import torch
from 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 common_cuda here,
# because if we do that, the TEST_CUDNN line from 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))

        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))

        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()
