refactor: Stop using deprecated typing classes (#353)

* Use Iterable, Sequence, Hashable, Callable from collections.abc rather than typing
* Use contextlib.AbstractContextManager rather than typing.ContextManager

typing.Iterable, typing.Sequence, typing.Callable and typing.ContextManager are deprecated since Python 3.9. typing.Hashable is not deprecated but it's an alias for collections.abc.Hashable, so it's better to use the latter.

Note that typing.TypeAlias is also deprecated, but only since Python 3.12, in favor of using the type statement. We can only make the change when we drop support for Python 3.10 and 3.11.
---------
Co-authored-by: Valérian Rey <[email protected]>

Author: PierreQuinton

src/torchjd/_autojac/_backward.py

@@ -1,4 +1,4 @@
-from typing import Iterable, Sequence
+from collections.abc import Iterable, Sequence
 
 from torch import Tensor
 

src/torchjd/_autojac/_mtl_backward.py

@@ -1,4 +1,4 @@
-from typing import Iterable, Sequence
+from collections.abc import Iterable, Sequence
 
 from torch import Tensor
 

src/torchjd/_autojac/_transform/_aggregate.py

@@ -1,5 +1,6 @@
 from collections import OrderedDict
-from typing import Hashable, TypeVar
+from collections.abc import Hashable
+from typing import TypeVar
 
 import torch
 from torch import Tensor

src/torchjd/_autojac/_transform/_base.py

@@ -1,7 +1,8 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import Generic, Sequence
+from collections.abc import Sequence
+from typing import Generic
 
 from torch import Tensor
 

src/torchjd/_autojac/_transform/_differentiate.py

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Sequence
+from collections.abc import Sequence
 
 from torch import Tensor
 

src/torchjd/_autojac/_transform/_grad.py

@@ -1,4 +1,4 @@
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 from torch import Tensor

src/torchjd/_autojac/_transform/_jac.py

@@ -1,7 +1,7 @@
 import math
+from collections.abc import Callable, Sequence
 from functools import partial
 from itertools import accumulate
-from typing import Callable, Sequence
 
 import torch
 from torch import Size, Tensor

src/torchjd/_autojac/_transform/_materialize.py

@@ -1,4 +1,4 @@
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 from torch import Tensor

src/torchjd/_autojac/_transform/_ordered_set.py

@@ -1,6 +1,6 @@
 from collections import OrderedDict
-from collections.abc import Set
-from typing import Hashable, Iterable, TypeVar
+from collections.abc import Hashable, Iterable, Set
+from typing import TypeVar
 
 _KeyType = TypeVar("_KeyType", bound=Hashable)
 

src/torchjd/_autojac/_transform/_stack.py

@@ -1,4 +1,4 @@
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 from torch import Tensor