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
  
  
  class TestReshape(unittest.TestCase):
      out_shape = (2, 2, 6)
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (4, 3, 2)).astype(numpy.float32)
          self.gy = numpy.random.uniform(-1, 1, (2, 2, 6)).astype(numpy.float32)
  
      def check_forward(self, x_data):
          shape = self.out_shape
          x = chainer.Variable(x_data)
          y = functions.reshape(x, shape)
          self.assertEqual(y.data.dtype, numpy.float32)
          self.assertTrue((self.x.reshape(shape) == cuda.to_cpu(y.data)).all())
  
      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, y_grad):
          gradient_check.check_backward(
              functions.Reshape(self.gy.shape), x_data, y_grad)
  
      def test_backward_cpu(self):
          self.check_backward(self.x, self.gy)
  
      @attr.gpu
      def test_backward_gpu(self):
          self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy))
  
  
  class TestReshapeUnknownDimension(TestReshape):
      out_shape = (2, -1, 6)
  
  
  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(
      {'out_shape': (2, 2, 6)},
      {'out_shape': (2, -1, 6)},
  )
  class TestReshape(unittest.TestCase):
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (4, 3, 2)).astype(numpy.float32)
          self.gy = numpy.random.uniform(-1, 1, (2, 2, 6)).astype(numpy.float32)
  
      def check_forward(self, x_data):
          shape = self.out_shape
          x = chainer.Variable(x_data)
          y = functions.reshape(x, shape)
          self.assertEqual(y.data.dtype, numpy.float32)
          self.assertTrue((self.x.reshape(shape) == cuda.to_cpu(y.data)).all())
  
      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, y_grad):
          gradient_check.check_backward(
              functions.Reshape(self.gy.shape), x_data, y_grad)
  
      def test_backward_cpu(self):
          self.check_backward(self.x, self.gy)
  
      @attr.gpu
      def test_backward_gpu(self):
          self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy))
  
  
  testing.run_module(__name__, __file__)
  
subject: Simplify reshape test