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7 Commits

Author SHA1 Message Date
Xuehai Pan
26f4f10ac8 [5/N][Easy] fix typo for usort config in pyproject.toml (kown -> known): sort torch (#127126) 
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
 2024-05-27 14:49:57 +00:00
PyTorch MergeBot
55c0ab2887 Revert "[5/N][Easy] fix typo for usort config in pyproject.toml (kown -> known): sort torch (#127126)" 
This reverts commit 7763c83af6.

Reverted https://github.com/pytorch/pytorch/pull/127126 on behalf of https://github.com/XuehaiPan due to Broken CI ([comment](https://github.com/pytorch/pytorch/pull/127126#issuecomment-2133044286))
 2024-05-27 09:22:08 +00:00
Xuehai Pan
7763c83af6 [5/N][Easy] fix typo for usort config in pyproject.toml (kown -> known): sort torch (#127126) 
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
ghstack dependencies: #127122, #127123, #127124, #127125
 2024-05-27 04:22:18 +00:00
Edward Z. Yang
dd3a77bc96 Apply UFMT to all files in benchmarks/ (#105928) 
Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/105928
Approved by: https://github.com/albanD
 2023-07-26 01:18:48 +00:00
Justin Chu
5ef023b05a [BE] Enable ruff's UP rules and autoformat benchmarks/ (#105429) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/105429
Approved by: https://github.com/malfet
 2023-07-19 04:46:37 +00:00
Xuehai Pan
a229b4526f [BE] Prefer dash over underscore in command-line options (#94505) 
Preferring dash over underscore in command-line options. Add `--command-arg-name` to the argument parser. The old arguments with underscores `--command_arg_name` are kept for backward compatibility.

Both dashes and underscores are used in the PyTorch codebase. Some argument parsers only have dashes or only have underscores in arguments. For example, the `torchrun` utility for distributed training only accepts underscore arguments (e.g., `--master_port`). The dashes are more common in other command-line tools. And it looks to be the default choice in the Python standard library:

`argparse.BooleanOptionalAction`: 4a9dff0e5a/Lib/argparse.py (L893-L895)

```python
class BooleanOptionalAction(Action):
    def __init__(...):
            if option_string.startswith('--'):
                option_string = '--no-' + option_string[2:]
                _option_strings.append(option_string)
```

It adds `--no-argname`, not `--no_argname`. Also typing `_` need to press the shift or the caps-lock key than `-`.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94505
Approved by: https://github.com/ezyang, https://github.com/seemethere
 2023-02-09 20:16:49 +00:00
Alexander
39f50f468d matmul performance benchmarks (#51647) 
Summary:
Minor PR following up the previous PR about sparse benchmarking utils https://github.com/pytorch/pytorch/pull/48397

Fixes https://github.com/pytorch/pytorch/issues/44634:  Performance benchmarks for matrix-matrix and matrix-vector ops (dense-sparse, sparse-sparse, and compare to dense-dense)

I ran  all benchmarks on an 2xRTX8000 machine with AMD 2970WX 24-cores for `DLMC/magnitude_pruning` dataset with different sparsity levels.

 ---
<details><summary> forward tests (expand for details).
</summary>

- `sparse@sparse`
```
[------------------------------- cpu:matmul-forward -------------------------------]
                           |   0.5   |   0.7   |   0.8   |   0.9   |  0.95  |   0.98
1 threads: -------------------------------------------------------------------------
      torch:dense@dense    |  108.1  |  100.5  |  101.3  |  108.4  |  98.4  |  187.4
      torch:sparse@sparse  |  659.1  |  368.8  |  156.5  |   53.3  |  26.8  |   14.9
      scipy:sparse@sparse  |  565.1  |  233.9  |  130.2  |   23.1  |  21.6  |   15.2

Times are in milliseconds (ms).

[----------------------------------- cuda:matmul-forward -----------------------------------]
                           |    0.5    |    0.7    |   0.8    |   0.9    |   0.95   |   0.98
1 threads: ----------------------------------------------------------------------------------
      torch:dense@dense    |   2243.5  |   4392.5  |  4419.8  |  2272.3  |  4433.9  |  8920.1
      torch:sparse@sparse  |  21369.2  |  11877.6  |  7339.2  |  1787.2  |  1335.1  |   845.7

Times are in microseconds (us).

```
- `sparse@dense`
```
[------------------------------- cpu:matmul-forward -------------------------------]
                          |   0.5   |   0.7   |   0.8   |   0.9   |   0.95  |   0.98
1 threads: -------------------------------------------------------------------------
      torch:dense@dense   |  105.8  |  103.8  |  103.0  |  104.4  |  104.4  |  197.0
      torch:sparse@dense  |  119.9  |  102.4  |   84.0  |   19.7  |   16.8  |   11.6
      scipy:sparse@dense  |  906.5  |  799.6  |  697.8  |  182.2  |  165.5  |  135.4

Times are in milliseconds (ms).

[------------------------- cuda:matmul-forward --------------------------]
                          |  0.5  |  0.7  |  0.8  |  0.9  |  0.95  |  0.98
1 threads: ---------------------------------------------------------------
      torch:dense@dense   |  2.2  |  4.4  |  4.4  |  2.3  |  4.5   |  2.3
      torch:sparse@dense  |  5.7  |  6.6  |  4.5  |  1.4  |  1.4   |  1.3

Times are in milliseconds (ms).

```
- `sparse@vector`
```
[----------------------------------- cpu:matmul-forward ----------------------------------]
                           |    0.5    |   0.7    |   0.8    |   0.9    |   0.95   |   0.98
1 threads: --------------------------------------------------------------------------------
      torch:dense@vector   |    510.6  |   505.8  |   759.6  |   782.1  |   682.4  |  764.6
      torch:sparse@vector  |  10122.8  |  6241.1  |  7935.6  |  2076.3  |  1049.5  |  826.3
      scipy:sparse@vector  |   1756.7  |  1033.9  |   678.2  |   343.5  |   168.5  |   65.4

Times are in microseconds (us).

[-------------------------------- cuda:matmul-forward --------------------------------]
                           |   0.5    |   0.7    |   0.8   |   0.9   |   0.95  |   0.98
1 threads: ----------------------------------------------------------------------------
      torch:dense@vector   |    36.1  |    21.5  |   21.6  |   21.5  |   21.6  |   21.5
      torch:sparse@vector  |  1099.2  |  1289.4  |  775.7  |  327.1  |  285.4  |  274.0

Times are in microseconds (us).

```
</details>

 ---
<details><summary> backward tests (expand for details).
</summary>

- `sparse@sparse`
```
[--------------------------------- cpu:matmul-backward ---------------------------------]
                           |   0.5    |   0.7    |   0.8    |   0.9    |   0.95  |   0.98
1 threads: ------------------------------------------------------------------------------
      torch:dense@dense    |   246.1  |   315.0  |   306.9  |   168.6  |  290.6  |  146.9
      torch:sparse@sparse  |  6417.5  |  4393.7  |  3012.7  |  1029.4  |  908.0  |  650.7

Times are in microseconds (us).

[----------------------------- cuda:matmul-backward -----------------------------]
                           |   0.5   |   0.7   |   0.8   |  0.9   |  0.95  |  0.98
1 threads: -----------------------------------------------------------------------
      torch:dense@dense    |    6.7  |   13.3  |   13.3  |   6.9  |  13.5  |   6.9
      torch:sparse@sparse  |  143.7  |  143.4  |  119.6  |  29.5  |  29.1  |  10.9

Times are in microseconds (us).

```
- `sparse@dense`
```
 [------------------------------ cpu:matmul-backward -------------------------------]
                          |   0.5   |   0.7   |   0.8   |   0.9   |   0.95  |   0.98
1 threads: -------------------------------------------------------------------------
      torch:dense@dense   |  185.9  |  304.8  |  305.8  |  169.9  |  308.7  |  168.4
      torch:sparse@dense  |  407.9  |  345.8  |  274.6  |  114.2  |  163.6  |  230.5

Times are in milliseconds (ms).

[--------------------------- cuda:matmul-backward --------------------------]
                          |  0.5   |  0.7   |  0.8   |  0.9  |  0.95  |  0.98
1 threads: ------------------------------------------------------------------
      torch:dense@dense   |   6.7  |  13.3  |  13.3  |  6.9  |  13.4  |   6.9
      torch:sparse@dense  |  16.7  |  19.0  |  15.1  |  6.3  |   8.2  |  12.7

Times are in milliseconds (ms).

```
</details>

Kindly review this  PR. cc mruberry, ngimel

Pull Request resolved: https://github.com/pytorch/pytorch/pull/51647

Reviewed By: albanD

Differential Revision: D27007809

Pulled By: mruberry

fbshipit-source-id: 8c1922cb3280027ca5e3eef31bfa20500c548cfd
 2021-03-14 00:25:45 -08:00