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981 Commits

Author SHA1 Message Date
zeshengzong
67355a1289 [Easy] Add torch.range, torch.arange params optional description (#143731) 
Fixes #129333

**Test Result**

**Before**

![image](https://github.com/user-attachments/assets/c5873690-7de7-4a14-9423-a150d17d137e)

![image](https://github.com/user-attachments/assets/ff4ee545-f27a-403b-bf92-51f9571022a3)

**After**

![image](https://github.com/user-attachments/assets/34e2c41f-8b54-417d-bb10-7ca6f679206a)

![image](https://github.com/user-attachments/assets/b54bcebd-70e9-4a1a-8a22-1ab815e17827)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/143731
Approved by: https://github.com/janeyx99
 2024-12-24 01:29:24 +00:00
zeshengzong
a70191da41 Add torch.topk indices vary description (#143736) 
Fixes #133542

**Test Result**

**Before**

![image](https://github.com/user-attachments/assets/65227efb-02af-45e7-804c-35588dff360d)

**After**

![image](https://github.com/user-attachments/assets/91f1f53f-008c-4784-82fe-013404e273cb)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/143736
Approved by: https://github.com/zou3519
 2024-12-23 17:16:31 +00:00
zeshengzong
12098ad242 Add torch.cat tensors type promotion description (#141339) 
Fixes #126964

Add note description about type promotion of `torch.cat`

**Test Result**

**Before**
![image](https://github.com/user-attachments/assets/2449f11b-48ed-406e-b73e-6d00f8eadb00)

**After**
![image](https://github.com/user-attachments/assets/cba99572-e8b1-4b9c-ba95-a963b54859ba)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/141339
Approved by: https://github.com/albanD
 2024-12-14 01:36:41 +00:00
Paden Milligan
07edb2ec4d Update documentation for torch.mean() to note behavior with empty tensors (#142039) 
This PR updates the documentation for `torch.mean()` to explicitly mention that computing the mean over an empty tensor returns `nan`. This clarification helps users understand the behavior and handle it appropriately in their code.

Fixes #141057

Pull Request resolved: https://github.com/pytorch/pytorch/pull/142039
Approved by: https://github.com/albanD
 2024-12-05 17:21:53 +00:00
axel
763038db66 Clarify torch.arange floating-point rounding behavior (#141655) 
Added documentation note clarifying the rounding behavior of `torch.arange` when using floating-point dtypes, particularly for reduced precision types like `bfloat16`. This helps users understand potential issues like repeated values and provides guidance on using integer dtypes for precise sequences.

## Changes
- Added explanatory note about floating-point rounding behavior and its effects
- Included specific mention of `bfloat16` dtype issues
- Added recommendation to use integer dtypes for precise sequences

Fixes [#137774](https://github.com/pytorch/pytorch/issues/137774)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/141655
Approved by: https://github.com/cpuhrsch
 2024-11-27 09:31:39 +00:00
Arthur Feeney
0c587c324d DOC: Correct torch.trapezoid docstring (#141459) 
This is super duper minor, but I believe this corrects a typo in the documentation of `torch.trapezoid`.

The documentation says the input is a 1-dimensional tensor $y_0, \dots, y_n$, but it uses summations going from 1 to n-1. Since it's summing over terms $y_i - y_{i-1}$, stopping at n-1 excludes the last partition $y_n - y_{n-1}$, which doesn't match the implementation...

```python
# (just showing it does include $y_n - y_{n-1}$)
torch.trapezoid([0, 0, 9999]) == 9999 / 2
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/141459
Approved by: https://github.com/colesbury
 2024-11-27 01:54:14 +00:00
Diego Sandoval
4fb4aa3e70 Updated docstrings referring to torch.expand to point to torch.Tensor.expand (#140045) 
`torch.expand` was moved to `torch.Tensor.expand` but some docstrings still refer to `torch.expand`

Pull Request resolved: https://github.com/pytorch/pytorch/pull/140045
Approved by: https://github.com/mikaylagawarecki
 2024-11-21 20:13:41 +00:00
zeshengzong
8f3c71ad27 Add torch.sum dtype promotion description (#140939) 
Fixes #82159

Add note description about type promotion of `torch.sum`.

**Test Result**

**Before**
![image](https://github.com/user-attachments/assets/fb952676-f190-4680-9e15-ea8c99d33c67)

**After**
![image](https://github.com/user-attachments/assets/ee0d46a6-5053-46d5-b412-5c919a40965a)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/140939
Approved by: https://github.com/zou3519
 2024-11-20 06:20:01 +00:00
zeshengzong
7167323644 Fix type description of torch.chunk (#140089) 
Fixes #126278

- Change return type description of `torch.chunk` to tuple
- Add type for input parameters

**Before**
![image](https://github.com/user-attachments/assets/087b6cfa-0815-443b-a69a-785ca4b421d7)

**After**
![image](https://github.com/user-attachments/assets/19532553-6004-4246-a6cf-f7f685f5775c)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/140089
Approved by: https://github.com/awgu
 2024-11-08 15:21:13 +00:00
zeshengzong
ff616c26fb Optimize isclose description (#139724) 
Fixes #139563

Make description user friendly.

After Change:

![image](https://github.com/user-attachments/assets/88a805c0-0105-4441-812b-582c09abc72b)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/139724
Approved by: https://github.com/janeyx99
 2024-11-06 19:30:44 +00:00
David Berard
aec179e2be Fix docs for logcumsumexp formula (#139768) 
The previous formula was wrong and reused some indexing variables.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/139768
Approved by: https://github.com/janeyx99
 2024-11-06 01:19:09 +00:00
vladimirrotariu
7d644f025f make equation behind torch.isclose element-wise (#138459) 
The current formula behind torch.isclose, according to the docs, is
![imagen](https://github.com/user-attachments/assets/6b79f6d8-e675-4585-b26b-0c6933f7ecdd)

However, torch.isclose acts element-wise, so this formula may be misleading at first, given that the docs said that `input` and `other` are the first, respectively second tensor to compare. I propose the following change, to stress the element-wise nature of the norms in the equation:
![imagen](https://github.com/user-attachments/assets/2926a1c6-c4fa-4c48-8874-106521d3f54c)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/138459
Approved by: https://github.com/soulitzer
 2024-11-01 18:18:33 +00:00
zeshengzong
7b863230ea [Docs] Optimize parameter description to declare allowed type (2/N) (#138152) 
Inspired by issue #137422 and #103847

Optimize method parameter types in docs to given users a more clear about what expected to pass to methods.

Previous PR:
- [x] https://github.com/pytorch/pytorch/pull/137956

Pull Request resolved: https://github.com/pytorch/pytorch/pull/138152
Approved by: https://github.com/albanD
 2024-10-18 11:18:19 +00:00
zeshengzong
b4f7f4bf49 [Docs] Optimize parameter description to declare allowed type (1/N) (#137956) 
Inspired by issue #137422 and #103847

Optimize method parameter types in docs to given users a more clear about what expected to pass to methods.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/137956
Approved by: https://github.com/albanD
 2024-10-17 01:19:55 +00:00
zeshengzong
abb00efc14 Add torch.squeeze parameter description to declare allowed type (#137485) 
Fixes #137422

Add parameter type definition in API docs to clarify allowed value type, eliminate users pass `None`  as `dim` value directly.

```python
>>> import torch
>>> x = torch.randn(3,1,2)
>>> x.squeeze(dim=None)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
RuntimeError: Please look up dimensions by name, got: name = None.
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/137485
Approved by: https://github.com/albanD
 2024-10-09 05:29:13 +00:00
Nikita Shulga
4830bd0dd4 [Doc] Clarify that NaNs are not equal to each other (#137386) 
Fixes https://github.com/pytorch/pytorch/issues/137337

Pull Request resolved: https://github.com/pytorch/pytorch/pull/137386
Approved by: https://github.com/janeyx99, https://github.com/huydhn, https://github.com/kit1980
 2024-10-05 06:19:12 +00:00
PyTorch MergeBot
e9d2765ec8 Revert "Add deterministic path for CUDA cumsum (#136224)" 
This reverts commit d1bb8e828f.

Reverted https://github.com/pytorch/pytorch/pull/136224 on behalf of https://github.com/atalman due to Break internal CI ([comment](https://github.com/pytorch/pytorch/pull/136224#issuecomment-2379214226))
 2024-09-27 12:54:47 +00:00
Kurt Mohler
d1bb8e828f Add deterministic path for CUDA cumsum (#136224) 
Change `cumsum` to call its decomposition when `use_deterministic_algorithms(True)` and input is CUDA.

Fixes #89492

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136224
Approved by: https://github.com/ezyang, https://github.com/justinchuby
 2024-09-26 04:52:05 +00:00
PyTorch MergeBot
e3b89ca124 Revert "Add deterministic path for CUDA cumsum (#136224)" 
This reverts commit b1a02bf708.

Reverted https://github.com/pytorch/pytorch/pull/136224 on behalf of https://github.com/ezyang due to Failing internall CI ([comment](https://github.com/pytorch/pytorch/pull/136224#issuecomment-2374201626))
 2024-09-25 14:11:01 +00:00
Kurt Mohler
b1a02bf708 Add deterministic path for CUDA cumsum (#136224) 
Change `cumsum` to call its decomposition when `use_deterministic_algorithms(True)` and input is CUDA.

Fixes #89492

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136224
Approved by: https://github.com/ezyang, https://github.com/justinchuby
 2024-09-24 21:34:43 +00:00
enkilee
54fc4f56ff [Docs fix] fix syntax error in docs :torch.blackman_window (#136354) 
Fixes #ISSUE_NUMBER
https://pytorch.org/docs/stable/generated/torch.blackman_window.html

error at : equal to torch.blackman_window(L + 1, periodic=False)[:-1]).
should delete the last ).

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136354
Approved by: https://github.com/soulitzer
 2024-09-24 14:00:26 +00:00
PyTorch MergeBot
fd182b90a7 Revert "Add deterministic path for CUDA cumsum (#136224)" 
This reverts commit d45b0151e5.

Reverted https://github.com/pytorch/pytorch/pull/136224 on behalf of https://github.com/atalman due to Failing internall CI ([comment](https://github.com/pytorch/pytorch/pull/136224#issuecomment-2369244135))
 2024-09-23 19:57:13 +00:00
Kurt Mohler
d45b0151e5 Add deterministic path for CUDA cumsum (#136224) 
Change `cumsum` to call its decomposition when `use_deterministic_algorithms(True)` and input is CUDA.

Fixes #89492

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136224
Approved by: https://github.com/ezyang, https://github.com/justinchuby
 2024-09-20 02:41:56 +00:00
Alexander Jipa
5ca46be15e Fix/torch cat doc attr (#135698) 
The `torch.cat` attr name for tensors in the docs differs from the method signature, unlike other methods.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/135698
Approved by: https://github.com/albanD

Co-authored-by: Alexander Jipa <azzhipa@amazon.com>
 2024-09-11 22:32:55 +00:00
PhilipMay
90e12cf63d Fix return type of nansum example. (#135435) 
One of the examples in the documentation of `torch.nansum` contains a wrong return type. This fixes it.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/135435
Approved by: https://github.com/ezyang
 2024-09-09 03:34:52 +00:00
ooooo
32e052e468 [docs] improve torch.stack example code to be reproducible (#133857) 
Improve the sample code can produce the expected results after copying and executing it.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/133857
Approved by: https://github.com/soulitzer
 2024-08-21 14:07:02 +00:00
Tobias Ringwald
441c1c03d5 Prevent an unnecessary device -> host copy for CuPy arrays when not explicitly setting a device in torch.as_tensor. (#132595) 
See title. Until now, calling `torch.as_tensor` on a CuPy array would return a CPU tensor, when not providing a device. This is most likely not desired.

Fixes #132553

```python3
import torch
import cupy as cp

cupy_arr = cp.asarray([1, 2, 3])

# Default case
t = torch.as_tensor(cupy_arr)
# New behavior, same device as cupy_arr now, was cpu before
print(t.device)  # cuda:0

# Explicitly set device
t = torch.as_tensor(cupy_arr, device='cpu')
print(t.device)  # cpu

# Implicit default device
torch.set_default_device('cpu')
t = torch.as_tensor(cupy_arr)
print(t.device)  # cpu

# Default device via context manager
torch.set_default_device('cuda')
with torch.device('cpu'):
    t = torch.as_tensor(cupy_arr)
    print(t.device)  # cpu

# Unset default device
torch.set_default_device(None)
t = torch.as_tensor(cupy_arr)
# New behavior, same device as cupy_arr now, was cpu before
print(t.device)  # cuda:0
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/132595
Approved by: https://github.com/ezyang
 2024-08-08 00:26:58 +00:00
Xuehai Pan
4226ed1585 [BE] Format uncategorized Python files with ruff format (#132576) 
Remove patterns `**`, `test/**`, and `torch/**` in `tools/linter/adapters/pyfmt_linter.py` and run `lintrunner`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/132576
Approved by: https://github.com/ezyang, https://github.com/Skylion007
ghstack dependencies: #132574
 2024-08-04 17:13:31 +00:00
Pearu Peterson
a4ea776881 Add pinned memory support to sparse COO/CSR/CSC/BSR/BSC tensors (#129645) 
As in the title:

To register indices/values of a sparse XYZ tensor with CUDA, the following methods are supported
- `sparse_xyz_tensor(indices, values, pin_memory=True)`
- `sparse_xyz_tensor(indices, values).pin_memory()`
- `sparse_xyz_tensor(indices.pin_memory(), values.pin_memory())`

Fixes https://github.com/pytorch/pytorch/issues/115330

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129645
Approved by: https://github.com/amjames, https://github.com/cpuhrsch, https://github.com/eqy
 2024-08-02 08:55:55 +00:00
Aos Dabbagh
9f6d7df3d9 docs(multinomial): Add reference to Multinomial class (#131904) 
This PR just adds the reference to the class
`torch.distributions.multinomial.Multinomial` in `torch.multinomial`.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/131904
Approved by: https://github.com/jbschlosser
 2024-07-30 18:05:07 +00:00
Yu, Guangye
9cae2160f5 Introduce the concept of Accelerators to PyTorch doc (#129363) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/129363
Approved by: https://github.com/EikanWang, https://github.com/gujinghui, https://github.com/albanD
ghstack dependencies: #129463, #129205
 2024-07-15 14:24:46 +00:00
Aaron Orenstein
634b62f111 typing proxy_tensor.py (#129182) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/129182
Approved by: https://github.com/Chillee
 2024-07-12 23:17:09 +00:00
Tianyi Tao
1d93367cfa Fix typo (#130305) 
Fixes #130241

that is a reopen pr of #130244, for possibly fixing the failed job
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130305
Approved by: https://github.com/Skylion007
 2024-07-09 20:02:00 +00:00
Xuehai Pan
735044191f [Easy] Add whitespace after comma when re-rendering tuple default value in schema (#129884) 
The default value of `rot90()` in the schema registry is `[0,1]` because we split the function schema by `", "`. There should be no space after `,` in `[0,1]`.

5c9d5272e4/aten/src/ATen/native/native_functions.yaml (L6120-L6126)

Then the the default value is formatted to `(0,1)` in `pyi` files. This PR manually adds an extra whitespace when rerendering the default value to a string.

```python
", ".join(string.split(","))
```

```python
# before
def rot90(input: Tensor, k: _int = 1, dims: _size = (0,1)) -> Tensor: ...
# after
def rot90(input: Tensor, k: _int = 1, dims: _size = (0, 1)) -> Tensor: ...
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129884
Approved by: https://github.com/ezyang
 2024-07-03 11:45:24 +00:00
Xuehai Pan
75f64e1203 Fix test test_type_hints.py::TestTypeHints::test_doc_examples (#129829) 
As per the title, this test was broken for months.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129829
Approved by: https://github.com/ezyang
 2024-07-01 13:28:37 +00:00
Shashank Shekhar
a70a7337d2 Update torch.nanmean() docstring to mention input dtype requirement (#128155) 
Fixes #120570

## Description
Update torch.nanmean() docstring to mention input dtype requirement as either floating point type or complex.
Previously, the torch.mean() docstring had been updated in #120208 in a similar manner, but the torch.nanmean() docstring was not updated.

## Checklist

- [X] The issue that is being fixed is referred in the description.
- [X] Only one issue is addressed in this pull request.
- [x] Labels from the issue that this PR is fixing are added to this pull request.
- [X] No unnecessary issues are included into this pull request.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/128155
Approved by: https://github.com/malfet
 2024-06-12 17:46:36 +00:00
Aaron Orenstein
afe15d2d2f Flip default value for mypy disallow_untyped_defs [3/11] (#127840) 
See #127836 for details.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/127840
Approved by: https://github.com/oulgen
 2024-06-08 18:28:01 +00:00
hippocookie
3591bce6c7 Add usage explanation in torch.dot ducment (#125908) 
Fixes #125842

Add unsupported declaration on <code>torch.dot</code>, avoid misused like:

```python
>>> t1, t2 = torch.tensor([0,1]), torch.tensor([2,3])
>>> torch.dot(input=t1, other=t2)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: dot() missing 1 required positional arguments: "tensor"
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125908
Approved by: https://github.com/albanD
 2024-05-22 20:33:12 +00:00
Tobias Ringwald
4f1a56cd42 Switched from parameter in can_cast to from_. (#126030) 
Fixes #126012.

`from` is a reserved keyword in Python, thus we can't make the C++ impl available with `from` as function parameter. This PR changes the name to `from_` and also adjusts the docs.

If we want to preserve backwards compatibility, we can leave the C++ name as-is and only fix the docs. However, `torch.can_cast(from_=torch.int, to=torch.int)` won't work then.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/126030
Approved by: https://github.com/albanD
 2024-05-16 20:58:24 +00:00
PyTorch MergeBot
6065a4d46e Revert "Switched from parameter in can_cast to from_. (#126030)" 
This reverts commit 06d6bb4eba.

Reverted https://github.com/pytorch/pytorch/pull/126030 on behalf of https://github.com/huydhn due to Sorry for reverting your change but i need to revert it to avoid a diff train conflict with https://github.com/pytorch/pytorch/pull/125995.  Please help rebase and I will reland the change ([comment](https://github.com/pytorch/pytorch/pull/126030#issuecomment-2113757469))
 2024-05-16 01:42:23 +00:00
Tobias Ringwald
06d6bb4eba Switched from parameter in can_cast to from_. (#126030) 
Fixes #126012.

`from` is a reserved keyword in Python, thus we can't make the C++ impl available with `from` as function parameter. This PR changes the name to `from_` and also adjusts the docs.

If we want to preserve backwards compatibility, we can leave the C++ name as-is and only fix the docs. However, `torch.can_cast(from_=torch.int, to=torch.int)` won't work then.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/126030
Approved by: https://github.com/albanD
 2024-05-16 00:09:54 +00:00
Tom Ritchford
4d8fa7df40 Fix four misspellings of "its" in documentation (#125681) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125681
Approved by: https://github.com/Skylion007, https://github.com/svekars
 2024-05-13 18:14:09 +00:00
Apurva
c0c2f6156a Updated docs to add the error case for torch.multinomial Issue#125388 (#125495) 
Summary: Updated docs to add the error condition for torch.multinomial

Test Plan: No change in code

Reviewers: @drisspg

Subscribers: @drisspg

Tasks:

Tags:

Fixes #125388

Pull Request resolved: https://github.com/pytorch/pytorch/pull/125495
Approved by: https://github.com/drisspg
 2024-05-07 00:26:27 +00:00
Aaron Orenstein
a8574a9719 Fix global flake8 issues (#124771) 
Prior to this `lintrunner --all-files --take FLAKE8` failed.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/124771
Approved by: https://github.com/Skylion007
ghstack dependencies: #124428
 2024-04-26 15:35:53 +00:00
PyTorch MergeBot
1ac60484c1 Revert "Fix global flake8 issues (#124771)" 
This reverts commit f01275934b.

Reverted https://github.com/pytorch/pytorch/pull/124771 on behalf of https://github.com/jeanschmidt due to Unfortunately, I needed to revert #123735 and this one depends on it. So please check if there are no merge conflicts or breakages and feel free to merge this PR again ([comment](https://github.com/pytorch/pytorch/pull/124428#issuecomment-2078699836))
 2024-04-26 06:15:17 +00:00
Aaron Orenstein
f01275934b Fix global flake8 issues (#124771) 
Prior to this `lintrunner --all-files --take FLAKE8` failed.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/124771
Approved by: https://github.com/Skylion007
ghstack dependencies: #124428
 2024-04-25 14:25:00 +00:00
Frank Lin
249e65b92d Graph-Safe RNG State Exchange for Tensor Parallelism (#114068) 
See #113541

The PR allows for registering and controlling multiple RNG states using indices, ensuring cudagraph-safe operations, and includes both C++ and Python API changes to support this functionality.

cc  @eellison @anijain2305 @jansel @ezyang @ptrblck @csarofeen @mcarilli
Pull Request resolved: https://github.com/pytorch/pytorch/pull/114068
Approved by: https://github.com/ezyang, https://github.com/eqy, https://github.com/xuzhao9
 2024-03-27 01:14:38 +00:00
PyTorch MergeBot
4dc09d6aa4 Revert "Graph-Safe RNG State Exchange for Tensor Parallelism (#114068)" 
This reverts commit e9dcda5cba.

Reverted https://github.com/pytorch/pytorch/pull/114068 on behalf of https://github.com/ezyang due to memory leak in another ci ([comment](https://github.com/pytorch/pytorch/pull/114068#issuecomment-2018044527))
 2024-03-25 13:49:04 +00:00
Frank Lin
e9dcda5cba Graph-Safe RNG State Exchange for Tensor Parallelism (#114068) 
See #113541

The PR allows for registering and controlling multiple RNG states using indices, ensuring cudagraph-safe operations, and includes both C++ and Python API changes to support this functionality.

cc  @eellison @anijain2305 @jansel @ezyang @ptrblck @csarofeen @mcarilli
Pull Request resolved: https://github.com/pytorch/pytorch/pull/114068
Approved by: https://github.com/ezyang
 2024-03-21 01:57:08 +00:00
lancerts
680cfec295 Fix the default value of side in torch.searchsorted (#120066) 
Fixes #119999, currently the [doc](https://pytorch.org/docs/stable/generated/torch.searchsorted.html#torch.searchsorted) shows the default value of `side = "left"`
<img width="600" alt="Screenshot 2024-02-16 at 10 36 08 AM" src="https://github.com/pytorch/pytorch/assets/7495155/e7d159aa-4985-4f50-9d81-6e71c3116c0d">
while the [implementation ](https://github.com/pytorch/pytorch/blob/main/aten/src/ATen/native/native_functions.yaml#L11247) gives the default value of `side = c10::nullopt`.

- fix the [torch doc](https://github.com/pytorch/pytorch/blob/main/torch/_torch_docs.py#L13782) such that the default value of side is None.

- fix the [comment in cpp](4dc75f9084/aten/src/ATen/native/Bucketization.cpp (L19)) such that the default value of side is None.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/120066
Approved by: https://github.com/malfet
 2024-02-22 19:35:17 +00:00