old_contents: import unittest
  
  import numpy
  
  from chainer.backends import cuda
  from chainer import gradient_check
  from chainer import links
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
  from chainer import utils
  
  
  @testing.parameterize(*testing.product({
      'nobias': [True, False],
      'initialization': ['explicit', 'placeholder']
  }))
  class TestDeformableConvolution2D(unittest.TestCase):
  
      def setUp(self):
          in_channels = 3
          out_channels = 2
          batch_size = 2
          h = 9
          w = 9
  
          ksize = 3
          stride = 2
          pad = 1
          out_h = utils.conv.get_conv_outsize(h, ksize, stride, pad)
          out_w = utils.conv.get_conv_outsize(w, ksize, stride, pad)
  
          self.x = numpy.random.uniform(
              -1, 1, (batch_size, in_channels, h, w)).astype(numpy.float32)
          self.gy = numpy.random.uniform(
              -1, 1,
              (batch_size, out_channels, out_h, out_w)).astype(numpy.float32)
  
          if self.initialization == 'explicit':
              pass
          elif self.initialization == 'placeholder':
              in_channels = None
          self.link = links.DeformableConvolution2D(
              in_channels, out_channels, ksize, stride=stride, pad=pad,
              nobias=self.nobias, offset_nobias=self.nobias)
  
      def check_backward(self, x_data, y_grad):
          if self.nobias:
              params = (self.link.deform_conv.W)
          else:
              params = (self.link.deform_conv.W, self.link.deform_conv.b)
  
          gradient_check.check_backward(
              self.link, x_data,
              y_grad, params,
              eps=2 ** -3, atol=1e-3, rtol=1e-3)
  
      @condition.retry(3)
      def test_backward_cpu(self):
          self.check_backward(self.x, self.gy)
  
      @attr.gpu
      @condition.retry(3)
      def test_backward_gpu(self):
          self.link.to_gpu()
          self.check_backward(cuda.to_gpu(self.x),
                              cuda.to_gpu(self.gy))
  
  
  testing.run_module(__name__, __file__)
  
new_contents: import unittest
  
  import numpy
  
  from chainer.backends import cuda
  from chainer import gradient_check
  from chainer import links
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
  from chainer import utils
  
  
  @testing.parameterize(*testing.product({
      'nobias': [True, False],
      'initialization': ['explicit', 'placeholder']
  }))
  class TestDeformableConvolution2D(unittest.TestCase):
  
      def setUp(self):
          in_channels = 3
          out_channels = 2
          batch_size = 2
          h = 9
          w = 9
  
          ksize = 3
          stride = 2
          pad = 1
          out_h = utils.conv.get_conv_outsize(h, ksize, stride, pad)
          out_w = utils.conv.get_conv_outsize(w, ksize, stride, pad)
  
          self.x = numpy.random.uniform(
              -1, 1, (batch_size, in_channels, h, w)).astype(numpy.float32)
          self.gy = numpy.random.uniform(
              -1, 1,
              (batch_size, out_channels, out_h, out_w)).astype(numpy.float32)
  
          if self.initialization == 'explicit':
              pass
          elif self.initialization == 'placeholder':
              in_channels = None
          self.link = links.DeformableConvolution2D(
              in_channels, out_channels, ksize, stride=stride, pad=pad,
              offset_nobias=self.nobias, deform_nobias=self.nobias)
  
      def check_backward(self, x_data, y_grad):
          if self.nobias:
              params = (self.link.deform_conv.W)
          else:
              params = (self.link.deform_conv.W, self.link.deform_conv.b)
  
          gradient_check.check_backward(
              self.link, x_data,
              y_grad, params,
              eps=2 ** -3, atol=1e-3, rtol=1e-3)
  
      @condition.retry(3)
      def test_backward_cpu(self):
          self.check_backward(self.x, self.gy)
  
      @attr.gpu
      @condition.retry(3)
      def test_backward_gpu(self):
          self.link.to_gpu()
          self.check_backward(cuda.to_gpu(self.x),
                              cuda.to_gpu(self.gy))
  
  
  testing.run_module(__name__, __file__)
  
subject: fix test