mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
cd05c3b98c
Comment about `TEST_CUDNN` called over and over has long been alleviated by wrapping the check with `LazyVal`, that caches the results. Also, delete unused `TEST_MAGMA`. Prep change for https://github.com/pytorch/pytorch/issues/100006 <!-- copilot:poem --> ### <samp>🤖 Generated by Copilot at e3a5b39</samp> > _`common_cuda.py`_ > _Refactored for dynamo tests_ > _Winter code cleanup_ Pull Request resolved: https://github.com/pytorch/pytorch/pull/103982 Approved by: https://github.com/atalman, https://github.com/janeyx99
110 lines
4.1 KiB
Python
110 lines
4.1 KiB
Python
# Owner(s): ["module: cuda"]
|
|
|
|
import torch
|
|
from torch.testing._internal.common_utils import TestCase, run_tests, skipIfRocmVersionLessThan, NoTest
|
|
from torch.testing._internal.common_cuda import TEST_CUDA, TEST_MULTIGPU
|
|
import sys
|
|
import unittest
|
|
|
|
# NOTE: this needs to be run in a brand new process
|
|
|
|
if not TEST_CUDA:
|
|
print('CUDA not available, skipping tests', file=sys.stderr)
|
|
TestCase = NoTest # noqa: F811
|
|
|
|
|
|
class TestCudaPrimaryCtx(TestCase):
|
|
CTX_ALREADY_CREATED_ERR_MSG = (
|
|
"Tests defined in test_cuda_primary_ctx.py must be run in a process "
|
|
"where CUDA contexts are never created. Use either run_test.py or add "
|
|
"--subprocess to run each test in a different subprocess.")
|
|
|
|
@skipIfRocmVersionLessThan((4, 4, 21504))
|
|
def setUp(self):
|
|
for device in range(torch.cuda.device_count()):
|
|
# Ensure context has not been created beforehand
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(device), TestCudaPrimaryCtx.CTX_ALREADY_CREATED_ERR_MSG)
|
|
|
|
@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
|
|
def test_str_repr(self):
|
|
x = torch.randn(1, device='cuda:1')
|
|
|
|
# We should have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
str(x)
|
|
repr(x)
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
|
|
def test_copy(self):
|
|
x = torch.randn(1, device='cuda:1')
|
|
|
|
# We should have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
y = torch.randn(1, device='cpu')
|
|
y.copy_(x)
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
@unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
|
|
def test_pin_memory(self):
|
|
x = torch.randn(1, device='cuda:1')
|
|
|
|
# We should have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
self.assertFalse(x.is_pinned())
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
x = torch.randn(3, device='cpu').pin_memory()
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
self.assertTrue(x.is_pinned())
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
x = torch.randn(3, device='cpu', pin_memory=True)
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
x = torch.zeros(3, device='cpu', pin_memory=True)
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
x = torch.empty(3, device='cpu', pin_memory=True)
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
x = x.pin_memory()
|
|
|
|
# We should still have only created context on 'cuda:1'
|
|
self.assertFalse(torch._C._cuda_hasPrimaryContext(0))
|
|
self.assertTrue(torch._C._cuda_hasPrimaryContext(1))
|
|
|
|
if __name__ == '__main__':
|
|
run_tests()
|