code: def _get_test_svm_regressor_linear(post_transform, one_class=0):
      X = make_tensor_value_info("X", TensorProto.FLOAT, [None, None])
      Y = make_tensor_value_info("Y", TensorProto.FLOAT, [None])
      kwargs = {
          "coefficients": [0.28290501, -0.0266512, 0.01674867],
          "kernel_params": [0.001, 0.0, 3.0],
          "kernel_type": "LINEAR",
          "rho": [1.24032312],
          "post_transform": post_transform,
          "n_supports": 0,
          "one_class": one_class,
      }
  
      node1 = make_node(
          "SVMRegressor", ["X"], ["Y"], domain="ai.onnx.ml", **kwargs
      )
      graph = make_graph([node1], "ml", [X], [Y])
      onx = make_model_gen_version(graph, opset_imports=OPSETS)
      check_model(onx)
      return onx
  
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 40 for calling the TestReferenceEvaluatorAiOnnxMl obj's underlying member method code with example usage: obj._get_test_svm_regressor_linear(post_transform, one_class) and returns: onx