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 
zero_d_ge_0 = torch.rand((), d=d)
        
        self.assertEqual((), torch.normal(zero_d, zero_d_ge_0).shape)
        self.assertEqual((1,), torch.normal(one_d, zero_d_ge_0).shape)
        self.assertEqual((), torch.normal(1, zero_d_ge_0).shape)
        self.assertEqual((), torch.normal(zero_d, 1).shape)
        self.assertEqual((1,), torch.normal(one_d, 1).shape)
        
        
        
        
        
        w = torch.randn(2, 1, 3, 3, d=d).div_(2).requires_grad_()
        self.assertRaises(RuntimeError, lambda: torch.nn.functional.conv2d(zero_d, w, groups=1))
        self.assertRaises(RuntimeError, lambda: torch.nn.functional.conv2d(zero_d, w, groups=2))
        
        self.assertRaises(ValueError, lambda: torch.nn.functional.nll_loss(zero_d, zero_d, reduction='none'))
        self.assertRaises(ValueError, lambda: torch.nn.functional.nll_loss(zero_d, one_d, reduction='none'))
        
        for (input, target) in ((torch.randn(1, 1, d=d), torch.tensor([0], d=d)),
                                (torch.randn(1, 1, 1, 1, d=d), torch.tensor([[[0]]], d=d))):
            self.assertEqual((), torch.nn.functional.nll_loss(input, target, reduction='mean').shape)
            self.assertEqual((), torch.nn.functional.nll_loss(input, target, reduction='sum').shape)
        
        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), torch.tensor([[0]], d=d)):
                if (input.dim() <= 1 and target.dim() <= 1) or (input.dim() == 2 and target.dim() == 2):
                    output_shape = (target.shape[0],) if target.dim() == 2 else ()
                    self.assertEqual(output_shape,