code: def __init__(
      self,
      ctx,
      axes=[],
      decay_rate=0.9,
      eps=1e-05,
      batch_stat=True,
      nonlinearity="relu",
  ):
      super(FusedBatchNormalizationBackward, self).__init__(ctx)
      self._func = _F.FusedBatchNormalization(
          ctx, axes, decay_rate, eps, batch_stat, nonlinearity
      )
      self.axes = axes
      self.decay_rate = decay_rate
      self.eps = eps
      self.batch_stat = batch_stat
      self.nonlinearity = nonlinearity
      self._is_add = False
  
imports: import nnabla
  import nnabla.function
  import nnabla.functions
  from nnabla.function import PythonFunction
  from .batch_normalization import double_backward_for_batch
  from .batch_normalization import double_backward_for_global
  from .utils import no_grad
label_desc: Use image node_id 1 to create a new FusedBatchNormalizationBackward object from inherited base classes: PythonFunction with example: obj = FusedBatchNormalizationBackward(ctx, axes, decay_rate, eps, batch_stat, nonlinearity)