How to prepare a data for Cochran-Mantel-Haenszel Test ?

Hi All,
I have got this dataframe:

dt <- readr::read_fwf("
gender age_group diagnosis
male     young    x
female   child    y
female   adult    x
male     old      z")

dt %<>%
  janitor::row_to_names(row_number = 1)

I have watched this and read this:
https://www.youtube.com/watch?v=LUuLGLGI650

https://stackoverflow.com/questions/34750987/3-way-chi-squared-test-in-r

Like a user Tybran in the comment section said:"I think this video misses one very important detail: the difference between a significant effect (in this case the female group) and the a nonsignificant effect (the male group) is not per se a significant difference of itself. So it is important to recognize that with this method, the three-way interaction is not directly tested but instead 2 two-way interactions are descriptively compared".

Because I believe that R can do what SPSS can't, I want to do sort of chi square test for 4x3 table which would be a task for Cochran-Mantel-Haenszel Test I suppose. I prepared my dt dataframe but when I want to do CMH test it errors to:

Error in mantelhaen.test(dt) : if 'x' is not an array, 'y' must be given

or: when I have done:

dt = table(dt)

mantelhaen.test(dt)

Error in mantelhaen.test(df) : sample size in each stratum must be > 1

How to rectify this, please ? In my opinion there are more than 1 level in each variable in my dt dataframe.