatorAiOnnxMl obj's underlying member method code with example usage: obj.test_svm_regressor_linear_one_class() without return types