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 
is_inplace = '_(' in inspect.getsource(fn)
                x_clone = x.clone() if is_inplace else x
                x_c_clone = x_c.clone() if is_inplace else x_c
                result_c = fn(x_c_clone, y_c)
                result = fn(x_clone, y)
                self.assertEqual(result, result_c, "Failed for '{}'".format(inspect.getsource(fn).strip()))
                self.assertTrue(
                    result.is_contiguous(memory_format=memory_format),
                    "result of the '{}' is not in '{}' format".format(inspect.getsource(fn).strip(), memory_format))
            for fn in bias_fns:
                result_c = fn(x_c, b_c)
                result = fn(x, bias)
                self.assertEqual(result, result_c, "Failed for '{}'".format(inspect.getsource(fn).strip()))
                self.assertTrue(
                    result.is_contiguous(memory_format=memory_format),
                    "result of the '{}' is not in '{}' format".format(inspect.getsource(fn).strip(), memory_format))
            for fn in return_contig_fns:
                result_c = fn(x_c, y_c)
                result = fn(x, y)
                self.assertEqual(result, result_c, "Failed for '{}'".format(inspect.getsource(fn).strip()))
                self.assertTrue(
                    result.is_contiguous(memory_format=torch.contiguous_format),
                    "result of the '{}' is not in '{}' format".format(inspect.getsource(fn).strip(), torch.contiguous_format))
        _test_helper(
            torch.randn((4, 3, 8, 8), d=d).contiguous(memory_format=torch.channels_last),
            abs(torch.randn((4, 3, 8, 8), d=d)) + 1,
            torch.randn((1, 3, 1, 1), d=d).contiguous(memory_format=torch.channels_last),
            torch.channels_last)
        _test_helper(
            torch.randn((4, 3, 8, 8, 8), d=d).contiguous(memory_format=torch.channels_last_3d),