Use `typing_extensions.deprecated` for deprecation annotation if possible. Otherwise, add `category=FutureWarning` to `warnings.warn("message")` if the category is missing.
Note that only warnings that their messages contain `[Dd]eprecat(ed|ion)` are updated in this PR.
Resolves#126888
- #126888
This PR is split from PR #126898.
- #126898
------
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127689
Approved by: https://github.com/Skylion007
Use `typing_extensions.deprecated` for deprecation annotation if possible. Otherwise, add `category=FutureWarning` to `warnings.warn("message")` if the category is missing.
Note that only warnings that their messages contain `[Dd]eprecat(ed|ion)` are updated in this PR.
UPDATE: Use `FutureWarning` instead of `DeprecationWarning`.
Resolves#126888
- #126888
Pull Request resolved: https://github.com/pytorch/pytorch/pull/126898
Approved by: https://github.com/albanD
Fixes#91648
As explained in the tracking issue, the incomplete type stubs in `torch/nn/parallel` mask `DataParallel` methods relevant for subclassing and also mask type issues present in the code as well.
One notable change here is the addition of [`allow_redefinition = True`](https://mypy.readthedocs.io/en/stable/config_file.html#confval-allow_redefinition) in `mypy.ini`, which allows for a common pattern:
> Allows variables to be redefined with an arbitrary type, as long as the redefinition is in the same block and nesting level as the original definition.
This is added specifically to allow for the type narrowing of `device_ids` in `torch.nn.parallel.data_parallel.data_parallel` from `Sequence[Union[int, torch.device]]` to `Sequence[int]`.
Other than this, there are various renamings and `type: ignore` comments added to bypass errors that arose from the merging.
@ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/101528
Approved by: https://github.com/ezyang
Summary:
Fixes #{[50510](https://github.com/pytorch/pytorch/issues/50510)}
Allows ```torch.nn.parallel.scatter_gather.gather``` to accept a list of NamedTuples as input and returns a NamedTuple whose elements are tensors. I added the author's fix using the ```is_namedtuple``` function.
While testing this fix, I encountered a deprecation warning instructing me to use ```'cpu'``` instead of ```-1``` to move the outputs to the CPU. However, doing this causes an assertion error in the ```_get_device_index``` function. I solved this by handling the CPU case in the affected ```forward``` function.
rohan-varma
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51104
Reviewed By: albanD
Differential Revision: D26395578
Pulled By: rohan-varma
fbshipit-source-id: 6e98c9ce1d9f1725973c18d24a6554c1bceae465
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/46304
In the case that a single process operates only on one GPU, we can
avoid this scatter and instead replace it with a recursive version of `to`
which transfers the input tensors to the correct device.
The implementation of `_recursive_to` is modeled after `scatter` in https://github.com/pytorch/pytorch/blob/master/torch/nn/parallel/scatter_gather.py, in order to keep parity with the previous conventions (i.e. custom types not having their tensors moved).
ghstack-source-id: 114896677
Test Plan: Added unittest, and CI
Reviewed By: pritamdamania87
Differential Revision: D24296377
fbshipit-source-id: 536242da05ecabfcd36dffe14168b1f2cf58ca1d
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44220
Closes https://github.com/pytorch/pytorch/issues/44009
Currently if a dataloader returns objects created with a
collections.namedtuple, this will incorrectly be cast to a tuple. As a result, if we have data of these types, there can be runtime errors during the forward pass if the module is expecting a named tuple.
Fix this in
`scatter_gather.py` to resolve the issue reported in
https://github.com/pytorch/pytorch/issues/44009
ghstack-source-id: 113423287
Test Plan: CI
Reviewed By: colesbury
Differential Revision: D23536752
fbshipit-source-id: 3838e60162f29ebe424e83e474c4350ae838180b
* Codemod to update our codebase to 0.4 standard
* Update some of the test scri[ts
* remove Variable in test_clip_grad_value
* fix _symbolic_override_wrapper_maker
