code: def __init__(self, groups, eigvals, eigvectors, y_hat_pca):
      self.groups = groups
      self.eigvals = eigvals
      self.eigvectors = eigvectors
      self.y_hat_pca = y_hat_pca
  
imports: import numpy
  from chainer import backend
  from chainer import function_node
  from chainer.utils import argument
  from chainer.utils import type_check
label_desc: Use image node_id 1 to create a new DecorrelatedBatchNormalizationGrad object from inherited base classes: function_node with example: obj = DecorrelatedBatchNormalizationGrad(groups, eigvals, eigvectors, y_hat_pca)