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7 Commits

Author SHA1 Message Date
Arash Pakbin
f3ddc08ddc Additional operators in operator benchmark (#145625) 
The list of added operators:
add_, addcmul, arange, baddbmm…, bmm, clamp, div, div_, gelu, index_add, logical_and, mul_, sub_, topk, where

This pull request is the same as a previous one: https://github.com/pytorch/pytorch/pull/145121 which inadvertently got deleted while merging.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/145625
Approved by: https://github.com/jeffdaily
 2025-01-26 19:20:02 +00:00
Xuehai Pan
c0ed38e644 [BE][Easy][3/19] enforce style for empty lines in import segments in benchmarks/ (#129754) 
See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter.

You can review these PRs via:

```bash
git diff --ignore-all-space --ignore-blank-lines HEAD~1
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129754
Approved by: https://github.com/ezyang
 2024-07-17 14:34:42 +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 7763c83af67eebfdd5185dbe6ce15ece2b992a0f.

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
Harut Movsisyan
956c8fa01e Microbenchmarking matrix mult (einsum, torch.mult, torch.mm) (#63654) 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63654

Test Plan:
```
> buck run mode/opt caffe2/benchmarks/operator_benchmark/pt:matrix_mult_test

# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : short

# Benchmarking PyTorch: einsum_bmm
# Mode: Eager
# Name: einsum_bmm_B4_M5_N3_K2_cpu
# Input: B: 4, M: 5, N: 3, K: 2, device: cpu
Forward Execution Time (us) : 27.970

# Benchmarking PyTorch: einsum_bmm
# Mode: Eager
# Name: einsum_bmm_B32_M25_N20_K30_cpu
# Input: B: 32, M: 25, N: 20, K: 30, device: cpu
Forward Execution Time (us) : 41.830

# Benchmarking PyTorch: einsum_bmm
# Mode: Eager
# Name: einsum_bmm_B128_M100_N120_K110_cpu
# Input: B: 128, M: 100, N: 120, K: 110, device: cpu
Forward Execution Time (us) : 499.114

# Benchmarking PyTorch: bmm
# Mode: Eager
# Name: bmm_B4_M5_N3_K2_cpu
# Input: B: 4, M: 5, N: 3, K: 2, device: cpu
Forward Execution Time (us) : 6.268

# Benchmarking PyTorch: bmm
# Mode: Eager
# Name: bmm_B32_M25_N20_K30_cpu
# Input: B: 32, M: 25, N: 20, K: 30, device: cpu
Forward Execution Time (us) : 12.676

# Benchmarking PyTorch: bmm
# Mode: Eager
# Name: bmm_B128_M100_N120_K110_cpu
# Input: B: 128, M: 100, N: 120, K: 110, device: cpu
Forward Execution Time (us) : 438.219

# Benchmarking PyTorch: einsum_elementwise
# Mode: Eager
# Name: einsum_elementwise_B4_M5_N3_cpu
# Input: B: 4, M: 5, N: 3, device: cpu
Forward Execution Time (us) : 7.657

# Benchmarking PyTorch: einsum_elementwise
# Mode: Eager
# Name: einsum_elementwise_B32_M25_N20_cpu
# Input: B: 32, M: 25, N: 20, device: cpu
Forward Execution Time (us) : 18.523

# Benchmarking PyTorch: einsum_elementwise
# Mode: Eager
# Name: einsum_elementwise_B100_M90_N110_cpu
# Input: B: 100, M: 90, N: 110, device: cpu
Forward Execution Time (us) : 55.103

# Benchmarking PyTorch: mul
# Mode: Eager
# Name: mul_B4_M5_N3_cpu
# Input: B: 4, M: 5, N: 3, device: cpu
Forward Execution Time (us) : 2.501

# Benchmarking PyTorch: mul
# Mode: Eager
# Name: mul_B32_M25_N20_cpu
# Input: B: 32, M: 25, N: 20, device: cpu
Forward Execution Time (us) : 10.589

# Benchmarking PyTorch: mul
# Mode: Eager
# Name: mul_B100_M90_N110_cpu
# Input: B: 100, M: 90, N: 110, device: cpu
Forward Execution Time (us) : 50.102

Reviewed By: ajyu

Differential Revision: D30455179

fbshipit-source-id: 9f2d92b2d2b860f41a8e59be2cc086d75b587f7b
 2021-08-24 16:26:26 -07:00