text: import unittest
  
  import numpy
  
  import chainer
  from chainer.backends import cuda
  import chainer.functions as F
  from chainer import testing
  from chainer.testing import attr
  
  
  class UnaryFunctionsTestBase(unittest.TestCase):
  
      def make_data(self):
          raise NotImplementedError
  
      def setUp(self):
          self.eps = 1e-3
          while True:
              self.x, self.gy = self.make_data()
              if (numpy.abs(self.x - numpy.round(self.x)) > self.eps * 10).all():
                  break
  
      def check_forward(self, op, op_xp, x_data):
          x = chainer.Variable(x_data)
          y = op(x)
          self.assertEqual(x.data.dtype, y.data.dtype)
          v = op_xp(x_data)
          testing.assert_allclose(
              v, y.data, atol=1e-7, rtol=1e-7)
  
      def check_forward_cpu(self, op, op_xp):
          self.check_forward(op, op_xp, self.x)
  
      def check_forward_gpu(self, op, op_xp):
          self.check_forward(op, op_xp, cuda.to_gpu(self.x))
  
  
  @testing.parameterize(*testing.product({
      'shape': [(3, 2), ()],
      'dtype': [numpy.float16, numpy.float32, numpy.float64],
  }))
  class TestCeil(UnaryFunctionsTestBase):
  
      def make_data(self):
          x = numpy.random.uniform(-10.0, 10.0, self.shape).astype(self.dtype)
          gy = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype)
          return x, gy
  
      def test_forward_cpu(self):
          self.check_forward_cpu(F.ceil, numpy.ceil)
  
      @attr.gpu
      def test_forward_gpu(self):
          self.check_forward_gpu(F.ceil, cuda.cupy.ceil)
  
  
  testing.run_module(__name__, __file__)
  