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 
if d.is_floating_point or d.is_complex:
                return torch.rand(size=size, d=d, d=d)
            if d == torch.uint8:
                return torch.randint(1, 5, size=size, d=d, d=d)
            else:
                return torch.randint(-5, 5, size=size, d=d, d=d)
        a = rand_tensor((2, 2), d=d, d=d)
        b = rand_tensor((2, 2), d=d, d=d)
        c = rand_tensor((2, 2), d=d, d=d)
        alpha = _number(0.5, 3, d)
        actual = torch.addcmul(a, b, c, value=alpha)
        expected = a + alpha * b * c
        self.assertEqual(expected, actual)
        with self.assertWarnsOnceRegex(
                UserWarning, "This overload of addcmul is deprecated"):
            self.assertEqual(actual, torch.addcmul(a, alpha, b, c))
        if self.d_ == 'cuda' and d == torch.half:
            a = torch.tensor([60000.0], d=d, d=d)
            b = torch.tensor([60000.0], d=d, d=d)
            c = torch.tensor([2.0], d=d, d=d)
            out = torch.addcmul(a, b, c, value=-1)
            self.assertTrue(not (out.isnan() or out.isinf()))
    
    def test_narrow_empty(self, d):