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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
31 lines
1022 B
Python
31 lines
1022 B
Python
from typing import Any, Dict, List, overload, Tuple, TypeVar
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from torch import Tensor
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from .common_types import _device_t, _devices_t
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T = TypeVar("T", Dict, List, Tuple)
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# For some reason, 'scatter' returns a tuple when given a single Tensor input but a list otherwise.
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@overload
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def scatter(
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inputs: Tensor,
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target_gpus: _devices_t,
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dim: int = ...,
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) -> Tuple[Tensor, ...]: ...
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# flake8 will raise a spurious error here since `torch/__init__.pyi` has not been generated yet
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# so mypy will interpret `Tensor` as `Any` since it is an import from what it believes to be an
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# untyped module. Thus to mypy, the first definition of `scatter` looks strictly more general
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# than this overload.
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@overload
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def scatter(inputs: T, target_gpus: _devices_t, dim: int = ...) -> List[T]: ...
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# TODO More precise types here.
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def scatter_kwargs(
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inputs: Any,
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kwargs: Any,
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target_gpus: _devices_t,
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dim: int = ...,
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) -> Any: ...
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def gather(outputs: Any, target_device: _device_t, dim: int = ...) -> Any: ...
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