Fixes#102768
- Provides proper function declarations in generated `torch/nn/functional.pyi`.
- Moves some functions from manually defined in `functional.pyi.in` to generated code, in order to single-source the signature.
- Includes some of the functions in `torch._C._nn` into its `.pyi.in`, but not exhaustive (only what's already there).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/102918
Approved by: https://github.com/drisspg, https://github.com/malfet
Changes:
- #95200
1. Recognize `.py.in` and `.pyi.in` files as Python in VS Code for a better development experience.
2. Fix deep setting merge in `tools/vscode_settings.py`.
- #95267
3. Use `Namedtuple` rather than `namedtuple + __annotations__` for `torch.nn.utils.rnn.PackedSequence_`:
`namedtuple + __annotations__`:
```python
PackedSequence_ = namedtuple('PackedSequence_',
['data', 'batch_sizes', 'sorted_indices', 'unsorted_indices'])
# type annotation for PackedSequence_ to make it compatible with TorchScript
PackedSequence_.__annotations__ = {'data': torch.Tensor, 'batch_sizes': torch.Tensor,
'sorted_indices': Optional[torch.Tensor],
'unsorted_indices': Optional[torch.Tensor]}
```
`Namedtuple`: Python 3.6+
```python
class PackedSequence_(NamedTuple):
data: torch.Tensor
batch_sizes: torch.Tensor
sorted_indices: Optional[torch.Tensor]
unsorted_indices: Optional[torch.Tensor]
```
- => this PR: #95268
4. Sort import statements and remove unnecessary imports in `.pyi`, `.pyi.in` files.
5. Format `.pyi`, `.pyi.in` files and remove unnecessary ellipsis `...` in type stubs.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95268
Approved by: https://github.com/huydhn
Summary:
Regularize mask handling for attn_mask and key_padding_mask
* Update documentation to remove reference to byte masks (which were deprecated long ago)
* Introduce check and warn about deprecation if attn_mask and key_padding_mask types mismatch
* Convert all masks to float before combining
* Combine by adding
Test Plan: sandcastle & github CI
Differential Revision: D42653215
Pull Request resolved: https://github.com/pytorch/pytorch/pull/92733
Approved by: https://github.com/ngimel, https://github.com/drisspg
Summary: Introduce causal mask
This PR introduces a causal mask option _causal_mask (as well as causal mask detection if attn_mask is provided), since current custom kernels do not support arbitrary masks.
Test Plan: sandcastle & github ci/cd
Differential Revision: D41723137
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90508
Approved by: https://github.com/albanD
Summary:
Original commit changeset: 4ce347cb0f30
Original Phabricator Diff: D34043182 (8315c9b885)
Test Plan: It's a backout of a backout
Reviewed By: pbelevich, jaceyca
Differential Revision: D34060843
fbshipit-source-id: 6aaf62ce74330cbf142ab483b2a31eccba775ca9
(cherry picked from commit 046b1dbb72)
Summary:
This PR adds a `padding_idx` parameter to `nn.EmbeddingBag` and `nn.functional.embedding_bag`. As with `nn.Embedding`'s `padding_idx` argument, if an embedding's index is equal to `padding_idx` it is ignored, so it is not included in the reduction.
This PR does not add support for `padding_idx` for quantized or ONNX `EmbeddingBag` for opset10/11 (opset9 is supported). In these cases, an error is thrown if `padding_idx` is provided.
Fixes https://github.com/pytorch/pytorch/issues/3194
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49237
Reviewed By: walterddr, VitalyFedyunin
Differential Revision: D26948258
Pulled By: jbschlosser
fbshipit-source-id: 3ca672f7e768941f3261ab405fc7597c97ce3dfc
Summary:
Fixes https://github.com/pytorch/pytorch/issues/49034
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49035
Test Plan:
Imported from GitHub, without a `Test Plan:` line.
Force rebased to deal with merge conflicts
Reviewed By: zhangguanheng66
Differential Revision: D25767065
Pulled By: walterddr
fbshipit-source-id: ffb904e449f137825824e3f43f3775a55e9b011b
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/43680
As discussed [here](https://github.com/pytorch/pytorch/issues/43342),
adding in a Python-only implementation of the triplet-margin loss that takes a
custom distance function. Still discussing whether this is necessary to add to
PyTorch Core.
Test Plan:
python test/run_tests.py
Imported from OSS
Reviewed By: albanD
Differential Revision: D23363898
fbshipit-source-id: 1cafc05abecdbe7812b41deaa1e50ea11239d0cb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38157
This removes the error prone process of assembling `torch/__init__.pyi`
(and frequently forgetting to expose things), since now we can simply
rely on the true source file to get things done. Most of the old
codegen in gen_pyi.py is now rerouted to various files:
- `torch/_C/__init__.pyi` (the dumping pile of all misc bindings)
- `torch/_C/_nn.pyi` (NN function bindings)
- `torch/_C/_VariableFunctions.pyi` (torch function bindings)
`torch.types` grew a bunch more definitions that previously where
defined in `torch/__init__.pyi`
Some miscellaneous changes
- Fixed a bug where we treat single TensorList argument as implying
varargs are accepted. This is actually only supported on IntList.
This means we can correctly generate a stub for dequantize.
- Add missing manual stub for nonzero
- Switched torch/onnx/operators.py to directly refer to _C module,
since apparently mypy doesn't think that methods prefixed with
underscores get reexported. This may be a recurring theme; maybe
we need to find a better way to solve it.
Because I was really lazy, I dumped namedtuple definitions in both
`torch._C` and `torch._C._VariableFunctions`. This is definitely wrong.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Differential Revision: D21497400
Pulled By: ezyang
fbshipit-source-id: 07b126141c82efaca37be27c07255cb2b9b3f064
