def test_mapper1_case_2(self):
arc_map = k2host.IntArray1(torch.IntTensor([2, 0, 3]))
mapper = k2host.AuxLabels1Mapper(self.aux_labels_in, arc_map)
aux_size = k2host.IntArray2Size()
mapper.get_sizes(aux_size)
labels_out = k2host.AuxLabels.create_array_with_size(aux_size)
mapper.get_output(labels_out)
self.assertEqual(aux_size.size1, 3)
self.assertEqual(aux_size.size2, 5)
expected_indexes = torch.IntTensor([0, 3, 4, 5])
expected_data = torch.IntTensor([4, 5, 6, 1, 7])
self.assertTrue(torch.equal(labels_out.indexes, expected_indexes))
self.assertTrue(torch.equal(labels_out.data, expected_data))
def test_int_array1(self):
data = torch.arange(10).to(torch.int32)
array = k2host.IntArray1(data)
self.assertFalse(array.empty())
self.assertIsInstance(array, k2host.IntArray1)
self.assertEqual(data.numel(), array.size)
self.assertEqual(array.data[9], 9)
# the underlying memory is shared between k2host and torch;
# so change one will change another
data[0] = 100
self.assertEqual(array.data[0], 100)
self.assertEqual(array.get_data(0), 100)
del data
# the array in k2host is still accessible
self.assertEqual(array.data[0], 100)
self.assertEqual(array.get_data(0), 100)