Fixes #1607: Allow MultiIndex to have mixed dtypes

[stress-tess]

This PR (Fixes #1607):

• Removes dtype parameter and associated validation that was introduced in PR Closes #1512: Bug in Series methods with MultiIndex #1516. Overrides the __repr__ of Index instead

NOTE:
The dtypes shown below are from Series and are not accurate since it's possible to have a mix of dtypes in Series. This should be investigated further, but I wanted to get this PR up to address the important bug

Output on reproducer for #1607:

>>> df = ak.DataFrame({'a': ak.arange(10, dtype=ak.int64), 'b': ak.arange(10, dtype=ak.uint64)})
>>> df.groupby(['a', 'b']).count()
0  0    1
1  1    1
2  2    1
3  3    1
4  4    1
5  5    1
6  6    1
7  7    1
8  8    1
9  9    1
dtype: int64

Output from reproducer for #1512 (to ensure it's still working):

>>> a = ak.array([1,2,3,2,3,4,5,6,5,4,3,2])
>>> b = ak.array([2,3,2,3,4,5,6,5,4,3,2,1])
>>> df = ak.DataFrame({'a':a, 'b':b})
>>> c = df.groupby(['a','b']).count()

# These all threw type or attribute errors before this PR
>>> c.index
MultiIndex((array([1 2 2 3 3 4 4 5 5 6]), array([2 1 3 2 4 3 5 4 6 5])))

>>> c.sort_values()
1  2    1
2  1    1
3  4    1
4  3    1
   5    1
5  4    1
   6    1
6  5    1
2  3    2
3  2    2
dtype: int64

>>> c.sort_index()
1  2    1
2  1    1
   3    2
3  2    2
   4    1
4  3    1
   5    1
5  4    1
   6    1
6  5    1
dtype: int64

>>> c.locate((ak.array([1, 2, 2, 3, 3, 4, 4, 5, 5, 6]), ak.array([2, 1, 3, 2, 4, 3, 5, 4, 6, 5])))
1  2    1
2  1    1
   3    2
3  2    2
   4    1
4  3    1
   5    1
5  4    1
   6    1
6  5    1
dtype: int64

[Ethan-DeBandi99]

Looks good to me. One comment, but not positive how important it is.

[reuster986]

looks good, thanks!