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ba48cf6535
See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter. You can review these PRs via: ```bash git diff --ignore-all-space --ignore-blank-lines HEAD~1 ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/129757 Approved by: https://github.com/ezyang
123 lines
4.2 KiB
Python
123 lines
4.2 KiB
Python
# Owner(s): ["module: cuda"]
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import sys
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import unittest
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import torch
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from torch.testing._internal.common_cuda import TEST_CUDA, TEST_MULTIGPU
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from torch.testing._internal.common_utils import (
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NoTest,
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run_tests,
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skipIfRocmVersionLessThan,
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TestCase,
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)
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# NOTE: this needs to be run in a brand new process
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if not TEST_CUDA:
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print("CUDA not available, skipping tests", file=sys.stderr)
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TestCase = NoTest # noqa: F811
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@torch.testing._internal.common_utils.markDynamoStrictTest
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class TestCudaPrimaryCtx(TestCase):
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CTX_ALREADY_CREATED_ERR_MSG = (
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"Tests defined in test_cuda_primary_ctx.py must be run in a process "
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"where CUDA contexts are never created. Use either run_test.py or add "
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"--subprocess to run each test in a different subprocess."
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)
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@skipIfRocmVersionLessThan((4, 4, 21504))
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def setUp(self):
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for device in range(torch.cuda.device_count()):
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# Ensure context has not been created beforehand
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self.assertFalse(
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torch._C._cuda_hasPrimaryContext(device),
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TestCudaPrimaryCtx.CTX_ALREADY_CREATED_ERR_MSG,
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)
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@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
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def test_str_repr(self):
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x = torch.randn(1, device="cuda:1")
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# We should have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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str(x)
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repr(x)
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
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def test_copy(self):
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x = torch.randn(1, device="cuda:1")
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# We should have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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y = torch.randn(1, device="cpu")
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y.copy_(x)
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
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def test_pin_memory(self):
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x = torch.randn(1, device="cuda:1")
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# We should have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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self.assertFalse(x.is_pinned())
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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x = torch.randn(3, device="cpu").pin_memory()
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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self.assertTrue(x.is_pinned())
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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x = torch.randn(3, device="cpu", pin_memory=True)
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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x = torch.zeros(3, device="cpu", pin_memory=True)
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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x = torch.empty(3, device="cpu", pin_memory=True)
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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x = x.pin_memory()
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# We should still have only created context on 'cuda:1'
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self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
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self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
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if __name__ == "__main__":
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run_tests()
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