text: 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(
      {'shape': (3,), 'dtype': 'f', 'axis': 0, 'inv': False},
      {'shape': (3,), 'dtype': 'f', 'axis': -1, 'inv': True},
      {'shape': (3, 4), 'dtype': 'd', 'axis': 1, 'inv': True},
      {'shape': (3, 4, 5), 'dtype': 'f', 'axis': 2, 'inv': False},
  )
  class TestPermutate(unittest.TestCase):
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype)
          self.g = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype)
          self.indices = numpy.random.permutation(
              self.shape[self.axis]).astype(numpy.int32)
  
      def check_forward(self, x_data, ind_data):
          x = chainer.Variable(x_data)
          indices = chainer.Variable(ind_data)
          y = functions.permutate(x, indices, axis=self.axis, inv=self.inv)
  
          y_cpu = cuda.to_cpu(y.data)
          y_cpu = numpy.rollaxis(y_cpu, axis=self.axis)
          x_data = numpy.rollaxis(self.x, axis=self.axis)
          for i, ind in enumerate(self.indices):
              if self.inv:
                  numpy.testing.assert_array_equal(y_cpu[ind], x_data[i])
              else:
                  numpy.testing.assert_array_equal(y_cpu[i], x_data[ind])
  
      def test_forward_cpu(self):
          self.check_forward(self.x, self.indices)
  
      @attr.gpu
      def test_forward_gpu(self):
          self.check_forward(cuda.to_gpu(self.x), cuda.to_gpu(self.indices))
  
      def check_backward(self, x_data, ind_data, g_data):
          fun = functions.Permutate(axis=self.axis, inv=self.inv)
          gradient_check.check_backward(
              fun, (x_data, ind_data), g_data, dtype='d', atol=0.001, rtol=0.001)
  
      def test_backward_cpu(self):
          self.check_backward(self.x, self.indices, self.g)
  
      @attr.gpu
      def test_backward_gpu(self):
          self.check_backward(cuda.to_gpu(self.x),
                              cuda.to_gpu(self.indices),
                              cuda.to_gpu(self.g))
  
  
  @testing.parameterize(
      {'indices': [0, 0]},
      {'indices': [-1, 0]},
      {'indices': [0, 2]},
  )
  class TestPermutateInvalidIndices(unittest.TestCase):
  
      def setUp(self):
          self.x = numpy.arange(10).reshape((2, 5)).astype('f')
          self.ind = numpy.array(self.indices, 'i')
          self.debug = chainer.is_debug()
          chainer.set_debug(True)
  
      def tearDown(self):
          chainer.set_debug(self.debug)
  
      def check_invalid(self, x_data, ind_data):
          x = chainer.Variable(x_data)
          ind = chainer.Variable(ind_data)
          with self.assertRaises(ValueError):
              functions.permutate(x, ind)
  
      def test_invlaid_cpu(self):
          self.check_invalid(self.x, self.ind)
  
      @attr.gpu
      def test_invlaid_gpu(self):
          self.check_invalid(cuda.to_gpu(self.x), cuda.to_gpu(self.ind))
  
  
  testing.run_module(__name__, __file__)
  