PERF: regression in MultiIndex get_loc indexing performance
From our benchmarks (`GetLoc` class in https://github.com/pandas-dev/pandas/blob/master/asv_bench/benchmarks/multiindex_object.py):

```
In [65]: mi_med = pd.MultiIndex.from_product( 
    ...:     [np.arange(1000), np.arange(10), list("A")], names=["one", "two", "three"] 
    ...: ) 

In [66]: %timeit mi_med.get_loc((999, 9, "A"))   
9.58 µs ± 106 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

In [67]: pd.__version__  
Out[67]: '0.25.0'
```

vs

```
In [18]: mi_med = pd.MultiIndex.from_product( 
    ...:     [np.arange(1000), np.arange(10), list("A")], names=["one", "two", "three"] 
    ...: )

In [19]: %timeit mi_med.get_loc((999, 9, "A"))  
34.7 µs ± 454 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)

In [20]: pd.__version__
Out[20]: '0.26.0.dev0+691.g157495696'
```

Not directly sure what recently changed related to MultiIndexes. 
And the benchmark suite is giving a rather broad range: https://github.com/pandas-dev/pandas/compare/2b284543...7c8c8c81 (because the benchmarks were not running for a while I suppose)