old_contents: 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
  
  
  @testing.parameterize(
      {'axis': 0, 'start': 2, 'out_shape': (3, 2, 4)},
      {'axis': 2, 'start': 0, 'out_shape': (4, 2, 3)},
      {'axis': 1, 'start': 1, 'out_shape': (2, 3, 4)},
      {'axis': -3, 'start': 2, 'out_shape': (3, 2, 4)},
      {'axis': -1, 'start': 0, 'out_shape': (4, 2, 3)},
      {'axis': -2, 'start': -2, 'out_shape': (2, 3, 4)},
  )
  class TestRollaxis(unittest.TestCase):
  
      dtype = numpy.float32
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (2, 3, 4)).astype(self.dtype)
          self.g = numpy.random.uniform(-1, 1, self.out_shape).astype(self.dtype)
  
      def check_forward(self, x_data):
          x = chainer.Variable(x_data)
          y = functions.rollaxis(x, self.axis, self.start)
  
          testing.assert_allclose(y.data, numpy.rollaxis(self.x, self.axis, self.start))
  
      def test_forward_cpu(self):
          self.check_forward(self.x)
  
      @attr.gpu
      def test_forward_cpu(self):
          self.check_forward(cuda.to_gpu(self.x))
  
      def check_backward(self, x_data, g_data):
          gradient_check.check_backward(
              functions.Rollaxis(self.axis, self.start), x_data, g_data)
  
      def test_backward_cpu(self):
          self.check_backward(self.x, self.g)
  
  
  testing.run_module(__name__, __file__)
  
new_contents: 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
  
  
  @testing.parameterize(
      {'axis': 0, 'start': 2, 'out_shape': (3, 2, 4)},
      {'axis': 2, 'start': 0, 'out_shape': (4, 2, 3)},
      {'axis': 1, 'start': 1, 'out_shape': (2, 3, 4)},
      {'axis': -3, 'start': 2, 'out_shape': (3, 2, 4)},
      {'axis': -1, 'start': 0, 'out_shape': (4, 2, 3)},
      {'axis': -2, 'start': -2, 'out_shape': (2, 3, 4)},
  )
  class TestRollaxis(unittest.TestCase):
  
      dtype = numpy.float32
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (2, 3, 4)).astype(self.dtype)
          self.g = numpy.random.uniform(-1, 1, self.out_shape).astype(self.dtype)
  
      def check_forward(self, x_data):
          x = chainer.Variable(x_data)
          y = functions.rollaxis(x, self.axis, self.start)
  
          expect = numpy.rollaxis(self.x, self.axis, self.start)
          testing.assert_allclose(y.data, expect)
  
      def test_forward_cpu(self):
          self.check_forward(self.x)
  
      @attr.gpu
      def test_forward_gpu(self):
          self.check_forward(cuda.to_gpu(self.x))
  
      def check_backward(self, x_data, g_data):
          gradient_check.check_backward(
              functions.Rollaxis(self.axis, self.start), x_data, g_data)
  
      def test_backward_cpu(self):
          self.check_backward(self.x, self.g)
  
      @attr.gpu
      def test_backward_gpu(self):
          self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.g))
  
  
  testing.run_module(__name__, __file__)
  
subject: Fix test