class_docstr: Layer normalization
code: def forward(self, inputs):
      self.retain_inputs((0, 1))
      xp = backend.get_array_module(*inputs)
      x, gamma, beta = inputs
      x_mu, var, inv_std, x_hat = self._compute(xp, x)
      scaled_x = x_hat * gamma[None,]
      shifted_x = scaled_x + beta[None,]
      return (shifted_x,)
  
file_path: chainer/chainer/functions/normalization/layer_normalization.py
imports: from chainer import backend
  from chainer import function_node
  import chainer.functions
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the LayerNormalization obj's underlying member method code with example usage: obj.forward(inputs) and returns: shifted_x