class_docstr: Randomized Leaky rectifier unit.
class_docstr_tok: ["Randomized","Leaky","rectifier","unit","."]
code: def forward_cpu(self, inputs):
      (x,) = inputs
      if chainer.config.train:
          if self.r is None:
              self.r = np.random.uniform(
                  self.lower, self.upper, x.shape
              ).astype(x.dtype, copy=False)
      else:
          self.r = np.full(
              x.shape, (self.lower + self.upper) / 2, dtype=x.dtype
          )
      y = np.where(x >= 0, x, x * self.r)
      self.retain_outputs((0,))
      return (y,)
  
imports: import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.utils import argument
  from chainer.utils import type_check
label_desc: Use image node_id 3 for calling the RReLU obj's underlying member method code with example usage: obj.forward_cpu(inputs) and returns: y