code: def _run(self, x, s, bias, epsilon=None):  # type: ignore
      dims_x = len(x.shape)
      axis = tuple(range(2, dims_x))
      mean = np.mean(x, axis=axis, keepdims=True)
      var = np.var(x, axis=axis, keepdims=True)
      dim_ones = (1,) * (dims_x - 2)
      s = s.reshape(-1, *dim_ones)
      bias = bias.reshape(-1, *dim_ones)
      y = s * (x - mean) / np.sqrt(var + epsilon) + bias
      return (y.astype(x.dtype),)
  
imports: import numpy
  from onnx.reference.op_run import OpRun
label_desc: Use image node_id 1 for calling the InstanceNormalization obj's underlying member method code with example usage: obj._run(x, s, bias, epsilon) and returns: y