code: def _run(self, x, alpha=None, beta=None):  # type: ignore
      alpha = alpha or self.alpha  # type: ignore
      beta = beta or self.beta  # type: ignore
      y = np.maximum(0, np.minimum(1, x * alpha + beta))
      return (y,)
  
imports: import numpy
  from onnx.reference.ops._op import OpRunUnaryNum
label_desc: Use image node_id 1 for calling the HardSigmoid obj's underlying member method code with example usage: obj._run(x, alpha, beta) and returns: y