class_docstr: Layer normalization
code: def _compute(self, xp, x):
      # xp: numpy, cupy, or chainer.functions
      mu = xp.mean(x, axis=1, keepdims=True)
      x_mu = x - mu
      squ_x_mu = xp.square(x_mu)
      var = xp.mean(squ_x_mu, axis=1, keepdims=True)
      std = xp.sqrt(var + self.eps)
      inv_std = 1.0 / std
      x_hat = x_mu * inv_std
      return x_mu, var, inv_std, x_hat
  
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 3 for calling the LayerNormalization obj's underlying member method code with example usage: obj._compute(xp, x) and returns: x_mu,  var,  inv_std,  x_hat