code: def _run(  # type: ignore
      self,
      x,
      scale,
      bias,
      mean,
      var,
      epsilon=None,
      momentum=None,
      training_mode=None,
  ):
      if training_mode == 0:  # type: ignore
          res = _batchnorm_test_mode(
              x, scale, bias, mean, var, epsilon=epsilon
          )
          return (res,)
      res, __, _, output_mean, output_var = _batchnorm_training_mode(
          x, scale, bias, mean, var, momentum, epsilon
      )
      return res, output_mean, output_var
  
file_path: onnx/onnx/reference/ops/op_batch_normalization.py
imports: import numpy
  from onnx.reference.op_run import OpRun
label_desc: Use image node_id 1 for calling the BatchNormalization_14 obj's underlying member method code with example usage: obj._run(x, scale, bias, mean, var, epsilon, momentum, training_mode) and returns: res,  output_mean,  output_var, res