old_contents: import unittest
  
  import numpy
  import six
  
  import chainer
  from chainer import cuda
  from chainer import gradient_check
  from chainer.testing import attr
  
  
  if cuda.available:
      cuda.init()
  
  
  class TestAccuracy(unittest.TestCase):
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (10, 3)).astype(numpy.float32)
          self.t = numpy.random.randint(3, size=(10,)).astype(numpy.int32)
  
      def check_forward(self, x_data, t_data):
          x = chainer.Variable(x_data)
          t = chainer.Variable(t_data)
          y = chainer.functions.accuracy(x, t)
  
          count = 0
          for i in six.moves.range(self.t.size):
              pred = self.x[i].argmax()
              if pred == self.t[i]:
                  count += 1
  
          expected = float(count) / self.t.size
          gradient_check.assert_allclose(expected, cuda.to_cpu(y.data))
  
      def test_forward_cpu(self):
          self.check_forward(self.x, self.t)
  
      @attr.gpu
      def test_forward_gpu(self):
          self.check_forward(cuda.to_gpu(self.x), cuda.to_gpu(self.t))
  
new_contents: import unittest
  
  import numpy
  import six
  
  import chainer
  from chainer import cuda
  from chainer import gradient_check
  from chainer.testing import attr
  
  
  if cuda.available:
      cuda.init()
  
  
  class TestAccuracy(unittest.TestCase):
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (10, 3)).astype(numpy.float32)
          self.t = numpy.random.randint(3, size=(10,)).astype(numpy.int32)
  
      def check_forward(self, x_data, t_data):
          x = chainer.Variable(x_data)
          t = chainer.Variable(t_data)
          y = chainer.functions.accuracy(x, t)
          self.assertEqual((), y.data.shape)
  
          count = 0
          for i in six.moves.range(self.t.size):
              pred = self.x[i].argmax()
              if pred == self.t[i]:
                  count += 1
  
          expected = float(count) / self.t.size
          gradient_check.assert_allclose(expected, cuda.to_cpu(y.data))
  
      def test_forward_cpu(self):
          self.check_forward(self.x, self.t)
  
      @attr.gpu
      def test_forward_gpu(self):
          self.check_forward(cuda.to_gpu(self.x), cuda.to_gpu(self.t))
  
subject: Add test fot shape of result of accuracy function