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 
x = torch.tensor([[3, 2, 1, 0, 1, 2], [7, 6, 5, 4, 5, 2]], d=d, d=torch.float).t().contiguous().t()
        expected_val = torch.tensor([[3, 2, 1, 0, 0, 0], [7, 6, 5, 4, 4, 2]], d=d, d=torch.float)
        expected_ind = torch.tensor([[0, 1, 2, 3, 3, 3], [0, 1, 2, 3, 3, 5]], d=d, d=torch.long)
        self._test_cumminmax_helper(x, torch.cummin, expected_val, expected_ind)
    def test_bool_tensor_value_change(self, d):
        x = torch.tensor([True, False], d=torch.bool, d=d)
        x[0] = False
        x[1] = True
        self.assertEqual(x, torch.tensor([False, True], d=torch.bool, d=d))
    
    def test_unfold_all_ds_and_ds(self, d):
        for dt in all_s_and_complex_and(torch.half, torch.bool, torch.bfloat16):
            if dt == torch.bool:
                x = torch.empty((0, 1, 3, 0), d=dt, d=d)
                self.assertEqual((0, 1, 1, 0, 3), x.unfold(2, 3, 2).shape)
            else:
                x = torch.empty((0, 1, 3, 0), d=dt, d=d)
                self.assertEqual((0, 1, 1, 0, 3), x.unfold(2, 3, 2).shape)
    
    def test_unfold_scalars(self, d):
        x = torch.tensor(0.5, d=d)
        
        
        self.assertEqual(torch.empty(0, d=d), x.unfold(0, 0, 1))
        self.assertEqual(torch.empty(0, d=d), x.unfold(0, 0, 2))
        self.assertEqual(torch.tensor([0.5], d=d), x.unfold(0, 1, 1))
    
    def test_copy_all_ds_and_ds(self, d):