mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/30445 Create distributed and rpc directories under caffe/test for better management of unit tests. Differential Revision: D18702786 fbshipit-source-id: e9daeed0cfb846ef68806f6decfcb57c0e0e3606
113 lines
4.3 KiB
Python
113 lines
4.3 KiB
Python
import torch
|
|
from torch.testing._internal.common_utils import TestCase, run_tests, skipIfRocm
|
|
import unittest
|
|
|
|
# NOTE: this needs to be run in a brand new process
|
|
|
|
# We cannot import TEST_CUDA and TEST_MULTIGPU from torch.testing._internal.common_cuda here,
|
|
# because if we do that, the TEST_CUDNN line from torch.testing._internal.common_cuda will be executed
|
|
# multiple times as well during the execution of this test suite, and it will
|
|
# cause CUDA OOM error on Windows.
|
|
TEST_CUDA = torch.cuda.is_available()
|
|
TEST_MULTIGPU = TEST_CUDA and torch.cuda.device_count() >= 2
|
|
|
|
if not TEST_CUDA:
|
|
print('CUDA not available, skipping tests')
|
|
TestCase = object # 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.")
|
|
|
|
@skipIfRocm
|
|
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()
|