code: def forward(self, inputs):
      self.retain_inputs((0, 1))
      xp = backend.get_array_module(*inputs)
      x0, x1 = inputs
      dtype = x0.dtype
      linear_part = utils.force_array(x0 - x1, dtype)
      delta = dtype.type(self.delta)
  
      xp.abs(linear_part, out=linear_part)
      square_part = utils.force_array(xp.square(linear_part), dtype)
      linear_part *= 2 * delta
      linear_part -= delta * delta
      xp.maximum(linear_part, delta * delta, out=linear_part)
      xp.minimum(square_part, linear_part, out=square_part)
      y = square_part
      y *= 0.5
  
      if self.reduce == "sum_along_second_axis":
          return (y.sum(axis=1),)
      else:
          return (y,)
  
file_path: chainer/chainer/functions/loss/huber_loss.py
imports: import chainer
  from chainer import backend
  from chainer import function_node
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 3 for calling the HuberLoss obj's underlying member method code with example usage: obj.forward(inputs) and returns: y, y