code: def test_linear_regressor_2(self):
      X = make_tensor_value_info("X", TensorProto.FLOAT, [None, None])
      Y = make_tensor_value_info("Y", TensorProto.FLOAT, [None, None])
      node1 = make_node(
          "LinearRegressor",
          ["X"],
          ["Y"],
          domain="ai.onnx.ml",
          coefficients=[0.3, -0.77, 0.3, -0.77],
          intercepts=[0.5, 0.7],
          post_transform="NONE",
          targets=2,
      )
      graph = make_graph([node1], "ml", [X], [Y])
      onx = make_model_gen_version(graph, opset_imports=OPSETS)
      check_model(onx)
      x = np.arange(6).reshape((-1, 2)).astype(np.float32)
      expected = np.array(
          [[-0.27, -0.07], [-1.21, -1.01], [-2.15, -1.95]],
          dtype=np.float32,
      )
      self._check_ort(onx, {"X": x}, equal=True)
      sess = ReferenceEvaluator(onx)
      got = sess.run(None, {"X": x})
      assert_allclose(expected, 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 18 for calling the TestReferenceEvaluatorAiOnnxMl obj's underlying member method code with example usage: obj.test_linear_regressor_2() without return types