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Update _torch_docs.py to Fix torch.bernoulli() #152104

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Update _torch_docs.py to Fix torch.bernoulli() #152104

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@ILCSFNO ILCSFNO commented Apr 24, 2025

Fixes #152095
@malfet Wondering whether to fix signature that from:

@overload
def bernoulli(input: Tensor, p: _float, *, generator: Optional[Generator] = None) -> Tensor:

to

@overload
def bernoulli(input: Tensor, p: _float, *, generator: Optional[Generator] = None, out: Optional[Tensor] = None) -> Tensor:

Or just merge them two to:

@overload
def bernoulli(input: Tensor, p: _float = None, *, generator: Optional[Generator] = None, out: Optional[Tensor] = None) -> Tensor:

which can cover the original both signatures.

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pytorch-bot bot commented Apr 24, 2025 •
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/152104

Note: Links to docs will display an error until the docs builds have been completed.

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@pytorch-bot pytorch-bot bot added the release notes: python_frontend python frontend release notes category label Apr 24, 2025
ILCSFNO
ILCSFNO commented Apr 24, 2025
View reviewed changes
torch/_torch_docs.py
Comment on lines +1411 to +1412
p (float): should be a scalar containing probabilities to be used
for drawing the binary random number.
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Copy and changed according to:

pytorch/torch/_tensor_docs.py

Lines 840 to 859 in d743a7b

add_docstr_all(
"bernoulli_",
r"""
bernoulli_(p=0.5, *, generator=None) -> Tensor
Fills each location of :attr:`self` with an independent sample from
:math:`\text{Bernoulli}(\texttt{p})`. :attr:`self` can have integral
``dtype``.
:attr:`p` should either be a scalar or tensor containing probabilities to be
used for drawing the binary random number.
If it is a tensor, the :math:`\text{i}^{th}` element of :attr:`self` tensor
will be set to a value sampled from
:math:`\text{Bernoulli}(\texttt{p\_tensor[i]})`. In this case `p` must have
floating point ``dtype``.
See also :meth:`~Tensor.bernoulli` and :func:`torch.bernoulli`
""",
)

@ILCSFNO ILCSFNO mentioned this pull request Apr 24, 2025
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@jerryzh168 jerryzh168 requested a review from malfet April 28, 2025 18:24
@jerryzh168 jerryzh168 added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label Apr 28, 2025
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@malfet malfet Awaiting requested review from malfet

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To fix inconsistency between signature and doc on torch.bernoulli()
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@ILCSFNO @jerryzh168 @pytorchbot