Platforms: linux

This test was disabled because it is failing on master ([recent examples](http://torch-ci.com/failure/test_torch.py%3A%3ATestTorch%3A%3Atest_equal)).

The cause seems to point to https://github.com/pytorch/pytorch/pull/100024 (or D45282119 as it was landed internally)

cc @mruberry @houseroad @ezyang 
with self.assertRaisesRegex(RuntimeError, "Boolean value of Tensor with no values is ambiguous"):
            torch._assert_async(torch.tensor([]))
        with self.assertRaisesRegex(RuntimeError, "Boolean value of Tensor with more than one value is ambiguous"):
            torch._assert_async(torch.tensor([0, 0]))
        with self.assertRaisesRegex(RuntimeError, "Expected Tensor with single nonzero value, but got zero"):
            torch._assert_async(torch.tensor(0))
        torch._assert_async(torch.tensor(1))
        torch._assert_async(torch.tensor(0.1))
        torch._assert_async(torch.tensor(-0.1))
        with self.assertRaisesRegex(RuntimeError, "Expected Tensor with single nonzero value, but got zero"):
            torch._assert_async(torch.tensor(0.0))
        torch._assert_async(torch.tensor(True))
        with self.assertRaisesRegex(RuntimeError, "Expected Tensor with single nonzero value, but got zero"):
            torch._assert_async(torch.tensor(False))
        torch._assert_async(torch.tensor(0 + 0.1j))
        with self.assertRaisesRegex(RuntimeError, "Expected Tensor with single nonzero value, but got zero"):
            torch._assert_async(torch.tensor(0 + 0j))
    # NB: we must not be built with CUDA; if we are built with CUDA but no CUDA
    # is available, we get a different error.
    @unittest.skipIf(torch.backends.cuda.is_built() or IS_SANDCASTLE, "CUDA is built, can't test CUDA not built error")
    def test_cuda_not_built(self):
        msg = "Torch not compiled with CUDA enabled"
        self.assertRaisesRegex(AssertionError, msg, lambda: torch.cuda.current_d())
        self.assertRaisesRegex(AssertionError, msg, lambda: torch.tensor([1], d="cuda"))
        self.assertRaisesRegex(AssertionError, msg, lambda: torch.tensor([1]).cuda())
        self.assertRaisesRegex(TypeError, msg, lambda: torch.cuda.FloatTensor())
        self.assertRaisesRegex(TypeError, msg, lambda: torch.set_default_tensor_(torch.cuda.FloatTensor))
        self.assertRaisesRegex(AssertionError, msg, lambda: torch.tensor([1]).to(d="cuda"))
    def test_has_internal_overlap(self):