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11 Commits

Author SHA1 Message Date
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
8d45f555d7 [BE] [1/3] Rewrite super() calls in caffe2 and benchmarks (#94587) 
Rewrite Python built-in class `super()` calls. Only non-semantic changes should be applied.

- #94587
- #94588
- #94592

Also, methods with only a `super()` call are removed:

```diff
class MyModule(nn.Module):
-   def __init__(self):
-       super().__init__()
-
    def forward(self, ...):
        ...
```

Some cases that change the semantics should be kept unchanged. E.g.:

f152a79be9/caffe2/python/net_printer.py (L184-L190)

f152a79be9/test/test_jit_fuser_te.py (L2628-L2635)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94587
Approved by: https://github.com/ezyang
 2023-02-11 18:19:48 +00:00
Xiaoqiang Zheng
88b36230f5 Add full reduction benchmark. (#50057) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50057

As part of the effort to calibrate TE reduction performance, adding a full reduction benchmark.
Also add a "skip_input_transformation" option.
Fixed other reduction benchmarks to accept specific benchmarks that was listed.

Test plans:
* python -m benchmarks.tensorexpr --device=cpu --mode=fwd reduce_full
* python -m benchmarks.tensorexpr --device=cpu --mode=fwd reduce_full_fwd_cpu_16777216_s1
* python -m benchmarks.tensorexpr --device=cpu --mode=fwd reduce_full_fwd_cpu_16777216_s0
* python -m benchmarks.tensorexpr --device=cpu --mode=fwd reduce2d_inner
* python -m benchmarks.tensorexpr --device=cpu --mode=fwd reduce2d_inner_fwd_cpu_640_524288
* python -m benchmarks.tensorexpr --device=cpu --mode=fwd reduce2d_outer
* python -m benchmarks.tensorexpr --device=cpu --mode=fwd reduce2d_outer_fwd_cpu_640_524288

Test Plan: Imported from OSS

Reviewed By: bertmaher

Differential Revision: D25774138

Pulled By: zheng-xq

fbshipit-source-id: fd4598e5c29991be476e42235a059e8021d4f083
 2021-01-21 09:56:46 -08:00
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