Previously, something like this would not raise an error, as
variadic+broadcast dimensions were stored in a separate namespace to
variadic+nonbroadcast dimensions:
```python
def f(x: Float[Array, "*foo"], y: Float[Array, "#*foo"]):
pass
a, b = ...
assert a.shape == (3, 4)
assert b.shape == (5,)
f(a, b)
```
* Various improvements.
- Added support for functions in symbolic dimensions, e.g. "min(foo,bar)", which were previously disallowed due to the presence of a comma. (#51)
- Added support for adding ignored names to dimensions, e.g. "cols=4". (#76)
* Now works with Python 3.10 A | B union types.
This required quite a lot of refactoring! JAX supports virtual subclass registration (its metaclass is ABCMeta) but NumPy does not, so we have to actually subclass `np.ndarray`.
Simple stuff like __base__ hacking fails due to deallocator conflicts.
- Float32 introduced to replace f32 (etc.)
- Old f32 aliases were previously around for backward-compatibility, but
the code is pretty hideous, and all stakeholders are now on board
through RFC #13.
- Overall feedback was that Int{Sign,Unsign} was too long and not enough
like numpy. Changed to Int, UInt, and Integer.
Patrick Kidger