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
  from chainer.testing import condition
  
  
  @testing.parameterize(
      {'shape': (4, 3)},
      {'shape': (4, 3, 2)},
      {'shape': (4,)},
  )
  class TestSquaredError(unittest.TestCase):
  
      def setUp(self):
          self.x0 = numpy.random.uniform(-1, 1, self.shape).astype(numpy.float32)
          self.x1 = numpy.random.uniform(-1, 1, self.shape).astype(numpy.float32)
          self.gy = numpy.random.random(self.shape).astype(numpy.float32)
  
      def check_forward(self, x0_data, x1_data):
          x0 = chainer.Variable(x0_data)
          x1 = chainer.Variable(x1_data)
          loss = functions.squared_error(x0, x1)
          loss_value = cuda.to_cpu(loss.data)
          self.assertEqual(loss_value.dtype, numpy.float32)
          self.assertEqual(loss_value.shape, x0_data.shape)
  
          for i in numpy.ndindex(self.x0.shape):
              # Compute expected value
              loss_expect = (self.x0[i] - self.x1[i]) ** 2
              self.assertAlmostEqual(loss_value[i], loss_expect, places=5)
  
      @condition.retry(3)
      def test_forward_cpu(self):
          self.check_forward(self.x0, self.x1)
  
      @attr.gpu
      @condition.retry(3)
      def test_forward_gpu(self):
          self.check_forward(cuda.to_gpu(self.x0), cuda.to_gpu(self.x1))
  
      def check_backward(self, x0_data, x1_data, y_grad):
          gradient_check.check_backward(
              functions.SquaredError(),
              (x0_data, x1_data), y_grad, eps=1e-2)
  
      @condition.retry(3)
      def test_backward_cpu(self):
          self.check_backward(self.x0, self.x1, self.gy)
  
      @attr.gpu
      @condition.retry(3)
      def test_backward_gpu(self):
          self.check_backward(
              cuda.to_gpu(self.x0), cuda.to_gpu(self.x1), cuda.to_gpu(self.gy))
  
  
  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
  from chainer.testing import condition
  
  
  @testing.parameterize(
      {'shape': (4, 3)},
      {'shape': (4, 3, 2)},
      {'shape': (4,)},
      {'shape': ()},
      {'shape': (1,)},
      {'shape': (1, 1)},
  )
  class TestSquaredError(unittest.TestCase):
  
      def setUp(self):
          self.x0 = numpy.random.uniform(-1, 1, self.shape).astype(numpy.float32)
          self.x1 = numpy.random.uniform(-1, 1, self.shape).astype(numpy.float32)
          self.gy = numpy.random.random(self.shape).astype(numpy.float32)
  
      def check_forward(self, x0_data, x1_data):
          x0 = chainer.Variable(x0_data)
          x1 = chainer.Variable(x1_data)
          loss = functions.squared_error(x0, x1)
          loss_value = cuda.to_cpu(loss.data)
          self.assertEqual(loss_value.dtype, numpy.float32)
          self.assertEqual(loss_value.shape, x0_data.shape)
  
          for i in numpy.ndindex(self.x0.shape):
              # Compute expected value
              loss_expect = (self.x0[i] - self.x1[i]) ** 2
              self.assertAlmostEqual(loss_value[i], loss_expect, places=5)
  
      @condition.retry(3)
      def test_forward_cpu(self):
          self.check_forward(self.x0, self.x1)
  
      @attr.gpu
      @condition.retry(3)
      def test_forward_gpu(self):
          self.check_forward(cuda.to_gpu(self.x0), cuda.to_gpu(self.x1))
  
      def check_backward(self, x0_data, x1_data, y_grad):
          gradient_check.check_backward(
              functions.SquaredError(),
              (x0_data, x1_data), y_grad, eps=1e-2)
  
      @condition.retry(3)
      def test_backward_cpu(self):
          self.check_backward(self.x0, self.x1, self.gy)
  
      @attr.gpu
      @condition.retry(3)
      def test_backward_gpu(self):
          self.check_backward(
              cuda.to_gpu(self.x0), cuda.to_gpu(self.x1), cuda.to_gpu(self.gy))
  
  
  testing.run_module(__name__, __file__)
  
subject: add tests