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81e370fc6b
Currently the `bias` attribute of `torch.nn.Linear` (and `Bilinear`) is typed incorrectly, because it relies on the implicit `Module.__getattr__` which types it as `Tensor | Module`. This has two issues: - It hides the fact that `bias` is optional, and can be `None`, which in turn can hide actual bugs on user side. - It blurs the type due to having `Module` in the union, which can require unnecessary `isistance(linear.bias, Tensor)` on user side. This PR types the `bias` attribute explicitly to fix these issues. CC @ezyang @Skylion007 Pull Request resolved: https://github.com/pytorch/pytorch/pull/142326 Approved by: https://github.com/ezyang
27 lines
771 B
Python
27 lines
771 B
Python
"""Miscellaneous utilities to aid with typing."""
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from typing import Optional, TYPE_CHECKING, TypeVar
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# Helper to turn Optional[T] into T when we know None either isn't
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# possible or should trigger an exception.
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T = TypeVar("T")
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# TorchScript cannot handle the type signature of `not_none` at runtime, because it trips
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# over the `Optional[T]`. To allow using `not_none` from inside a TorchScript method/module,
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# we split the implementation, and hide the runtime type information from TorchScript.
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if TYPE_CHECKING:
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def not_none(obj: Optional[T]) -> T:
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...
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else:
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def not_none(obj):
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if obj is None:
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raise TypeError(
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"Invariant encountered: value was None when it should not be"
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)
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return obj
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