ASEM000/PyTreeClass: v0.5.0

Changelog PyTreeClass v0.5 Breaking changes Auto generation of `initmethod from type hints is decoupled fromTreeClass`

Alternatives

Use:

1) Preferably decorate with pytreeclass.autoinit with pytreeclass.field as field specifier. as pytreeclass.field has more features (e.g. callbacks, multiple argument kind selection) and the init generation is cached compared to dataclasses. 2) decorate with dataclasses.dataclass with dataclasses.field as field specifier. however : 1) Must set fronzen=False because the __setattr__, __delattr__ is handled by TreeClass 2) Optionally repr=False to be handled by TreeClass 3) Optionally eq=hash=False as it is handled by TreeClass

<div align="center"> <table> <tr> <td> ### Before ```python import jax.tree_util as jtu import pytreeclass as pytc import dataclasses as dc class Tree(pytc.TreeClass): a: int = 1 jtu.tree_leaves(Tree()) # [1] ``` </td> <td> ### After Equivalent behavior when decorating with either: 1) `@pytreeclass.autoinit` 2) `@dataclasses.dataclass` ```python import jax.tree_util as jtu import pytreeclass as pytc @pytc.autoinit class Tree(pytc.TreeClass): a: int = 1 jtu.tree_leaves(Tree()) # [1] ``` </td> <tr> </table> </div>

This change aims to fix the ambiguity of using the dataclass mental model in the following siutations:

1) subclassing. previously, using TreeClass as a base class is equivalent to decorating the class with dataclasses.dataclass, however this is a bit challenging to understand as demonstrated in the next example:

``` python
import pytreeclass as pytc
import dataclasses as dc

class A(pytc.TreeClass):
    def ___init__(self, a:int):
        self.a = a

class B(A):
    ...

```

When instantiating `B(a=...)`, an error will be raised, because using `TreeClass` is equivalent of decorating all classes with `@dataclass`, which synthesize the `__init__` method based on the fields.
Since no fields (e.g. type hinted values) then the synthesized `__init__` method .

The previous code is equivalent to this code.

```python
@dc.dataclass
class A:
    def __init__(self, a:int):
        self.a = a
@dc.dataclass
class B:
    ...
```

2) dataclass_transform does not play nicely with user created __init__ see 1, 2

leafwise_transform is decoupled from TreeClass.

instead decorate the class with pytreeclass.leafwise.