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24 Commits

Author SHA1 Message Date
Xuehai Pan
17687eb792 [BE][4/6] fix typos in test/ (test/inductor/) (#157638) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/157638
Approved by: https://github.com/yewentao256, https://github.com/jansel
 2025-07-06 06:34:25 +00:00
PyTorch MergeBot
2344eca5eb Revert "Fix skipIfXpu and skipIfHpu disables tests when used on class (#151315)" 
This reverts commit ee096b89f6.

Reverted https://github.com/pytorch/pytorch/pull/151315 on behalf of https://github.com/jeanschmidt due to Seems to have introduced internal regressions, see [D74668899](https://www.internalfb.com/diff/D74668899). @malfet may you help the author get this PR merged? ([comment](https://github.com/pytorch/pytorch/pull/151315#issuecomment-2880203323))
 2025-05-14 13:15:03 +00:00
Wang, Eikan
ee096b89f6 Fix skipIfXpu and skipIfHpu disables tests when used on class (#151315) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/151315
Approved by: https://github.com/Skylion007, https://github.com/malfet
 2025-05-13 14:44:17 +00:00
Tom Ritchford
d8c8ba2440 Fix unused Python variables in test/[e-z]* (#136964) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136964
Approved by: https://github.com/justinchuby, https://github.com/albanD
 2024-12-18 23:02:30 +00:00
Xingyuan Li
cc6c248919 [Inductor UT] Generalize newly introduced inductor UTs for intel GPU (Part 2) (#136856) 
[Inductor UT] Generalize Newly introduced inductor UTs for intel GPU
reuse `test/inductor/test_inductor_freezing.py`
reuse `test/inductor/test_layout_optim.py`
reuse `test/inductor/test_loop_ordering.py`
reuse `test/inductor/test_memory_planning.py`
reuse `test/inductor/test_padding.py`

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136856
Approved by: https://github.com/EikanWang, https://github.com/etaf, https://github.com/jansel
 2024-10-18 03:58:00 +00:00
Oguz Ulgen
920f0426ae Add None return type to init -- tests rest (#132376) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/132376
Approved by: https://github.com/jamesjwu
ghstack dependencies: #132335, #132351, #132352
 2024-08-01 15:44:51 +00:00
Xuehai Pan
134bc4fc34 [BE][Easy][12/19] enforce style for empty lines in import segments in test/i*/ (#129763) 
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/129763
Approved by: https://github.com/jansel
 2024-07-18 07:49:19 +00:00
PyTorch MergeBot
b732b52f1e Revert "[BE][Easy][12/19] enforce style for empty lines in import segments in test/i*/ (#129763)" 
This reverts commit aecc746fcc.

Reverted https://github.com/pytorch/pytorch/pull/129763 on behalf of https://github.com/XuehaiPan due to need reland after rerunning lintrunner on main ([comment](https://github.com/pytorch/pytorch/pull/129763#issuecomment-2235736732))
 2024-07-18 06:39:58 +00:00
Xuehai Pan
aecc746fcc [BE][Easy][12/19] enforce style for empty lines in import segments in test/i*/ (#129763) 
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/129763
Approved by: https://github.com/jansel
 2024-07-18 05:13:41 +00:00
Sam Larsen
4cd503c1f3 Enable FX graph cache for a batch of inductor tests (#121696) 
Summary: Get more FX graph cache coverage by enabling it for these unit tests

Pull Request resolved: https://github.com/pytorch/pytorch/pull/121696
Approved by: https://github.com/eellison
 2024-03-14 03:39:59 +00:00
Shunting Zhang
1ce5049692 [inuctor] fix the layout problem for nll_loss2d_backward (#121173) 
Fixes https://github.com/pytorch/pytorch/issues/120759 .

The CUDA implementation of nll_loss2d_backward.default requires that the 'self' tensor to be contiguous. These implicit assumption may be broken by layout optimizations. The fix here is to add the constraint when we explicitly defining the fallback for the op.

Not sure if we can improve the cuda kernel to release the constraints though.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/121173
Approved by: https://github.com/jansel, https://github.com/desertfire
 2024-03-07 09:05:07 +00:00
eqy
86e6497c6f [Inductor][cuDNN] Disable tf32 in test_mutate_view_for_conv_output (#120953) 
Another disablement of TF32 to unblock #120642

Pull Request resolved: https://github.com/pytorch/pytorch/pull/120953
Approved by: https://github.com/Skylion007
 2024-03-01 05:51:29 +00:00
eqy
d1d50d2e4c [Inductor][cuDNN] Disable tf32 in test_mutate_base_for_conv_output (#120867) 
Looks like there is a sum? comparison where TF32 may not provide the necessary accuracy, leading to failures on sm86.

CC @Skylion007 , hopefully this unblocks #120642

Pull Request resolved: https://github.com/pytorch/pytorch/pull/120867
Approved by: https://github.com/Skylion007
 2024-02-29 06:59:32 +00:00
PyTorch MergeBot
1e60174891 Revert "[dynamo] Add run_inductor_tests entrypoint (#113278)" 
This reverts commit b00311ce9e.

Reverted https://github.com/pytorch/pytorch/pull/113278 on behalf of https://github.com/huydhn due to Sorry for reverting your stack, but it is failing to list test internally with buck2 ([comment](https://github.com/pytorch/pytorch/pull/113278#issuecomment-1811646325))
 2023-11-15 01:19:48 +00:00
Jason Ansel
b00311ce9e [dynamo] Add run_inductor_tests entrypoint (#113278) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113278
Approved by: https://github.com/yanboliang
 2023-11-11 08:54:43 +00:00
Jack Taylor
c9a806be28 [ROCm] enable additional inductor/dynamo UTs (#104624) 
Enables additional inductor UTs on ROCm and un skips outdated skips.

I have also removed a group of failures in `test_torchinductor_opinfo` which are now passing for CUDA and ROCm

```
-    # The following 3 tests fail on CUDA with AssertionError: expected size 5==5, stride 5==1 at dim=0
-    # linalg._svd's return value has different strides on CUDA vs CPU which causes this
-    # In test_meta.py there is a mechanism to skipping strides checks for some ops
-    # (including _linalg_svd), possibly we should have something similar here
-    "linalg.cond": {f32, f64},
-    "linalg.svdvals": {f32, f64},
-    "linalg.matrix_rank": {f32, f64},
-    "linalg.svd": {f32, f64},
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/104624
Approved by: https://github.com/malfet
 2023-07-11 20:44:02 +00:00
Shunting Zhang
98f00f881f [inductor] convert layout of conv weight ahead of time for inference (#103642) 
This PR handles inference. Will do similar thing for training later.

Some manual testing results shows this can improve inference perf by 2-3% (absolute improvement not relative one).
- convmixer: 4.285x -> 4.309x
- resnet50: 2.170x -> 2.203x

The PR is built upon freezing. Since without freezing, the weight input for a conv node may not be a parameter directly but be the output of precision converting ops. It's so much easier to implement this PR after freezing.

Commands
```
TORCHINDUCTOR_FREEZING=1 python benchmarks/dynamo/timm_models.py --backend inductor --amp --performance --only convmixer_768_32 --inference
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103642
Approved by: https://github.com/eellison
 2023-06-28 17:42:32 +00:00
Shunting Zhang
ec922efe3b [inductor] fix a failed test for layout optimization (#103984) 
Summary:
The test fail because a fixed port is used to initialize the process group. That does not work in stress test when multiple instance of the tests are being run concurrently.

Pick a random port and do some small retry for that.

Test Plan:
```
buck2 test 'fbcode//mode/opt' fbcode//caffe2/test/inductor:layout_optim -- --exact 'caffe2/test/inductor:layout_optim - test_mutate_view (caffe2.test.inductor.test_layout_optim.TestLayoutOptim)' --run-disabled --jobs 18 --stress-runs 10 --record-results
```

Differential Revision: D46908114

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103984
Approved by: https://github.com/williamwen42
 2023-06-22 19:34:10 +00:00
Edward Z. Yang
7a2a006c9e Remove dynamic_shapes test for inductor static weights (#103377) 
Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103377
Approved by: https://github.com/anijain2305
 2023-06-14 15:00:34 +00:00
PyTorch MergeBot
a980b19be7 Revert "Remove dynamic_shapes test for inductor static weights (#103377)" 
This reverts commit 53cb1a7d15.

Reverted https://github.com/pytorch/pytorch/pull/103377 on behalf of https://github.com/malfet due to broke lint ([comment](https://github.com/pytorch/pytorch/pull/103377#issuecomment-1591356769))
 2023-06-14 14:41:13 +00:00
Edward Z. Yang
53cb1a7d15 Remove dynamic_shapes test for inductor static weights (#103377) 
Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103377
Approved by: https://github.com/anijain2305
 2023-06-14 13:32:24 +00:00
Shunting Zhang
daf75c0759 [AOTAutograd] compare with stride hints (#103342) 
We previously compare FakeTensor's strides with real tensor's strides. This cause dynamic dimension of FakeTensor being specialized to static int. This may cause a graph specialized for one shape being used by another shape which is wrong.

Use stride hints for the comparison instead.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103342
Approved by: https://github.com/malfet
 2023-06-10 06:51:54 +00:00
Shunting Zhang
bf312f2d9d [inductor] add a few tests to verify view_to_reshape pass is safe (#103034) 
This PR follows up on issue https://github.com/pytorch/pytorch/issues/102229 . I added 2 unit tests and verified that autoaugorad/functionalization already handles view properly. The view_to_reshape pass does not cause an issues.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103034
Approved by: https://github.com/ezyang
 2023-06-06 22:32:51 +00:00
Shunting Zhang
86c7652503 [inductor] layout optimization for conv (#99773) 
convolution kernel with channels last runs much faster then kernel with contiguous inputs. The PR leverage that to optimize tensor layouts so we provide 'channels last' inputs to convolution. Some care need to be taken to not convert tensor layout between contiguous and channels last back and forth. Those extra copies hurt performance quite much.

Latest perf number [here](https://hud.pytorch.org/benchmark/compilers?startTime=Wed%2C%2024%20May%202023%2023%3A40%3A37%20GMT&stopTime=Wed%2C%2031%20May%202023%2023%3A40%3A37%20GMT&granularity=hour&suite=torchbench&mode=training&dtype=amp&lBranch=shunting-layout-opt-19&lCommit=baa797fc100688dfb044fbcbdebcfd2591710f78&rBranch=main&rCommit=999bae0f54108ffc5b7cf2524a02a83901554b16)
- TB: 1.64x -> 1.69x
- HF: 1.79x -> 1.78x (random noise)
- TIMM: 1.51x -> 1.65x

Right now we disable layout optimization for dynamic shape since there is perf loss in that combination. Here is a GH issue to followup: https://github.com/pytorch/pytorch/issues/102670

Pull Request resolved: https://github.com/pytorch/pytorch/pull/99773
Approved by: https://github.com/jansel
 2023-06-02 21:08:18 +00:00