Commit Graph

14 Commits

Author SHA1 Message Date
Tom Ritchford
498a7808ff Fix unused Python variables outside torch/ and test/ (#136359)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136359
Approved by: https://github.com/albanD
2024-12-11 17:10:23 +00:00
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
Aaron Gokaslan
6de28e92d2 [BE]: Apply FURB118 (prev): replaces unnecessary lambdas with operator. (#116027)
This replaces a bunch of unnecessary lambdas with the operator package. This is semantically equivalent, but the operator package is faster, and arguably more readable. When the FURB rules are taken out of preview, I will enable it as a ruff check.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116027
Approved by: https://github.com/malfet
2023-12-20 19:35:08 +00:00
Aaron Gokaslan
b7b2178204 [BE]: Remove useless lambdas (#113602)
Applies PLW0108 which removes useless lambda calls in Python, the rule is in preview so it is not ready to be enabled by default just yet. These are the autofixes from the rule.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/113602
Approved by: https://github.com/albanD
2023-11-14 20:06:48 +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
shmsong
56a3831bc6 [NVFuser]Benchmark minor update (#46778)
Summary:
This is a tiny PR for two minor fixes:

1. Added `torch._C._jit_set_texpr_fuser_enabled(False)` to enable shape inference on nv fuser runs.
2. Renamed dynamic benchmark module names to avoid multiple matching. i.e. `simple_element` with `dynamic_simple_element`. I guess it'd be much easier if the pattern matching was based on `startswith`. Would be happy to update that if agreed.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/46778

Reviewed By: zhangguanheng66

Differential Revision: D24516911

Pulled By: bertmaher

fbshipit-source-id: 839f9a3e058f9d7aca17b2e6eb8b558e0e48e8f4
2020-10-26 12:22:36 -07:00
shmsong
43fe45ab0f [JIT] Add dynamic shape benchmark for NV Fuser (#46107)
Summary:
This PR modifies `benchmarks/tensorexpr`. It follows up[ https://github.com/pytorch/pytorch/issues/44101](https://github.com/pytorch/pytorch/pull/44101) and further supports characterizing fusers with dynamic shape benchmarks. Dynamic shape condition models the use case when the input tensor shape changes in each call to the graph.

Changes include:

Added an auxiliary class `DynamicShape `that provides a simple API for enabling dynamic shapes in existing test cases, example can be found with `DynamicSimpleElementBench`

Created new bench_cls: `DynamicSimpleElementBench`, `DynamicReduce2DInnerBench`, `DynamicReduce2DOuterBench`, and `DynamicLSTM`. They are all dynamic shaped versions of existing benchmarks and examples of enabling dynamic shape with `DynamicShape`.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/46107

Reviewed By: glaringlee

Differential Revision: D24229400

Pulled By: bertmaher

fbshipit-source-id: 889fece5ea87d0f6f6374d31dbe11b1cd1380683
2020-10-09 22:09:21 -07:00
Kevin Stephano
26a91a9f04 [WIP][JIT] Add benchmarking support of NV Fuser with FP16 dtype support (#44101)
Summary:
Modified files in `benchmarks/tensorexpr` to add support for NVIDIA's Fuser for the jit compiler.

This support has some modifications besides adding an option to support the NVIDIA fuser:

* Adds FP16 Datatype support
* Fixes SOL/Algo calculations to generally use the data type instead of being fixed to 4 bytes
* Adds IR printing and kernel printing knobs
* Adds a knob `input_iter` to create ranges of inputs currently only for reductions
* Adds further reduction support for Inner and Outer dimension reductions that are compatible with the `input_iter` knob.
* Added `simple_element`, `reduce2d_inner`, and `reduce2d_outer` to isolate performance on elementwise  and reduction operations in the most minimal fashion.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/44101

Reviewed By: ngimel

Differential Revision: D23713658

Pulled By: bertmaher

fbshipit-source-id: d6b83cfab559aefe107c23b3c0f2df9923b3adc1
2020-09-15 15:10:49 -07:00
Mikhail Zolotukhin
9fe3b1857d [TensorExpr] Fix imports in tensorexpr benchmarks. (#35830)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35830

Test Plan: Imported from OSS

Differential Revision: D20799464

Pulled By: ZolotukhinM

fbshipit-source-id: 1b5981ad15042f601a9b6eb01a799cdf71200666
2020-04-01 14:23:33 -07:00
Mikhail Zolotukhin
8998a1b3d3 Add tensorexpr benchmarks. (#35064)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35064

Test Plan: Imported from OSS

Differential Revision: D20543695

Pulled By: ZolotukhinM

fbshipit-source-id: 1cf294ab19465cb93557c2b195252c739b40a0f7
2020-03-20 12:01:31 -07:00
Mikhail Zolotukhin
976d6aaa51 Revert D20251830: [TensorExpr] Add tensorexpr benchmarks.
Test Plan: revert-hammer

Differential Revision:
D20251830

Original commit changeset: bafd66ce32f6

fbshipit-source-id: d8aea4b26441d8aba90c11d7350d3424df494052
2020-03-16 13:20:16 -07:00
Mikhail Zolotukhin
e93e7b2795 [TensorExpr] Add tensorexpr benchmarks. (#34230)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34230

This PR adds some benchmarks that we used to assess tensor expressions performance.

Differential Revision: D20251830

Test Plan: Imported from OSS

Pulled By: ZolotukhinM

fbshipit-source-id: bafd66ce32f63077e3733112d854f5c750d5b1af
2020-03-16 11:49:39 -07:00