code: def exponential_decay_noise(xp, shape, dtype, hook, opt):
      """Time-dependent annealed Gaussian noise function from the paper:
  
      `Adding Gradient Noise Improves Learning for Very Deep Networks
      <https://arxiv.org/pdf/1511.06807>`_.
      """
      std = numpy.sqrt(hook.eta / numpy.power(1 + opt.t, 0.55))
      return xp.random.normal(0, std, shape).astype(dtype)
  
file_path: chainer/chainer/optimizer_hooks/gradient_noise.py
imports: import numpy
  import chainer
  from chainer import cuda
label_desc: Use image node_id 1 for calling a global function with example usage: exponential_decay_noise(xp, shape, dtype, hook, opt) and returns: xp