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torch.cuda.memory_allocated to return {} if not initialized #51179

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torch.cuda.memory_allocated to return {} if not initialized #51179

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d9666fb
torch.cuda.memory_allocated to return `{}` if not initialized
malfet Jan 27, 2021
7e0d818
Add handling for torch.cuda.device as an argument
malfet Jan 27, 2021
8f3a3b0
Added test that verifies torch.cuda.memory_allocated works with torch…
malfet Jan 27, 2021
63bc8ec
Update test
malfet Jan 28, 2021
776ed5c
Move the test to TestCuda vs TestCudaComm class
malfet Jan 28, 2021
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9 changes: 9 additions & 0 deletions test/test_cuda.py
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Expand Up @@ -3496,6 +3496,15 @@ class TestNamedTupleInput_1(NamedTuple):
self.assertEqual(expected_a, x.a)
self.assertEqual(expected_b, x.b)

@unittest.skipIf(not TEST_MULTIGPU, "Test needs multiple GPUs")
def test_cuda_device_memory_allocated(self):
from torch.cuda import memory_allocated
device_count = torch.cuda.device_count()
current_alloc = [memory_allocated(idx) for idx in range(device_count)]
x = torch.ones(10, device="cuda:0")
self.assertTrue(torch.cuda.memory_allocated(0) > current_alloc[0])
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self.assertTrue(all(memory_allocated(torch.cuda.device(idx)) == current_alloc[idx] for idx in range(1, device_count)))


if __name__ == '__main__':
run_tests()