id int64 2.74B 3.05B | title stringlengths 1 255 | user stringlengths 2 26 | state stringclasses 2
values | labels listlengths 0 24 | comments int64 0 206 | author_association stringclasses 4
values | body stringlengths 7 62.5k ⌀ | is_title bool 1
class |
|---|---|---|---|---|---|---|---|---|
3,006,122,585 | [Easy] Fix the compilation warning of BlasKernel. | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 16 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151736
As the title stated.
Change Before:
```C++
[2/21] Building CXX object caffe2/CMakeFiles/torch_cpu.dir/__/aten/src/ATen/native/BlasKernel.cpp.o
/root/Git.d/pytorch/pytorch/aten/src/ATen/native/BlasKernel.cpp:346:6: warning: ‘v... | true |
3,006,111,862 | [inductor] [silent incorrectness] `.flatten()-torch.vdot` outputs incorrect results when meeting edge case inputs | shaoyuyoung | closed | [
"oncall: pt2",
"module: inductor"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: `.flatten()-torch.vdot` outputs incorrect results when meeting **edge case inputs** on **cuda**. **0.1** in `inputs` is the key factor in incorrect calculation.
**device backend**: only triton
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch._... | true |
3,006,104,536 | [inductor] [cuda] [silent incorrectness] `torch.ormqr-torch.index_add` outputs incorrect calculation when meeting internal `indices` and `values` | shaoyuyoung | open | [
"high priority",
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: `torch.ormqr-torch.index_add` outputs incorrect calculation when meeting **internal** `indices` and `values`. If using **external** `indices` or `values` (i.e., using them in `inputs`), calculation is correct.
**device backend**: triton
```python
import torch
import torch.nn as nn... | true |
3,006,094,694 | Add explict type info in the try-catch for dynamo logging | houseroad | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 16 | MEMBER | Differential Revision: D73295871
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,006,079,281 | [Testing] Make test_add_complex3 run on different devices | malfet | closed | [
"Merged",
"Reverted",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 8 | CONTRIBUTOR | By constructing tensor on that device, because it does not call `self.common` but rather executes test directly.
Otherwise `test_add_complex3_mps` will test CPU inductor, rather than MPS one
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ip... | true |
3,006,020,000 | [ca] mark scalar int sizes as dynamic via tensor wrapping | xmfan | open | [
"Merged",
"Reverted",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"module: compiled autograd",
"ci-no-td"
] | 5 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151860
* #152119
* #151962
* __->__ #151731
This is the only way to support dynamic shapes on scalars right now.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipi... | true |
3,005,996,151 | [Inductor] Update should_decompose_mm condition for CPU | hl475 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Summary:
Similar to what we did previously in D70033166
Previously, for cpu we decompose addmm if
```
check_device(mat1, mat2, device="cpu")
and statically_known_true(mat1.shape[0] == 1)
and statically_known_true(mat2.shape[0] <= 64)
and statically_known_true(mat2.shape[1] <= 512)
```
We have a... | true |
3,005,986,284 | [audio hash update] update the pinned audio hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 18 | COLLABORATOR | This PR is auto-generated nightly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/nightly.yml).
Update the pinned audio hash. | true |
3,005,986,132 | [executorch hash update] update the pinned executorch hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 21 | COLLABORATOR | This PR is auto-generated nightly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/nightly.yml).
Update the pinned executorch hash. | true |
3,005,981,547 | [ROCm] Maxpool forward NHWC Perf Improvement targeting Resnet scenarios | amd-hhashemi | open | [
"module: rocm",
"triaged",
"open source",
"ciflow/trunk",
"release notes: rocm",
"ciflow/rocm"
] | 10 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
3,005,961,196 | Exported Module cannot call train() or eval() | supercharleszhu | open | [
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Hi Team, we are trying to load an exported module for continuous training and evaluation, but seems that we cannot call module.train() of module.eval(). Do you have any suggestions on what can be the best way to support this or workaround with this issue?
To reproduce:
```python
saved_ex... | true |
3,005,958,976 | run lintrunner for Export d68846308 | Camyll | closed | [
"module: lint",
"Merged",
"ciflow/trunk",
"topic: deprecation",
"topic: not user facing",
"oncall: fx",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 3 | CONTRIBUTOR | fixes broken lint tests in https://github.com/pytorch/pytorch/pull/151481
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,005,955,277 | [ROCm] AtomicAdd specialization on AMD for fp64. | naromero77amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda",
"topic: not user facing"
] | 14 | COLLABORATOR | Fixes https://github.com/pytorch/pytorch/issues/151039
Improve scatter add performance on MI250X.
Some numbers from the reporter's benchmark:
```
Before: dtype torch.float64 time = 3.577979326248169
After: dtype torch.float64 time = 0.0031385421752929688
```
No perf. improvement to MI300 or MI100.
cc ... | true |
3,005,942,011 | Add api to enable/disable NaN detector per-PG | wconstab | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151723
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @d4l3k @pavanbalaji
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @d4l3k | true |
3,005,939,919 | Add maxcount Parameter to torch.unique and torch.unique_consecutive | cora-codes | open | [
"module: performance",
"triaged",
"enhancement",
"needs design",
"module: python frontend"
] | 3 | NONE | ### 🚀 The feature, motivation and pitch
My hope is that this feature would prevent a synchronization, make both operations more easily compose with `torch.compile` and mirror the escape hatch provided by `torch.bincount`
### Alternatives
_No response_
### Additional context
_No response_
cc @msaroufim @jerryzh16... | true |
3,005,939,754 | [Benchmarking] Enable HF_GPT2 benchmarking on Metal | malfet | closed | [
"Merged",
"release notes: releng",
"topic: not user facing"
] | 3 | CONTRIBUTOR | By building wheel with USE_DISTRIBUTED=1
Otherwise attempt to run
```
python3 benchmarks/dynamo/torchbench.py --performance --only hf_T5 --backend inductor --inference --devices mps
```
wil fail with
```
File "/Users/nshulga/Library/Python/3.10/lib/python/site-packages/transformers/modeling_utils.py", line 4... | true |
3,005,939,496 | Maxpool Perf Improvement targeting resnet scenarios | amd-hhashemi | closed | [
"oncall: distributed",
"oncall: jit",
"module: rocm",
"module: cpu",
"release notes: releng",
"fx",
"module: inductor",
"module: dynamo",
"release notes: distributed (checkpoint)",
"release notes: inductor (aoti)"
] | 3 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd @mingfeima @XiaobingSuper @ashokei @jingxu10 @jerryzh168 @ezyang @Sherl... | true |
3,005,919,836 | flex attention: fix dispatch order for tensor subclasses, avoid hardcoding call to faketensor impl in dynamo | bdhirsh | open | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | This is enough to get @XilunWu 's stack in a state where his flex_attention DTensor implementations worked E2E for me. It also required these changes on the DTensor side, to properly add a DTensor rule for flex backward: P1789852198
There are two problems:
(1) in the normal dispatcher, we have a precedence orderi... | true |
3,005,903,996 | [WIP][draft_export] suppress pending unbacked for divisibility symbol | pianpwk | open | [
"fb-exported",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Differential Revision: D73287751
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
3,005,874,014 | [NJT] Dropout with p=0 still drops values | imh | open | [
"triaged",
"module: nestedtensor"
] | 3 | NONE | I'm trying to track down discrepancies where an NJT version of my model diverges in training while the padded version converges nicely.
I found a discrepancy in dropout between NJT and normal tensors that was interfering with reproducibility efforts: Setting dropout to 0 does not prevent dropout from happening with NJ... | true |
3,005,869,583 | [symmem] Add some code comments to rendezvous code | fduwjj | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151716
While reading and learning the rendezvous code, I just want to add some comments to explain the code.
cc @H-Huang @awgu @wanchaol @fegin @wz337 @wconstab @d4l3k | true |
3,005,869,142 | Use gather in index_select | isuruf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151715
| true |
3,005,859,330 | [ONNX] Auto-fallback in torch.onnx.export(..., dynamo=True) with deprecation warning | titaiwangms | open | [
"module: onnx",
"triaged",
"onnx-triaged"
] | 0 | COLLABORATOR | In the current implementation of `torch.onnx.export(..., dynamo=True)`, certain TorchScript-based operations are not supported. To ensure a smooth user experience, we should implement an automatic fallback mechanism with a deprecation warning. This fallback should handle cases where only the TorchScript-based exporter ... | true |
3,005,820,553 | [Cutlass] Only run EVT tests on sm90 | mlazos | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 15 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150910
* #152390
* #150909
* #150908
* #150907
* #151406
* #150906
* __->__ #151713
* #151405
* #150905
* #152306
* #152305
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayi... | true |
3,005,811,791 | DISABLED test_cublas_addmm_reduced_precision_fp16_accumulate_size_100_cuda_float16 (__main__.TestMatmulCudaCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"module: linear algebra",
"skipped"
] | 4 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_cublas_addmm_reduced_precision_fp16_accumulate_size_100_cuda_float16&suite=TestMatmulCudaCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/py... | true |
3,005,790,183 | Remove unnecessary recompile | tugsbayasgalan | open | [
"fb-exported",
"ciflow/inductor",
"release notes: export"
] | 2 | CONTRIBUTOR | Summary: Title
Test Plan: CI
Differential Revision: D73277480
| true |
3,005,783,617 | [c10] add #pragma once to leftright | dolpm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 17 | CONTRIBUTOR | Summary: i am getting duplicate defn's when including in my binary that already includes the dispatcher.
Test Plan: CI
Differential Revision: D73237748
| true |
3,005,782,045 | [provenance_tracking][reland] Fix UT error and re-land `ExternKernel` support | YUNQIUGUO | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 10 | CONTRIBUTOR | Summary:
ATT.
reverted previous diff : D72572050
Test Plan:
```
TORCH_LOGS="+inductor, output_code" buck2 run -c fbcode.enable_gpu_sections=true -c fbcode.nvcc_arch=h100 @//mode/opt fbcode//caffe2/test/inductor:provenance_tracing -- -r test_triton_kernel_to_post_grad_tracing_extern_kernel
```
Differential Revisio... | true |
3,005,746,511 | [DO NOT MERGE] Test new mi300 node capacity. | saienduri | closed | [
"module: rocm",
"triaged",
"open source",
"topic: not user facing",
"keep-going",
"ciflow/inductor-rocm",
"ciflow/rocm-mi300",
"ciflow/periodic-rocm-mi300"
] | 9 | CONTRIBUTOR | This commit is to merely test additional mi300 capacity.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
3,005,740,744 | difficulty creating magma tarball when new rocm or cuda versions are deployed | jeffdaily | closed | [
"module: rocm",
"module: ci",
"triaged",
"better-engineering"
] | 4 | COLLABORATOR | There is a chicken/egg problem with magma tarballs. Building magma for rocm or cuda is done in the manylinux image, for example:
pytorch/manylinux2_28-builder:rocm${DESIRED_CUDA}-main
but this image is built using a Dockerfile that calls install_magma.sh (for cuda) or install_rocm_magma.sh. These scripts just fetch... | true |
3,005,732,745 | Use folder tagged docker images for binary builds | clee2000 | closed | [
"Merged",
"ciflow/binaries",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Should be the last part of https://github.com/pytorch/pytorch/pull/150558, except for maybe s390x stuff, which I'm still not sure what's going on there
For binary builds, do the thing like we do in CI where we tag each image with a hash of the .ci/docker folder to ensure a docker image built from that commit gets us... | true |
3,005,727,697 | Enable TorchInductor to Generate Matmuls Natively via `tl.dot` | nullplay | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 8 | NONE | ### 🚀 The feature, motivation and pitch
TorchInductor currently relies on hand-written templates for matrix multiply variants, such as:
- [`bmm.py`](https://github.com/pytorch/pytorch/blob/main/torch/_inductor/kernel/bmm.py)
- [`mm.py`](https://github.com/pytorch/pytorch/blob/main/torch/_inductor/kernel/mm.py)
- [`m... | true |
3,005,725,783 | Added to docs for out_dtype arg in torch gemms | PaulZhang12 | closed | [
"Merged",
"ciflow/trunk",
"release notes: python_frontend"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151704
| true |
3,005,699,979 | [ONNX] Improve and sort out fallback mechanism | titaiwangms | closed | [
"module: onnx",
"triaged",
"onnx-triaged"
] | 3 | COLLABORATOR | In `torch.onnx.export(..., dynamo=True)`, when `fallback=True`, the current behavior involves attempting four different strategies within the FX-based exporter (exported program-based exporter) before falling back to the TorchScript-based exporter. These strategies include `TorchExportNonStrictStrategy`, `TorchExportSt... | true |
3,005,692,414 | [cutlass] Define GELU_taylor<float> only if CUTLASS version is <= 380 | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Summary:
#buildmore
https://github.com/NVIDIA/cutlass/blame/df8a550d3917b0e97f416b2ed8c2d786f7f686a3/include/cutlass/epilogue/thread/activation.h#L610
was added in v3.9 (not tagged yet)
Test Plan:
mostly ci.
Logic seems same.
Reviewed By: drisspg
Differential Revision: D72615240
| true |
3,005,683,743 | Non-deterministic alert in histc_cuda for floating types only | amjames | closed | [
"module: cuda",
"module: determinism",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"ciflow/inductor",
"ci-no-td"
] | 13 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151701
The note about atomic add only applies for floating point. The
implementation is deterministic for integer data types.
fixes: #151610
cc @ptrblck @msaroufim @eqy @jerryzh168 @mruberry @kurtamohler | true |
3,005,682,015 | [test] larger runner for cuda | clee2000 | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
3,005,676,688 | [ONNX] Migrate torchscript-based exporter test to exported program-based exporter | titaiwangms | closed | [
"module: onnx",
"triaged",
"onnx-triaged"
] | 1 | COLLABORATOR | Go through https://github.com/pytorch/pytorch/tree/main/test/onnx, and keep the important one. Specifically, In [test_pytorch_onnx_onnxruntime.py](https://github.com/pytorch/pytorch/blob/main/test/onnx/test_pytorch_onnx_onnxruntime.py), we have all the bugs fixed tests. | true |
3,005,661,821 | Replace perf-nightly-macos with inductor-perf-nightly-macos | huydhn | closed | [
"Merged",
"topic: not user facing",
"test-config/default"
] | 3 | CONTRIBUTOR | The name was updated by https://github.com/pytorch/pytorch/pull/151155. The benchmark results weren't updated on the dashboard otherwise.
For PT2 compiler perf benchmark, we are still relying on this old workflow. To get rid of this, we need to update PT2 benchmark dashboard to use the new benchmark database (cc @... | true |
3,005,636,111 | consolidate ATen/test/dispatch_key_set_test.cpp with rest of DispatchKeySet tests | swolchok | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151682
* __->__ #151697
* #151630
* #151629
* #151628
* #151627
* #151626
Doesn't seem to be a reason to have two test files for this.
Differential Revision: [D73274020](https://our.internmc.facebook.com/intern/diff/D73274020/) | true |
3,005,594,406 | ci: Ensure runners have a prefix | seemethere | closed | [
"topic: not user facing",
"ciflow/inductor",
"ciflow/linux-aarch64"
] | 10 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151696
Ensures that runners that should have a prefix do have a prefix. These
runners were continuously queueing since most of our pool was in
ephemeral type runners so we should switch these over to utilize the
prefixes as well.
Fu... | true |
3,005,587,509 | FP8 Support for FlexAttention | harveyp123 | open | [
"triaged",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
For FlexAttention, is it possible to add FP8 support for inference? FP8+Flash Attention 3 seems to be a great success, it will be great if FlexAttention can support FP8 inference
### Alternatives
_No response_
### Additional context
_No response_
cc @clee2000 @chauhang @pe... | true |
3,005,582,461 | [ONNX] Test 1.18 rc ONNX | titaiwangms | closed | [
"open source",
"topic: not user facing"
] | 23 | COLLABORATOR | Test ONNX 1.18rc with the current tests
| true |
3,005,560,533 | [ONNX] Flip `dynamo` default to True in torch.onnx.export | titaiwangms | open | [
"module: onnx",
"triaged",
"onnx-triaged",
"oncall: pt2",
"oncall: export"
] | 3 | COLLABORATOR | ### NOTE
The task will not commence until the sub-issues outlined below are addressed or resolved.
### Description
The torch.onnx.export function currently defaults the dynamo parameter to False. However, the dynamo=True path is the recommended approach for ONNX export, as it leverages the modern torch.export.export... | true |
3,005,554,059 | The docstring linter should not force overridden methods to be documented | rec | closed | [
"module: docs",
"module: lint",
"triaged",
"actionable"
] | 0 | COLLABORATOR | ### 🐛 Describe the bug
The [docstring linter](https://github.com/pytorch/pytorch/blob/28974a1ec3b921809c20a1217178da3792e5c545/tools/linter/adapters/docstring_linter.py) is asking me to document [this method](https://github.com/pytorch/pytorch/blob/28974a1ec3b921809c20a1217178da3792e5c545/torch/_inductor/ir.py#L6058)... | true |
3,005,552,609 | Turn on static cuda launcher in OSS | jamesjwu | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 28 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151691
After a few small bugfixes on tests (to make it so we throw/catch similar exceptions to triton), I think we're ready to flip the switch and use StaticCudaLauncher on by default in OSS.
Initial round of benchmarks look goo... | true |
3,005,549,990 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod7_BLOCK_SIZE_256_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod7_BLOCK_SIZE_256_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,005,549,559 | DISABLED test_non_equal_head_dims_score_mod2_float16_head_dims1_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_non_equal_head_dims_score_mod2_float16_head_dims1_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/... | true |
3,005,549,529 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod5_BLOCK_SIZE2_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod5_BLOCK_SIZE2_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/... | true |
3,005,549,462 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod3_BLOCK_SIZE_256_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod3_BLOCK_SIZE_256_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,005,549,453 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod5_BLOCK_SIZE_256_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod5_BLOCK_SIZE_256_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,005,484,322 | DTensor HOP call in TorchDispatchMode | XilunWu | closed | [
"oncall: distributed",
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151903
* __->__ #151685
* #151497
* #151507
* #151495
## Test
`pytest test/distributed/tensor/test_attention.py -s -k test_ring_flex_attention`
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,005,469,509 | More fix for aot_export_module name collision during unlifting | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Summary: Also check the module's named buffers and parameters when resolving name collision
Test Plan:
```
buck2 run mode/dev-nosan caffe2/test/inductor:test_aot_inductor -- -r aoti_constant_tensor_name_collision
```
Differential Revision: D73264885
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @Xi... | true |
3,005,436,049 | [c10d][fr] Fix a bug when first rank is not zero in the script | fduwjj | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary: Further testing the script, we found that we shouldn't always assume rank 0 is the first rank, so we need to check all entries and see if it P2P op for this coalesced group.
Test Plan: Directly test with corner case.
Differential Revision: D73266257
| true |
3,005,423,055 | Speed up OperatorEntry construction by avoiding updateDispatchTableFull_ | swolchok | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: performance",
"topic: not user facing"
] | 15 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151850
* #151849
* #151810
* #151807
* #151806
* #151805
* #151804
* #151803
* #151802
* #151801
* #151800
* __->__ #151682
The purpose of the updateDispatchTableFull_ call is, according to the comment, just to pick up fallback kernels if t... | true |
3,005,360,790 | Integrate with ONNX 1.18.0 release branch | ramkrishna2910 | open | [
"module: onnx",
"triaged"
] | 0 | NONE | ### 🚀 The feature, motivation and pitch
We are releasing ONNX 1.18.0. A release branch is created (https://github.com/onnx/onnx/tree/rel-1.18.0). Release candidates are also available from TestPyPI: pip install -i https://test.pypi.org/simple/ --pre onnx
Updates to op-list and other key updates can be found here: h... | true |
3,005,321,053 | undefined reference to `at::native::blas_impl::fp16_gemv_notrans(int, int, float, c10::Half const*, int, c10::Half const*, int, float, c10::Half*, int)' | shink | open | [
"module: build",
"triaged",
"module: regression",
"module: arm"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Compile error when building PyTorch from source:
```
/usr/bin/ld: /home/devuser/workspace/pytorch/build/lib/libtorch_cpu.so: undefined reference to `at::native::blas_impl::fp16_gemv_notrans(int, int, float, c10::Half const*, int, c10::Half const*, int, float, c10::Half*, int)'
```
But everyth... | true |
3,005,313,374 | [dtensor] op_schema recursive check for symints | IvanKobzarev | open | [
"oncall: distributed",
"topic: not user facing",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151679
Fix for https://github.com/pytorch/pytorch/issues/151106
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,005,233,281 | fix spammy library deinit errors when user passes an invalid TORCH_LOGS argument | bdhirsh | closed | [
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 9 | CONTRIBUTOR | fixes https://github.com/pytorch/pytorch/issues/151055. Thanks @desertfire for the patch that fixed this.
I was a bit careful about the test - I wanted to make sure the test accurately ensures that we don't regress and our error message is not spammy when users enter an invalid `TORCH_LOGS=....` argument. But I trie... | true |
3,005,217,244 | [BE][Easy]: Change typing to DimsType in dim_reduction | Skylion007 | closed | [
"oncall: distributed",
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 23 | COLLABORATOR | Use prims_common DimsType to reduce duplication of DType
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,005,216,362 | [aot] Set config partitioner recompute_views True by default | IvanKobzarev | open | [
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151676
Differential Revision: [D73260370](https://our.internmc.facebook.com/intern/diff/D73260370) | true |
3,005,206,921 | DISABLED test_cublas_addmm_reduced_precision_fp16_accumulate_size_1000_cuda_float16 (__main__.TestMatmulCudaCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"module: linear algebra",
"skipped"
] | 4 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_cublas_addmm_reduced_precision_fp16_accumulate_size_1000_cuda_float16&suite=TestMatmulCudaCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pyt... | true |
3,005,202,986 | [BE][Easy]: Simplify reversed call in graph matcher | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"fx",
"release notes: AO frontend"
] | 6 | COLLABORATOR | Another list call on reversed that is no longer necessary since ItemViews reversed
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
3,005,156,421 | [BE][Easy]: Simplify ModuleList reversed method | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | Removes unnecessary list calls now that we are in Python 3.9 and KeyViews implement reversed directly. | true |
3,004,939,136 | [torch] Expose PCI info from CUDA device | efiks | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 15 | CONTRIBUTOR | Summary:
PR#125083 add cuda device UUID info, but due to meta internal [version of ROCM the code was excluded](https://github.com/pytorch/pytorch/pull/125083?fbclid=IwY2xjawJvLnNleHRuA2FlbQIxMQABHlY55crrkTqWBWTsr2HVfuqnZ3R1GHR3o9Kf1o3h3uvyawEmCEdhdT48iY1P_aem_8tfrGrWE9SxFYasGfH8kCQ#issuecomment-2103315320).
This chang... | true |
3,004,938,510 | Migrate Windows Arm64 workflows to the new GitHub Actions Runner | iremyux | open | [
"module: windows",
"module: ci",
"triaged",
"module: arm"
] | 1 | COLLABORATOR | Windows Arm64 workflows and jobs should be migrated to use the newly available GitHub Actions runner, as described [here](https://github.com/actions/partner-runner-images/blob/main/images/arm-windows-11-image.md). This update ensures compatibility, improves performance, and leverages officially supported runner images ... | true |
3,004,901,642 | [inductor] [cuda] [fake tensor] `torch.ones(x.size(0))` becomes a fake tensor for `torch.diagonal_scatter` | shaoyuyoung | open | [
"high priority",
"triaged",
"oncall: pt2",
"module: fakeTensor",
"module: dynamo",
"module: pt2-dispatcher"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: `torch.diagonal_scatter` throws fake tensor error, misaligning with eager.
**device**: only cuda
**repro**
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch._inductor import config
config.fallback_random = True
torch.set_grad_enabled(False)
im... | true |
3,004,852,713 | [Infra] Jobs got frequently cancelled, sometimes mid-checkout | malfet | open | [
"module: ci",
"triaged",
"module: flaky-tests"
] | 13 | CONTRIBUTOR | ### 🐛 Describe the bug
I'm looking at the hud now and see some red:
https://hud.pytorch.org/hud/pytorch/pytorch/14293c237729a99440470206c0f791a8e76224ec/1?per_page=50&mergeEphemeralLF=true
But than clicking on those changes shows that jobs has been cancelled, for example see following workflow:
- https://github.com/p... | true |
3,004,710,575 | [autodeps2] Replace third-party/pyyaml with third-party/pypi/pyyaml | kkolur76 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Summary: We should use the pypi version.
Test Plan: CI
Differential Revision: D73211869
| true |
3,004,660,226 | [MPS] MultiheadAttention with masks and dropout produces NaNs | matkozak | open | [
"needs reproduction",
"triaged",
"module: macos",
"module: NaNs and Infs",
"module: correctness (silent)",
"module: mps"
] | 6 | NONE | ### 🐛 Describe the bug
Summary:
On MPS backend, combining MultiheadAttention with attention masks and dropout produces NaNs, while CPU execution works correctly.
I tried trimming down my code as much as possible, but I've ran into some seriously non-deterministic behaviors; this is a minimal snippet I've built whic... | true |
3,004,606,245 | Encountered NCCL stuck, I have got the flight recorder trace | XZLancer | closed | [
"oncall: distributed",
"module: nccl"
] | 1 | NONE | I encountered NCCL stuck error and below is the flight recorder trace. The error occurs at random position in one epoch. It seems there is a size mismatch causing the all-reduce error. How should I debug further to resolve the issue? Thanks for any reply.
```
Collective sequence number: 1487 has errors
internal record ... | true |
3,004,577,554 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod4_BLOCK_SIZE_128_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod4_BLOCK_SIZE_128_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,004,577,325 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod7_BLOCK_SIZE3_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod7_BLOCK_SIZE3_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/... | true |
3,004,577,246 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod4_BLOCK_SIZE_256_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod4_BLOCK_SIZE_256_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,004,577,237 | DISABLED test_builtin_score_mods_different_block_size_bfloat16_score_mod7_BLOCK_SIZE3_cuda_bfloat16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_bfloat16_score_mod7_BLOCK_SIZE3_cuda_bfloat16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.co... | true |
3,004,576,162 | DISABLED test_cublas_addmm_reduced_precision_fp16_accumulate_size_10000_cuda_float16 (__main__.TestMatmulCudaCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"module: linear algebra",
"skipped"
] | 5 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_cublas_addmm_reduced_precision_fp16_accumulate_size_10000_cuda_float16&suite=TestMatmulCudaCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/... | true |
3,004,576,159 | DISABLED test_kv_batch_broadcast_float16_batch_dims2_head_dims1_score_mod2_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_kv_batch_broadcast_float16_batch_dims2_head_dims1_score_mod2_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/py... | true |
3,004,576,158 | DISABLED test_load_rel_bias_float16_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_load_rel_bias_float16_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40767675430).
Over the past... | true |
3,004,574,407 | nn.Linear same weight and bias running on cuda float16 with input shape [2, 4] vs [1, 4] + [1, 4] got different results. | ganlvtech | closed | [
"module: cuda",
"triaged",
"module: cublas",
"module: half"
] | 3 | NONE | ### 🐛 Describe the bug
```python
import torch
for i in [44191, 47224]:
torch.manual_seed(i)
torch.cuda.manual_seed(i)
x = torch.empty(1, 4, device='cuda:0', dtype=torch.float16).uniform_(-1, 1)
x = torch.cat([x, torch.zeros_like(x)], dim=0)
weight = torch.empty(1, 4, device='cuda:0', dtype=torch.... | true |
3,004,509,151 | Device Check in torch.linalg.solve_triangular | hegdeadithyak | closed | [
"open source",
"release notes: linalg_frontend"
] | 2 | NONE | Fixes #142048
- [ ] Added Device Check in `pytorch/torch/testing/_internal/opinfo/definitions`
- [x] Added Test in `pytorch/test/test_linalg.py`
@lezcano I have no cuda on my device hence the tests got skipped , and I'm unsure wether this is a right approach. | true |
3,004,496,880 | Add a custom profiler configuration option | fwenguang | open | [
"triaged",
"open source"
] | 3 | CONTRIBUTOR | We aim to pass some configuration options to our custom Kineto backend via ExperimentalConfig,, so we added a `custom_profiler_config` parameter.
Requires https://github.com/pytorch/kineto/pull/1077 , | true |
3,004,400,722 | [Intel GPU] Use user-friendly err msg in mm | ZhiweiYan-96 | open | [
"module: cpu",
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"ciflow/xpu"
] | 7 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151655
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 | true |
3,004,355,224 | [sparse][exported-graph] Wrong Exported Graph for the Sparse Tensor | VimalWill | open | [
"oncall: pt2",
"oncall: export"
] | 5 | NONE | The exported graph neither reflected the incoming sparse tensor's layout nor threw an error message.
```
import torch
import torch.export
import torch.sparse
class BikNet(torch.nn.Module):
def __init__(self):
super(BikNet, self).__init__()
return
def forward(self, x):
return x.sum()
biknet = Bi... | true |
3,004,290,133 | [Easy] Optimize container.py typing | zeshengzong | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: nn",
"topic: docs",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
3,004,179,348 | [AMD] Remove fbcode limit for uuid | xw285cornell | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary: We're now w/ later rocm version so ok to add uuid back.
Test Plan: sandcastle
Differential Revision: D73240086
| true |
3,004,142,595 | [Inductor] Keep quiet if compile without CUDA support | shink | closed | [
"topic: not user facing",
"module: inductor"
] | 3 | CONTRIBUTOR | Fixes #151650
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,004,139,950 | [Inductor] Error getting cuda arch: Torch not compiled with CUDA enabled | shink | closed | [] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
If you run the model with `torch.compile` in a non-cuda env, will get an error:
```
Error getting cuda arch: Torch not compiled with CUDA enabled
```
Here's a simple case can repro this issue:
```python
@torch.compile(backend="inductor")
def fn(x, y):
return x + y
x = torch.randn(10)
y ... | true |
3,004,071,273 | Inductor pattern matcher replaces aten.reshape with aten.view in pattern | ProExpertProg | open | [
"triaged",
"oncall: pt2",
"module: inductor",
"vllm-compile"
] | 17 | NONE | ### 🐛 Describe the bug
Based on my rudimentary debugging, it seems that the pattern will record a `torch.ops.aten.reshape.default` as a `aten.view.default`. When a reshape is found in the fx.Graph, it is hence not matched.
In the example below, we compile the pattern itself, which should obviously match, but it does... | true |
3,004,058,353 | UnsupportedOperatorError: Exporting the operator 'aten::searchsorted' to ONNX opset version 20 is not supported. | ElinLiu0 | closed | [
"module: onnx",
"triaged"
] | 9 | NONE | ### 🚀 The feature, motivation and pitch
When expoprting a `torch.nn.Module()` with `torch.searchsorted()`,it raise:
```python
UnsupportedOperatorError: Exporting the operator 'aten::searchsorted' to ONNX opset version 20 is not supported.Please feel free to request support or submit a pull request on PyTorch GitHub: ... | true |
3,004,055,244 | Update link to NVIDIA cuDNN Support Matrix | radeksm | open | [
"triaged",
"open source",
"ciflow/trunk",
"topic: not user facing"
] | 6 | NONE | Fortunately or unfortunately the generic cuDNN version agnostic link doesn't wotk and now NVIDIA publishes supported hardware per cuDNN version.
| true |
3,004,000,027 | [Inductor] Test ND block pointers with dynamic shapes | blaine-rister | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | With ND tiling, we can get multi-dimensional block pointers with dynamic shapes. This is an important capability, but I couldn't find any CI tests for it. This PR adds a couple of tests checking that we get the expected block pointers with dynamic shapes, both for pointwise and reduction kernels.
Example kernels:
... | true |
3,003,921,175 | [demo] Verify test runner integration | codeJRV | open | [
"triaged",
"open source",
"topic: not user facing"
] | 1 | NONE | **Fixes #000. Do NOT Merge, this is just a test PR to test Nvidia CI-CD Runners**
@ZainRizvi PTAL. I'm out tomorrow afternoon, so we can test either tomorrow morning or on Monday afternoon.
cc: @zhe-thoughts
| true |
3,003,885,233 | DISABLED test_builtin_score_mods_different_block_size_float32_score_mod7_BLOCK_SIZE3_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float32_score_mod7_BLOCK_SIZE3_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/... | true |
3,003,885,213 | DISABLED test_captured_buffers_all_dims_bfloat16_cuda_bfloat16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_captured_buffers_all_dims_bfloat16_cuda_bfloat16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40761172832).
... | true |
3,003,885,157 | DISABLED test_builtin_score_mods_dynamic_float16_score_mask_mod4_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_dynamic_float16_score_mask_mod4_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs... | true |
3,003,885,156 | DISABLED test_non_equal_head_dims_score_mod3_bfloat16_head_dims0_cuda_bfloat16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_non_equal_head_dims_score_mod3_bfloat16_head_dims0_cuda_bfloat16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/run... | true |
3,003,884,896 | DISABLED test_non_equal_head_dims_score_mod7_float16_head_dims1_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_non_equal_head_dims_score_mod7_float16_head_dims1_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/... | true |
3,003,884,869 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod6_BLOCK_SIZE_256_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod6_BLOCK_SIZE_256_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,003,866,023 | Modified Dr. CI so it could detect runner disconnection failures | ParamThakkar123 | closed | [
"open source",
"topic: not user facing"
] | 3 | NONE | Fixes #66902 | true |
3,003,859,775 | [Intel GPU][Inductor] Fallback embedding_dense_backward on XPU | jianyizh | open | [
"triaged",
"open source",
"topic: not user facing",
"module: inductor",
"keep-going",
"ciflow/xpu",
"release notes: xpu",
"module: xpu"
] | 19 | CONTRIBUTOR | Reopen #146888, now the modification only affects xpu device. We do not want to decompose embedding_dense_backward for torch.compile. Current XPU devices have hardware limitations on atomic ops. Fallback to eager and we can use sort to implement this op. hf_T5 amp bf16 training in torchbench can get 2x improvement on ... | true |
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