code: def forward_expected(self, inputs):
      (x,) = inputs
      mean = self.mean.copy()
      projection = self.projection.copy()
      return (
          _decorrelated_batch_normalization(
              x, mean, projection, self.groups
          ),
      )
  
imports: import numpy
  from chainer import functions
  from chainer import testing
label_desc: Use image node_id 4 for calling the TestFixedDecorrelatedBatchNormalization obj's underlying member method code with example usage: obj.forward_expected(inputs) and returns: _decorrelated_batch_normalization