code: def forward_expected(self, link, inputs):
      gamma = link.gamma.array
      beta = link.beta.array
      (x,) = inputs
      shape = self.shape
      param_reshape = tuple(
          [s if i == 1 else 1 for i, s in enumerate(shape)]
      )
      x = x.astype(
          chainer.get_dtype(self.dtype, map_mixed16=numpy.float32)
      )
      x = x.reshape(shape[0] * self.groups, -1)
      x -= x.mean(axis=1, keepdims=True)
      x /= numpy.sqrt(
          link.eps + numpy.square(x).mean(axis=1, keepdims=True)
      )
      x = x.reshape(shape)
      x = gamma.reshape(param_reshape) * x + beta.reshape(param_reshape)
      if self.dtype == chainer.mixed16:
          x = x.astype(numpy.float16)
      return (x,)
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import links
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 5 for calling the GroupNormalizationTest obj's underlying member method code with example usage: obj.forward_expected(link, inputs) and returns: x