def test_serialization(self):
a = [torch.randn(5, 5).float() for i in range(2)]
b = [a[i % 2] for i in range(4)]
b += [a[0].storage()]
b += [a[0].storage()[1:4]]
b += [torch.arange(1, 11).int()]
t1 = torch.FloatTensor().set_(a[0].storage()[1:4], 0, (3,), (1,))
t2 = torch.FloatTensor().set_(a[0].storage()[1:4], 0, (3,), (1,))
b += [(t1.storage(), t1.storage(), t2.storage())]
b += [a[0].storage()[0:2]]
for use_name in (False, True):
with tempfile.NamedTemporaryFile() as f:
handle = f if not use_name else f.name
torch.save(b, handle)
f.seek(0)
c = torch.load(handle)
self.assertEqual(b, c, 0)
self.assertTrue(isinstance(c[0], torch.FloatTensor))
self.assertTrue(isinstance(c[1], torch.FloatTensor))
self.assertTrue(isinstance(c[2], torch.FloatTensor))
self.assertTrue(isinstance(c[3], torch.FloatTensor))
self.assertTrue(isinstance(c[4], torch.FloatStorage))
c[0].fill_(10)
self.assertEqual(c[0], c[2], 0)
self.assertEqual(c[4], torch.FloatStorage(25).fill_(10), 0)
c[1].fill_(20)
self.assertEqual(c[1], c[3], 0)
self.assertEqual(c[4], c[5][1:4], 0)
# check that serializing the same storage view object unpickles
# it as one object not two (and vice versa)
views = c[7]
self.assertEqual(views[0]._cdata, views[1]._cdata)
self.assertEqual(views[0], views[2])
self.assertNotEqual(views[0]._cdata, views[2]._cdata)
rootview = c[8]
self.assertEqual(rootview.data_ptr(), c[0].data_ptr())
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