code: def _run(self, x, scale, bias, mean, var, epsilon=None, is_test=None, momentum=None, spatial=None):  # type: ignore
      if is_test:
          res = _batchnorm_test_mode(
              x, scale, bias, mean, var, epsilon=epsilon
          )
      else:
          res = _batchnorm_training_mode(
              x,
              scale,
              bias,
              mean,
              var,
              epsilon=epsilon,
              momentum=momentum,
          )
      return (res,)
  
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_6 obj's underlying member method code with example usage: obj._run(x, scale, bias, mean, var, epsilon, is_test, momentum, spatial) and returns: res