PERF: statically define classes for is_dtype checks
This moves the definition of the functions passed to `_is_dtype_type` from dynamically generated functions is `is_integer_dtype` to top-level functions. I can't run asv right now (https://github.com/pandas-dev/pandas/issues/33315#issuecomment-610329344) but here are some timeits

master

```python
In [2]: t = np.dtype('int64')

In [3]: %timeit pd.api.types.is_integer_dtype(t)
2.22 µs ± 51.6 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
```
This PR

```python
In [3]: %timeit pd.api.types.is_integer_dtype(t)
1.54 µs ± 39.6 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
```
in fact could simply instantiate classes  Nice, I didnt expect `classes` to account for that much overhead.
 > I can't run asv right now ([#33315 (comment)](https://github.com/pandas-dev/pandas/issues/33315#issuecomment-610329344)) but here are some timeits

Hmm don't think that issue is the root of any ASV issues - are you getting any other error messages from the run? Maybe worth opening a dedicated issue Which logic would you move? It seems like `_is_dtype_or_type` requires a callable, and I want to keep the definition of that callable out of e.g. `is_bool_dtype`. @TomAugspurger is this still something you want to merge, or is it superceded by #33400? Probably a non-issue (or less pressing) after #33400 is done. I'll re-run
benchmarks after that's merged.

On Thu, Apr 16, 2020 at 12:23 PM jbrockmendel <notifications@github.com>
wrote:

> @TomAugspurger <https://github.com/TomAugspurger> is this still something
> you want to merge, or is it superceded by #33400
> <https://github.com/pandas-dev/pandas/pull/33400>?
>
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 needs rebase ok with this if we can update to comments. conceptually ok with this if you can update to comments closing as stale