old_contents: import unittest
  
  import numpy
  
  import cupy
  from cupy import testing
  
  
  @unittest.skipUnless(
      cusolver_enabled, 'Only cusolver in CUDA 8.0 is supported')
  @testing.gpu
  class TestEigenvalue(unittest.TestCase):
  
      _multiprocess_can_split_ = True
  
      @testing.for_all_dtypes(no_float16=True)
      @testing.numpy_cupy_allclose(rtol=1e-3, atol=1e-4)
      def test_eigh(self, xp, dtype):
          a = xp.array([[1, 0, 3], [0, 5, 0], [3, 0, 5]], dtype)
          w, v = xp.linalg.eigh(a)
  
          # Order of eigen values is not defined.
          # They must be sorted to compare them.
          if xp is numpy:
              inds = numpy.argsort(w)
          else:
              inds = cupy.array(numpy.argsort(w.get()))
          w = w[inds]
          v = v[inds]
          return xp.concatenate([w[None], v])
  
      def test_eigh_float16(self):
          # NumPy's eigh deos not support float16
          a = cupy.array([[1, 0, 3], [0, 5, 0], [3, 0, 5]], 'e')
          w, v = cupy.linalg.eigh(a)
  
          self.assertEqual(w.dtype, numpy.float16)
          self.assertEqual(v.dtype, numpy.float16)
  
          a = a.astype('d')
          w = w.astype('d')
          v = v.astype('d')
  
          testing.assert_allclose(a.dot(v), w * v, rtol=1e-3, atol=1e-4)
  
      @testing.for_all_dtypes(no_float16=True)
      @testing.numpy_cupy_allclose(rtol=1e-3, atol=1e-4)
      def test_eigvals(self, xp, dtype):
          a = xp.array([[1, 0, 3], [0, 5, 0], [3, 0, 5]], dtype)
          w = xp.linalg.eigvals(a)
  
          # Order of eigen values is not defined.
          # They must be sorted to compare them.
          if xp is numpy:
              inds = numpy.argsort(w)
          else:
              inds = cupy.array(numpy.argsort(w.get()))
          w = w[inds]
          return w
  
new_contents: import unittest
  
  import numpy
  
  import cupy
  from cupy import cuda
  from cupy import testing
  
  
  @unittest.skipUnless(
      cuda.cusolver_enabled, 'Only cusolver in CUDA 8.0 is supported')
  @testing.gpu
  class TestEigenvalue(unittest.TestCase):
  
      _multiprocess_can_split_ = True
  
      @testing.for_all_dtypes(no_float16=True)
      @testing.numpy_cupy_allclose(rtol=1e-3, atol=1e-4)
      def test_eigh(self, xp, dtype):
          a = xp.array([[1, 0, 3], [0, 5, 0], [3, 0, 5]], dtype)
          w, v = xp.linalg.eigh(a)
  
          # Order of eigen values is not defined.
          # They must be sorted to compare them.
          if xp is numpy:
              inds = numpy.argsort(w)
          else:
              inds = cupy.array(numpy.argsort(w.get()))
          w = w[inds]
          v = v[inds]
          return xp.concatenate([w[None], v])
  
      def test_eigh_float16(self):
          # NumPy's eigh deos not support float16
          a = cupy.array([[1, 0, 3], [0, 5, 0], [3, 0, 5]], 'e')
          w, v = cupy.linalg.eigh(a)
  
          self.assertEqual(w.dtype, numpy.float16)
          self.assertEqual(v.dtype, numpy.float16)
  
          a = a.astype('d')
          w = w.astype('d')
          v = v.astype('d')
  
          testing.assert_allclose(a.dot(v), w * v, rtol=1e-3, atol=1e-4)
  
      @testing.for_all_dtypes(no_float16=True)
      @testing.numpy_cupy_allclose(rtol=1e-3, atol=1e-4)
      def test_eigvals(self, xp, dtype):
          a = xp.array([[1, 0, 3], [0, 5, 0], [3, 0, 5]], dtype)
          w = xp.linalg.eigvals(a)
  
          # Order of eigen values is not defined.
          # They must be sorted to compare them.
          if xp is numpy:
              inds = numpy.argsort(w)
          else:
              inds = cupy.array(numpy.argsort(w.get()))
          w = w[inds]
          return w
  
subject: Fix typo