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 
torch.nn.functional.multilabel_margin_loss(input, target, reduction='none').shape)
                    self.assertEqual((), torch.nn.functional.multilabel_margin_loss(input, target, reduction='mean').shape)
                    self.assertEqual((), torch.nn.functional.multilabel_margin_loss(input, target, reduction='sum').shape)
                else:
                    self.assertRaises(RuntimeError,
                                      lambda: torch.nn.functional.multilabel_margin_loss(input, target, reduction='none'))
                    self.assertRaises(RuntimeError,
                                      lambda: torch.nn.functional.multilabel_margin_loss(input, target, reduction='mean'))
                    self.assertRaises(RuntimeError,
                                      lambda: torch.nn.functional.multilabel_margin_loss(input, target, reduction='sum'))
        
        for input in (zero_d, one_d, torch.randn(1, 1, d=d)):
            for target in (torch.tensor(0, d=d), torch.tensor([0], d=d)):
                self.assertEqual(target.shape, torch.nn.functional.multi_margin_loss(input, target, reduction='none').shape)
                self.assertEqual((), torch.nn.functional.multi_margin_loss(input, target, reduction='mean').shape)
                self.assertEqual((), torch.nn.functional.multi_margin_loss(input, target, reduction='sum').shape)
    
    def test_check_tensor_all(self, d):
        default_message = 'Expected cond to be True'
        check_fn = torch._check_tensor_all
        expected_error = RuntimeError
        
        with self.assertRaisesRegex(TypeError, 'cond must be a tensor'):
            check_fn(True)
        
        with self.assertRaisesRegex(TypeError, 'cond tensor must have d torch.bool'):
            check_fn(torch.ones(1, d=d))
        test_sizes = [
            (),
            (1,),