Reorganized the two C++ and Python pytree submodules into a subpackage. I think this would be easier to implement the abstract `PyTreeAPI` class with two implementations. And it will be much easier for the user to switch between the two implementations.
Before:
```text
torch
├── utils
│ ├── _pytree.py
│ ├── _cxx_pytree.py
│ ...
...
```
After:
```text
torch
├── utils
│ ├── _pytree
│ │ ├── __init__.py
│ │ └── api
│ │ ├── __init__.py
│ │ ├── cxx.py
│ │ └── python.py
│ ...
...
```
The `torch.utils._pytree` module will import all APIs from `torch.utils._pytree.api.python`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/112278
Approved by: https://github.com/zou3519
ghstack dependencies: #112111
Custom classes that are serialized with pytree are serialized by default with `f”{class.__module__}.{class.__name__}”`. This is a dependency from our serialized program directly into the outer Python environment. If a user moves the class to a different directory, the serialized program will be unable to be loaded. So, we will require users to pass in an FQN if they want to serialize their custom treespec type.
Differential Revision: [D50886366](https://our.internmc.facebook.com/intern/diff/D50886366)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/112428
Approved by: https://github.com/suo
Part of #109684
- #109684
Changes:
- Add new functions `tree_structure`, `tree_leaves`, `tree_map_` and `tree_map_only_` to Python pytree.
- Extract reusable tests for pytree to `TestGenericPytree`.
- Change `treespec_dumps` and `treespec_loads` in C++ pytree to call Python pytree and use JSON string as serialization type.
- Rename `torch.utils.pytree` -> `torch.utils._cxx_pytree`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110395
Approved by: https://github.com/zou3519
