Previously, using the import hook with dataclasses resulted in the `__init__` method of the dataclass being checked.
This was undesirable when using `eqx.field(converter=...)`, as the annotation didn't necessarily reflect the argument type.
A typical example was
```python
class Foo(eqx.Module):
x: jax.Array = eqx.field(converter=jnp.ndarray)
Foo(1) # 1 is not an array! But this code is valid.
```
After this change, we instead monkey-patch our checks to happen at the end of the `__init__` of the dataclass -- after conversion has run.
Note that this requires https://github.com/patrick-kidger/equinox/pull/524. Otherwise, Equinox does conversion too late (in `_ModuleMeta.__call__`, after `__init__` has been run).
* 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