GeezerVison

This is a first part, that should address python#136681.  With this patch
there should be no overhead for function calls if it's signature allows
keyword arguments.

Below are micro-benchmarks for math.fmin(), when only positional
arguments are allowed (as in the main) vs positional-or-keyword.

The missing part is specialization for 1-arg functions, like cmath.sin():
python#136681 (comment)

In the main:

| Benchmark                  | posonly-patch | posorkw-patch         |
|----------------------------|:-------------:|:---------------------:|
| fmin(1.0, 2.0)             | 169 ns        | 170 ns: 1.01x slower  |
| fmin(1.0, 2.0) x   2 times | 913 ns        | 890 ns: 1.03x faster  |
| fmin(1.0, 2.0) x 100 times | 14.7 us       | 14.8 us: 1.01x slower |
| Geometric mean             | (ref)         | 1.00x faster          |

Benchmark hidden because not significant (1): fmin(1.0, 2.0) x  10 times

With the patch:

| Benchmark                  | posonly-ref | posorkw-ref           |
|----------------------------|:-----------:|:---------------------:|
| fmin(1.0, 2.0)             | 177 ns      | 199 ns: 1.12x slower  |
| fmin(1.0, 2.0) x   2 times | 937 ns      | 980 ns: 1.05x slower  |
| fmin(1.0, 2.0) x  10 times | 2.08 us     | 2.25 us: 1.08x slower |
| fmin(1.0, 2.0) x 100 times | 14.8 us     | 16.5 us: 1.12x slower |
| Geometric mean             | (ref)       | 1.09x slower          |

Benchmark code:

```py
import pyperf
from math import fmin

def f(n):
    for _ in range(n):
        fmin(1.0, 2.0)

runner = pyperf.Runner()
runner.bench_func('fmin(1.0, 2.0)', fmin, 1.0, 2.0)
for n in [2, 10, 100]:
    s = f'fmin(1.0, 2.0) x {n:3} times'
    runner.bench_func(s, f, n)
```