self.assertEqual(t._version, old_version + 1)
@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
+ # Note: fails sometimes on the CI, passes on dual gfx906
@skipIfRocm
def test_broadcast_coalesced(self):
numel = 5
self.assertEqual(t._version, old_version + 1)
@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
- @skipIfRocm
def test_reduce_add_coalesced(self):
numel = 5
num_bytes = numel * 8
def test_scatter_gpu(self):
self._test_scatter(torch.randn(4, 4).cuda(), dim=0)
+ # Note: This test fails on ROCm CI gfx900 but passes on gfx906
@skipIfRocm
def test_scatter_gpu_dim(self):
self._test_scatter(torch.randn(4, 4).cuda(), dim=1)
self.assertTrue("torch.cuda.Event" in e.__repr__())
@unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
+ # Note: fails sometimes on the CI, passes on dual gfx906
@skipIfRocm
def test_stream_context(self):
s0 = torch.cuda.current_stream()
self.assertTrue(s1.query())
@unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
- @skipIfRocm
def test_streams_multi_gpu_eq(self):
d0 = torch.device('cuda:0')
d1 = torch.device('cuda:1')
self.assertEqual(t.cpu().bincount(), t.bincount())
self.assertEqual(t.cpu().bincount(w_cpu), t.bincount(w))
- @skipIfRocm
def test_histc_cuda(self):
_TestTorchMixin._test_histc(self, device='cuda')
a = torch.ones(65536).cuda().half()
self.assertEqual(a.norm(p=0, dtype=torch.float32), 65536)
+ # Note: This test fails on ROCm CI gfx900 but passes on gfx906
@skipIfRocm
# Test that wrap_with_cuda_memory_check successfully detects leak
def test_cuda_memory_leak_detection(self):