code: def _run(  # type: ignore
      self,
      x,
      coefficients=None,
      intercepts=None,
      targets=1,
      post_transform=None,
  ):
      coefficients = np.array(coefficients).astype(x.dtype)
      intercepts = np.array(intercepts).astype(x.dtype)
      n = coefficients.shape[0] // targets
      coefficients = coefficients.reshape(targets, n).T
      score = np.dot(x, coefficients)
      if intercepts is not None:
          score += intercepts
      if post_transform == "NONE":
          return (score,)
      raise NotImplementedError(
          f"post_transform: {post_transform!r} is not implemented."
      )
  
imports: import numpy
  from onnx.reference.ops.aionnxml._op_run_aionnxml import OpRunAiOnnxMl
label_desc: Use image node_id 1 for calling the LinearRegressor obj's underlying member method code with example usage: obj._run(x, coefficients, intercepts, targets, post_transform) and returns: score