Fix test comparison ops check for scalar overflow (#48597)
Summary:
Test should verify, that all listed conditions throw, not just the first one
Refactor duplicated constants
Use `self.assertTrue()` instead of suppressing flake8 `B015: Pointless Comparison` warning
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48597
Reviewed By: mruberry
Differential Revision: D25222734
Pulled By: malfet
fbshipit-source-id: 7854f755a84f23a1a52dc74402582e34d69ff984
diff --git a/test/test_binary_ufuncs.py b/test/test_binary_ufuncs.py
index beac622..8147f7b 100644
--- a/test/test_binary_ufuncs.py
+++ b/test/test_binary_ufuncs.py
@@ -158,36 +158,64 @@
# TODO: update to work on CUDA, too
@onlyCPU
def test_comparison_ops_check_for_scalar_overflow(self, device):
+ s = 1 << 20
+ t = torch.tensor([1 << 5], dtype=torch.uint8)
with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
- torch.tensor([1 << 5], dtype=torch.uint8) < (1 << 20) # noqa: B015
- (1 << 20) < torch.tensor([1 << 5], dtype=torch.uint8) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) <= (1 << 20) # noqa: B015
- (1 << 20) <= torch.tensor([1 << 5], dtype=torch.uint8) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) > (1 << 20) # noqa: B015
- (1 << 20) > torch.tensor([1 << 5], dtype=torch.uint8) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) >= (1 << 20) # noqa: B015
- (1 << 20) >= torch.tensor([1 << 5], dtype=torch.uint8) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) == (1 << 20) # noqa: B015
- (1 << 20) == torch.tensor([1 << 5], dtype=torch.uint8) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) != (1 << 20) # noqa: B015
- (1 << 20) != torch.tensor([1 << 5], dtype=torch.uint8) # noqa: B015
+ self.assertTrue(t < s)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(s < t)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t <= s)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(s <= t)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t > s)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(s > t)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t >= s)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(s >= t)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t == s)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(s == t)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t != s)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(s != t)
# TODO: update to work on CUDA, too
@onlyCPU
def test_comparison_ops_check_for_zerodim_tensor_overflow(self, device):
+ t1 = torch.tensor([1 << 5], dtype=torch.uint8)
+ t2 = torch.tensor([1 << 30], dtype=torch.int32)
+ ts1 = torch.tensor(1 << 20, dtype=torch.int32)
+ ts2 = torch.tensor(1 << 40, dtype=torch.int64)
with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
- torch.tensor([1 << 5], dtype=torch.uint8) < torch.tensor(1 << 20, dtype=torch.int32) # noqa: B015
- torch.tensor(1 << 40, dtype=torch.int64) < torch.tensor([1 << 30], dtype=torch.int32) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) <= torch.tensor(1 << 20, dtype=torch.int32) # noqa: B015
- torch.tensor(1 << 40, dtype=torch.int64) <= torch.tensor([1 << 30], dtype=torch.int32) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) > torch.tensor(1 << 20, dtype=torch.int32) # noqa: B015
- torch.tensor(1 << 40, dtype=torch.int64) > torch.tensor([1 << 30], dtype=torch.int32) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) >= torch.tensor(1 << 20, dtype=torch.int32) # noqa: B015
- torch.tensor(1 << 40, dtype=torch.int64) >= torch.tensor([1 << 30], dtype=torch.int32) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) == torch.tensor(1 << 20, dtype=torch.int32) # noqa: B015
- torch.tensor(1 << 40, dtype=torch.int64) == torch.tensor([1 << 30], dtype=torch.int32) # noqa: B015
- torch.tensor([1 << 5], dtype=torch.uint8) != torch.tensor(1 << 20, dtype=torch.int32) # noqa: B015
- torch.tensor(1 << 40, dtype=torch.int64) != torch.tensor([1 << 30], dtype=torch.int32) # noqa: B015
+ self.assertTrue(t1 < ts1)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(ts2 < t2)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t1 <= ts1)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(ts2 <= t2)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t1 > ts1)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(ts2 > t2)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t1 >= ts1)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(ts2 >= t2)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t1 == ts1)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(ts2 == t2)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(t1 != ts1)
+ with self.assertRaisesRegex(RuntimeError, 'value cannot be converted to type'):
+ self.assertTrue(ts2 != t2)
# TODO: update to work on CUDA, too
@onlyCPU
