new_contents: import random
  import unittest
  
  import numpy
  
  import chainer
  from chainer import cuda
  from chainer import functions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
  
  
  @testing.parameterize(*testing.product({
      'shape': [(3, 2), (5, 6)],
      'dtype': [numpy.float16, numpy.float32, numpy.float64],
  }))
  class TestRReLU(unittest.TestCase):
  
      def setUp(self):
          # Avoid unstability of numeraical grad
          self.x = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype)
          for i in numpy.ndindex(self.shape):
              if -0.05 < self.x[i] < 0.05:
                  self.x[i] = 0.5
          self.gy = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype)
          self.l = random.random()
          self.u = random.random()        
          self.check_forward_options = {}
          self.check_backward_options = {'dtype': numpy.float64}
          if self.dtype == numpy.float16:
              self.check_forward_options = {'atol': 1e-4, 'rtol': 1e-3}
              self.check_backward_options = {
                  'dtype': numpy.float64, 'atol': 5e-4, 'rtol': 5e-3}
  
      def check_forward(self, x_data):
          x = chainer.Variable(x_data)
          y = functions.randomized_leaky_relu(x, l=self.l, u=self.u, train=False)
          self.assertEqual(y.data.dtype, self.dtype)
  
          expected = self.x.copy()
          for i in numpy.ndindex(self.x.shape):
              if self.x[i] < 0:
                  expected[i] *= (self.l+self.u)/2
  
          testing.assert_allclose(
              expected, y.data, **self.check_forward_options)
  
      @condition.retry(3)
      def test_forward_cpu(self):
          self.check_forward(self.x)
  
      @attr.gpu
      @condition.retry(3)
      def test_forward_gpu(self):
          self.check_forward(cuda.to_gpu(self.x))
  
      def check_backward(self, x_data, y_grad):
          gradient_check.check_backward(
              functions.RReLU(self.l, self.u, False), x_data, y_grad,
              **self.check_backward_options)
  
      @condition.retry(10)
      def test_backward_cpu(self):
          self.check_backward(self.x, self.gy)
  
      @attr.gpu
      @condition.retry(10)
      def test_backward_gpu(self):
          self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy))
  
  
  testing.run_module(__name__, __file__)
  
subject: Add test for RReLU