code: def forward_expected(self, inputs):
      x, gamma, beta = inputs
      mean = numpy.mean(x, axis=1, keepdims=True)
      var = numpy.mean(numpy.square(x - mean), axis=1, keepdims=True)
      std = numpy.sqrt(var + self.eps)
      y_expected = numpy.expand_dims(gamma, axis=0) * (
          x - mean
      ) / std + numpy.expand_dims(beta, axis=0)
      return (y_expected,)
  
file_path: chainer/tests/chainer_tests/functions_tests/normalization_tests/test_layer_normalization.py
imports: import numpy
  from chainer import functions
  from chainer import testing
label_desc: Use image node_id 3 for calling the TestLayerNormalization obj's underlying member method code with example usage: obj.forward_expected(inputs) and returns: y_expected