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 |
|---|---|---|---|---|---|---|---|---|
2,754,588,032 | [inductor][gpu] torch.fft.fft outputs incorrect results when `n>1` | maybeLee | closed | [
"triaged",
"module: fft",
"oncall: pt2",
"module: inductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
I find this issue when running on a GPU card (RTX 3090). After torch.compile, torch.fft.fft outputs incorrect results. Here is the code to reproduce.
```
import torch
print(torch.__version__)
@torch.compile
def fft(input, n=None, dim=-1, norm=None):
return torch.fft.fft(input, n... | true |
2,754,565,536 | [ROCm] [STILL NOT FIXED] (Stable diffusion LoRA training, sd-scripts) ModuleNotFoundError: No module named 'triton.ops' | devsantiagoweb | closed | [
"module: rocm",
"triaged"
] | 5 | NONE | ### 🐛 Describe the bug
ROCm 6.2.4 + Linux Ubuntu 22.04.5 LTS, Using latest Pytorch Preview (Nightly) version.
AMD® Radeon graphics / AMD® Radeon rx 6700 xt
``` Traceback (most recent call last):
File "/home/santi-linux/trainer_kohya_ss/sd-scripts/library/train_util.py", line 4161, in get_optimizer
import b... | true |
2,754,558,089 | [Fake Tensor] [aot_eager] `.div` pass the check on inductor when divisor is zero | shaoyuyoung | open | [
"triaged",
"oncall: pt2",
"module: fakeTensor",
"module: aotdispatch",
"module: pt2-dispatcher"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
An error is raised when the divisor is 0 on eager. However, inductor passes the check and outputs the max value of Long.
both occurs on cpu and cuda.
**aot_eager** is where it starts to return bad results.
```python
import torch
import torch.nn as nn
class Model(nn.Module):
def __init_... | true |
2,754,527,910 | [2/N] Add Intel GPU Support to Torch Test Cases | daisyden | closed | [
"oncall: distributed",
"open source",
"release notes: distributed (fsdp)",
"module: inductor",
"module: dynamo"
] | 4 | NONE | This PR is merged with https://github.com/pytorch/pytorch/pull/141479 for testing purpose.
For RFC https://github.com/pytorch/pytorch/issues/142029, this PR will make the op_db general for all GPU devices defined in GPU_TYPES list.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-... | true |
2,754,432,320 | Unused var python | cyyever | closed | [
"open source",
"Stale",
"topic: not user facing"
] | 3 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,754,431,854 | [16/N] Fix extra warnings brought by clang-tidy-17 | cyyever | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 6 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,754,430,060 | Upgrading torch 2.5.0+xpu to torch 2.6.0+xpu breaks import torch on Ubuntu 24.04.1 / Python 3.12 | bmilde | open | [
"needs reproduction",
"module: binaries",
"triaged",
"module: regression",
"module: xpu"
] | 4 | NONE | ### 🐛 Describe the bug
Installing the new 2.6.0 xpu torch version from https://download.pytorch.org/whl/test/xpu on Ubuntu 24.04.1 / Python 3.12 breaks
`import torch`
for me with an undefined symbol error. This error does not happen with version 2.5.0+xpu, where I can successfully import torch on the same syst... | true |
2,754,349,896 | Make functionalization `ViewMeta` serializable with pickle. | ysiraichi | open | [
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"suppress-bc-linter",
"ci-no-td"
] | 18 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143712
Fix: #141974
This PR makes `ViewMeta` sequence, present in functional tensors,
serializable with pickle. In order to accomplish that, it makes
`ViewMeta` an abstract class with overridable `forward` and `reverse`
functi... | true |
2,754,331,431 | DistNetworkError when using multiprocessing_context parameter in pytorch dataloader | forestbat | closed | [
"oncall: distributed",
"module: dataloader"
] | 3 | NONE | ### 🐛 Describe the bug
Because of some special reasons I want to use `spawn` method to create worker in `DataLoader` of Pytorch, this is demo:
```
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader
from torch.utils.data import TensorDataset
import lightning... | true |
2,754,327,143 | Refactor AdamW into Adam (heavily inspired by tfsingh) | EmmettBicker | closed | [
"oncall: distributed",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"suppress-bc-linter",
"release notes: optim"
] | 11 | CONTRIBUTOR | Fixes #104899
Refactors AdamW into Adam by making AdamW a subclass of Adam. Additionally adds a test to assert that the added parameter `decoupled_weight_decay` is True in AdamW and also updates test_defaults_changed_to_foreach to account for the differences in module location for AdamW.
Heavily heavily inspired ... | true |
2,754,311,211 | Rename cache limit to recompile limit in configs | oulgen | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143709
This PR renames every cache_limit to recompile_limit via sed.
Old config options are maintained via Config(alias='xyz')
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @we... | true |
2,754,208,625 | Add a test for checking that the CUDA stubs directory is not in libcaffe2_nvrts.so's RPATH or RUNPATH | Flamefire | closed | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 3 | COLLABORATOR | The CUDA stub directory must not appear in the rpath or RUNPATH of any library as that would make it unusable at runtime. This should no longer happen (it did before, see the previous PR) but we better check that it stays like that. See the referenced issue https://github.com/pytorch/pytorch/issues/35418
The test ve... | true |
2,754,075,812 | [inductor] handle empty matrix on addmv on torch.compile | maybeLee | closed | [
"open source",
"module: inductor"
] | 3 | CONTRIBUTOR | Fix an issue when torch.addmv behaves inconsistent between torch.compile mode and eager mode. Here is the code to reproduce:
```
import torch
import numpy as np
@torch.compile
def test_optimized(input, mat, vec):
return torch.addmv(input, mat, vec)
def test(input, mat, vec):
return torch.addmv(i... | true |
2,753,940,063 | RuntimeError: tensor does not have a device | dev-kamran2001 | closed | [
"module: onnx",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
When trying to export a PyTorch YOLOv11 model (trained using ultralytics on a custom dataset) I get the error in the title.
Using .to(torch.device('cpu')) or just .to('cpu') on both or one of the models doesn't help, tried to tell torch to use CPU with every available function but no luck in... | true |
2,753,862,599 | Unable for CMake in setup.py to list anything OpenCL-ROCm | KISSEsWHISPERsFEEtBACKHUGs | open | [
"module: build",
"module: rocm",
"triaged"
] | 2 | NONE | ### Commands that are run to build PyTorch
```
python3.11 -m venv /opt/pyt2c1k/pyenv
source /opt/pyt2c1k/pyenv/bin/activate
export HSA_OVERRIDE_GFX_VERSION=9.0.0
export PATH=/opt/rocm/bin:$PATH
export LD_LIBRARY_PATH=/opt/rocm/lib:$LD_LIBRARY_PATH
export OpenCL_INCLUDE_DIR=/opt/rocm-6.3.0/include
export OpenCL_... | true |
2,753,861,784 | Segmentation Fault (core dumped) on as_strided with torch.compile | maybeLee | open | [
"module: crash",
"triaged",
"oncall: pt2",
"module: fakeTensor",
"module: aotdispatch"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
The following script lead to a segmentation fault.
```
import torch
@torch.compile
def as_strided(input, size, stride, storage_offset=0):
return input.as_strided(size, stride, storage_offset)
input = torch.tensor([], dtype=torch.float32)
size = [17,18]
stride = [-80,1]
stora... | true |
2,753,859,917 | Remove unused <ATen/core/Array.h> inclusion | cyyever | closed | [
"module: cpu",
"open source",
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor",
"ciflow/s390"
] | 6 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,753,829,320 | fix: all_gather_intotensor in torch.compile graph | yangxiaorun | closed | [
"oncall: distributed",
"triaged",
"open source",
"topic: not user facing"
] | 5 | NONE | Fixes #ISSUE_NUMBER
My PR request is to fix the bug in torch.compile.
An example of the error is as follows:
```
import os
import torch
import torch.distributed as dist
torch._logging.set_logs(graph=True, graph_code=True)
class allgather_in_tensor(torch.nn.Module):
def __init__(self):
super().__in... | true |
2,753,725,117 | [dynamo] Remove dead code after introducing UserDefinedDictVariable | anijain2305 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143698
* __->__ #143699
* #143722
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,753,722,530 | [dynamo] Remove HFPretrained config hack | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143698
* #143888
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,753,691,278 | [torch.compile] `torch.compile` throws an error when nn.Module contains a dataclass with float values. | nanlliu | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | ### 🐛 Describe the bug
I think `torch.compile` somehow treats scalar values as `tensors` but i don't see how scalar values should be a problem in this case.
This helps but falls back to eager mode
```
torch._dynamo.config.suppress_errors = True
```
What is the best way to debug this?
```
Traceback (mos... | true |
2,753,688,581 | [cumsum][CUDA][64-bit indexing] Add 64-bit indexing path for `cumsum` | eqy | closed | [
"module: cuda",
"triaged",
"module: 64-bit",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing"
] | 6 | COLLABORATOR | For #143486
Interestingly enough changing the indexing type seems to degrade performance when a larger width is not needed, even on small sizes, so making this a template param rather than forcing all cases to 64-bit
cc @ptrblck @msaroufim | true |
2,753,681,638 | [ROCm] CK Flash Attention Backend | xw285cornell | closed | [
"module: rocm",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)",
"topic: not user facing",
"skip-pr-sanity-checks",
"module: dynamo",
"ciflow/inductor",
"ciflow/rocm"
] | 14 | CONTRIBUTOR | Replace https://github.com/pytorch/pytorch/pull/138947 for re-import.
Replaces https://github.com/ROCm/pytorch/pull/1592
This PR contains the initial implementation of SDPA with composable_kernel backend. The CK path can be forced by simply calling torch.backends.cuda.preferred_rocm_fa_library("ck"). Similarly, ... | true |
2,753,660,904 | [audio hash update] update the pinned audio hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | 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 |
2,753,656,321 | Fix issue with setAttribute and int8_t vs int32_t variables | r-barnes | closed | [
"fb-exported",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: cpp",
"topic: improvements",
"ci-no-td"
] | 78 | CONTRIBUTOR | Test Plan: Sandcastle
| true |
2,753,655,322 | Enable Dynamic Memory Budget Solver | basilwong | closed | [
"fb-exported",
"topic: not user facing",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Summary:
Full Context: https://docs.google.com/document/d/1-j5KSbfGFJQcH4sYh7BIeJXso3zYzl5G5yFQqXdKx_o/edit?usp=sharing
tl;dr
This change introduces classes which help determine a dynamic memory budget. This will mostly be helpful for models with many implicit graph breaks.
---
New Classes:
*GraphInfoProvider*
* T... | true |
2,753,647,263 | Apply TorchFix TOR203 fixes | kit1980 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Codemodded via `torchfix . --select=TOR203 --fix`.
This is a step to unblock https://github.com/pytorch/pytorch/pull/141076 | true |
2,753,626,149 | [rpc] Fix unit test after c10::nullopt removal | yf225 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"topic: improvements",
"topic: not user facing"
] | 4 | CONTRIBUTOR | null | true |
2,753,615,508 | [torch][fx] Add support for EXIR dialect overload ops in normalize_function | dulinriley | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx"
] | 11 | CONTRIBUTOR | Summary:
I had a minor annoyance when debugging graphs using EXIR dialect ops,
that all the function normalization went away. For functions with > 5 arguments,
some of which are just simple bools and ints, it's very helpful to have
the kwarg names attached.
Enhance `normalize_target` to handle EdgeOpOverload targets. ... | true |
2,753,605,578 | [Codemod][AddExplicitStrictExportArg] caffe2/test | gmagogsfm | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: quantization",
"topic: not user facing",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 19 | CONTRIBUTOR | Reviewed By: avikchaudhuri
Differential Revision: D67530154
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @ipiszy @yf225 @chenyang78 @kade... | true |
2,753,604,001 | [ROCm] Inductor CK GEMM backend very slow | LunNova | open | [
"module: rocm",
"triaged",
"oncall: pt2"
] | 8 | NONE | ### 🐛 Describe the bug
When using the CK backend via `TORCHINDUCTOR_MAX_AUTOTUNE_GEMM_BACKENDS="CK,ATEN,TRITON,CPP"` compilation of CK kernels is very slow. (>one minute per file in some cases)
It looks like some very long symbol names in these files are making compilation slower because LLVM uses `SmallString<1... | true |
2,753,597,236 | [Codemod][AddExplicitStrictExportArg] caffe2/benchmarks/dynamo | gmagogsfm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"test-config/default",
"module: dynamo",
"ciflow/inductor"
] | 26 | CONTRIBUTOR | Reviewed By: avikchaudhuri
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,753,579,064 | [BE] Remove gcc-5 workaround for unused args | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | ditto
| true |
2,753,569,748 | Enhance provenance tracing unit test to cover `torch.compile()` | YUNQIUGUO | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 14 | CONTRIBUTOR | Summary: Follow up as title.
Test Plan:
```
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
```
Differential Revision: D67543556
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-C... | true |
2,753,555,060 | [inductor] Fix an aten.squeeze stride computation issue | desertfire | closed | [
"topic: bug fixes",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143683
Summary: Fixes https://github.com/pytorch/pytorch/issues/143498. The root cause is incorrect output stride for aten.squeeze (coming from aten.select in this case). If the input to aten.squeeze is non-contiguous, its output str... | true |
2,753,540,311 | Use random64 in Fischer-Yates algorithm for large N | ngimel | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: cpp",
"ci-no-td"
] | 27 | COLLABORATOR | Fixes bug in randperm https://nbsanity.com/static/a4774194938414dedcec7d6e99727d31/Shuffling_20in_20torch_20vs_20numpy-public.html
| true |
2,753,536,066 | [NestedTensors] Add an op to index on the ragged dimensions | krzysztofjordan | open | [
"triaged",
"open source",
"fb-exported",
"Stale",
"release notes: nested tensor"
] | 3 | CONTRIBUTOR | Summary:
One of the functionality we want is to be able to truncate nested tensors to new specified length arrays (rather than a narrow that does a uniform truncation across all batches).
This change enables that through the indexing operator.
Test Plan: N6362104
Differential Revision: D67514922
| true |
2,753,534,383 | [AOTI][reland] Emit a CMakeLists.txt when package_cpp_only | desertfire | closed | [
"Merged",
"ciflow/trunk",
"topic: new features",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"ciflow/rocm",
"ci-no-td"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143680
Summary: Emit a CMakeLists.txt with compile and link options when package_cpp_only is specified. After unzipping AOTI generated .pt2 package file, user can manually build the generated model code in their local environment.
c... | true |
2,753,517,797 | Add support for differentiable weight decay | EmmettBicker | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: optim"
] | 7 | CONTRIBUTOR | (Actual) second PR in a larger project to broaden support for differentiable optimizers with @janeyx99!
In this PR, I did a lot of pattern matching from the previous PR to add support for differentiable weight_decay.
And also added a single new line on line 359 (previously line 352) to make the code from the last... | true |
2,753,512,774 | [PTD] Dump rcclexp proxy trace in pytorch | dmwu | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 12 | CONTRIBUTOR | Summary:
Dump the active proxyOp status per rank and per communicator when WatchDog timeout or aborts.
Added
`#if defined(USE_ROCM) && defined(NCCL_COMM_DUMP)` guard in the print function, so only rcclexp users will see this dump in console.
This is the changes of the PTD.
Test Plan:
Job with A2A hang due to recei... | true |
2,753,506,415 | Upload METADATA file with whl binaries | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Upload the metadata file for wheels for pep658 https://peps.python.org/pep-0658/
Using a python script but using bash might be easier...
--
Testing
Example run https://github.com/pytorch/pytorch/actions/runs/12550595201/job/34994883276 without actual upload, just dry run
Lightly tested the script to make s... | true |
2,753,486,970 | graph module retracing without preserving MCS | avikchaudhuri | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143676
* #143664
Retracing while preserving module call signatures used to be a problem because graph modules don't have submodules at given paths. This led to a number of failing retracebility tests. By not trying to wrap modules w... | true |
2,753,464,526 | Fix incorrect python expression | mhorowitz | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 13 | CONTRIBUTOR | Summary:
This expression would return True always, causing the input to be deleted
on error, even for non-write modes:
```
>>> bool("w" or "+" or "a" in "rb")
True
```
Test Plan: new test in test_fsspec.py
Differential Revision: D67537234
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 ... | true |
2,753,451,772 | [easy] Set feature use for aot autograd remote cache | jamesjwu | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: AO frontend"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143674
Use set_feature_use for logging aot autograd cache so that dynamo_compile has this data as well as PT2 Compile Events.
Differential Revision: [D67536293](https://our.internmc.facebook.com/intern/diff/D67536293/) | true |
2,753,386,276 | [ROCm] Enable post-merge trunk workflow on MI300 runners; skip and fix MI300 related failed tests | dnikolaev-amd | closed | [
"oncall: distributed",
"module: rocm",
"module: cpu",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/periodic",
"module: inductor",
"ciflow/inductor",
"rocm",
"rocm priority",
"keep-going",
"ciflow/rocm",
"ciflow/inductor-rocm"
] | 33 | CONTRIBUTOR | This PR
* makes changes to the workflow files and scripts so we can run CI workflows on the MI300 runners
* skips and fixes several tests, failed on MI300, observed in https://github.com/pytorch/pytorch/pull/140989
Skipped due to unsupported Float8_e4m3fn data type on MI300 (need to update test code to use dataty... | true |
2,753,347,424 | ci: Add scaffolding for buidling wheels sequentially | seemethere | open | [
"release notes: releng"
] | 2 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149675
* __->__ #143672
* #148419
Signed-off-by: Eli Uriegas <eliuriegas@meta.com> | true |
2,753,323,779 | Getattr access for subclasses in pre-dispatch | tugsbayasgalan | closed | [
"Stale",
"ciflow/trunk",
"fx",
"ciflow/inductor",
"release notes: export"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143671
This is a draft PR that tries to prototype how to capture attribute access in pre-dispatch IR. The motivating use case is: https://github.com/pytorch/ao/blob/039cef4ad546716aa04cd54c461feb173f7fe403/tutorials/developer_api_... | true |
2,753,319,835 | Potential rooms for fewer recompilations by introducing higher-level guards | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
I encountered this while investigating recompilations in #128071. The relevant model code is [here](https://github.com/HazyResearch/based/blob/5cee0bf62be1582580d073af069b96f7fb8dc6b2/based/models/mixers/convolution.py#L131-L146).
## Repro
```python
import torch
@torch.compile(backend="... | true |
2,753,300,281 | String representation of nn.MultiheadAttention should contain arguments | fiskrt | open | [
"module: nn",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
Following the recommendation of the [python docs](https://docs.python.org/3/reference/datamodel.html#object.__repr__), the string representation of an object should contain enough information to be re-constructable. Hence, the `nn.MultiheadAttention` class should follow this, like other modules... | true |
2,753,277,709 | Fix test_serialization_zipfile_actually_jit when weights_only is not default | mikaylagawarecki | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Fails in fbcode where weights_only isn't default
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143668
* #143403
* #143326
| true |
2,753,268,676 | Inductor specializes over input dimension when it's used in a `torch.full` call | StrongerXi | closed | [
"triaged",
"oncall: pt2",
"module: dynamic shapes",
"module: inductor"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
I encountered this while investigating recompilations in #128071. The relevant model code is [here](https://github.com/HazyResearch/based/blob/5cee0bf62be1582580d073af069b96f7fb8dc6b2/based/generation.py#L143-L153).
## Repro
Run the following with `TORCH_LOGS="guards, dynamic, recompiles"... | true |
2,753,231,897 | Extend vec backend with BF16 SVE intrinsics | Ryo-not-rio | closed | [
"oncall: distributed",
"module: cpu",
"triaged",
"open source",
"module: arm",
"Merged",
"NNC",
"Reverted",
"ciflow/trunk",
"release notes: quantization",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd",
"ci... | 36 | COLLABORATOR | - Following the work in https://github.com/pytorch/pytorch/pull/119571, BF16 SVE intrinsics are added to the Vectorized class, providing ~1.7x speedup on `silu` and `softmax`.
- Added bf16 detection in CMake
- Added a guard for native NEON code to prevent compilation errors
@aditew01 @maajidkhann please have a loo... | true |
2,753,210,034 | Support multiple prefetches | xyg-coder | closed | [
"oncall: distributed",
"release notes: distributed (fsdp)"
] | 2 | NONE | This will prefetch multiple modules. It's useful to increase the overlap. Although most of the time this will only cause extra prefetches in the first module call.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,753,206,431 | unflatten isinstance | avikchaudhuri | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: export"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143676
* __->__ #143664
When we unflatten, the submodules we generate (`InterpreterModule` or `InterpreterModuleDispatcher`) are not related by type to the original submodules `N`. This makes `isinstance(mod, N)` checks fail. Since we do n... | true |
2,753,204,866 | [don't merge] update vs2022 | xuhancn | closed | [
"module: windows",
"open source",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel",
"intel",
"ciflow/xpu"
] | 1 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremyux @Blackhex @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,753,204,863 | fix test_rng bisector test | eellison | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143662
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,753,167,317 | Fix separate in process bisector cache, cleanup on exit | eellison | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143662
* __->__ #143661
* #143657
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @cha... | true |
2,753,131,767 | allow profiling on all threads via experimentalConfig | ngimel | closed | [
"Merged",
"ciflow/trunk",
"release notes: profiler"
] | 3 | COLLABORATOR | In some situations we want to profile calls coming from all threads (similar to on-demand), not just the thread that started profiling and the spawned threads that would inherit KinetoThreadLocal state.
| true |
2,753,108,276 | Log more contextual data when nan is detected under the anomaly mode | yunjiangster | open | [
"module: autograd",
"triaged",
"module: NaNs and Infs",
"actionable"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
Currently the anomaly mode only reports a nan is found at a particular op, without showing the full input/output tensors as well as their sizes. This makes it difficult to narrow down the root cause of nan.
PR #143633 addresses this.
### Alternatives
Log the problema... | true |
2,753,084,377 | Fix emulate low precision bool inp | eellison | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143662
* #143661
* __->__ #143657
Fix for https://github.com/pytorch/pytorch/issues/143502
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang... | true |
2,753,061,745 | RFC: Use plain metal kernel for MPS mul | swolchok | closed | [
"Stale",
"release notes: mps",
"ciflow/mps"
] | 2 | CONTRIBUTOR | I suspect that torchchat MPS generation speed may be limited by dispatch overheads.
Test command: python3 torchchat.py generate llama3.2-1b-base --device mps --dtype float --num-samples=3
Run 3 + total average result (the first run drags the average down, which is why I'm also including run 3 results) before:
``... | true |
2,753,043,413 | 反射填充的反向传播没有确定性实现 | tyth66 | open | [
"triaged",
"module: determinism"
] | 0 | NONE | ### 🐛 Describe the bug
UserWarning: reflection_pad2d_backward_cuda does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True, warn_only=True)'. You can file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operat... | true |
2,752,978,774 | Pytorch 3.13t wheels for release 2.6 - triton dependency | atalman | closed | [
"module: binaries",
"triaged"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
While testing I noticed that wheel constraint does not work :
```
Requires-Dist: pytorch-triton==3.2.0+git35c6c7c6; platform_system == "Linux" and platform_machine == "x86_64" and python_version != "3.13t"
```
Workflow:
https://github.com/pytorch/pytorch/actions/runs/12427438642/job/3470... | true |
2,752,922,088 | [BE][Sparse] Get rid of gcc-5 workaround | malfet | closed | [
"Merged",
"release notes: sparse",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Discovered those comments while looking at https://github.com/pytorch/pytorch/pull/143620
| true |
2,752,890,288 | Improve performance of casted elementwise add operations | doru1004 | closed | [
"triaged",
"open source",
"Stale",
"release notes: cuda"
] | 2 | CONTRIBUTOR | Improve performance of casted elementwise add operations. | true |
2,752,889,957 | `MemoryDenyWriteExecute` in systemd service causes `RuntimeError: could not create a primitive` | MatthewCroughan | open | [
"needs reproduction",
"module: error checking",
"module: convolution",
"triaged",
"module: mkldnn",
"security"
] | 3 | NONE | `MemoryDenyWriteExecute` would be nice to use, but when pytorch is ran in this context, it throws the following, likely due to generating assembly at runtime, where that generated code is both +w and +x, which is generally a security issue. The code should be `-w`'d when it is done generating.
https://www.freedeskto... | true |
2,752,886,043 | AttributeError: 'GraphModule' object has no attribute 'xxxxx' when accessing module layers via path string (e.g., layer.1.bn3) | Yicooong | closed | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 0 | NONE | ### 🐛 Describe the bug
I encountered a AttributeError: 'GraphModule' object has no attribute 'xxxxx' when trying to access a layer of a PyTorch model using a string path (e.g., layer.1.bn3). This issue arises when attempting to dynamically access layers in a model using a path that includes both dot notation and num... | true |
2,752,816,284 | Floating Point Exception (core dumped) when running floordiv/remainder/fmod under torch.compile | maybeLee | open | [
"module: crash",
"triaged",
"oncall: pt2",
"oncall: cpu inductor"
] | 6 | CONTRIBUTOR | ### 🐛 Describe the bug
It is likely a division-by-zero problem.
Under eager mode, these APIs do not throw the `ZeroDivisionError` exception instead of a floating point error.
Here is the code to reproduce:
```
import torch
@torch.compile
def div(input,value):
return torch.Tensor.floor_divide_(inpu... | true |
2,752,801,634 | torch.special.polygamma outputs incorrect when using torch.compile | maybeLee | closed | [
"triage review",
"module: special",
"oncall: pt2",
"module: inductor"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
When receiving the following inputs:
```
n = 0
input = torch.tensor(2, dtype=torch.float32)
```
`torch.special.polygamma` (in compile mode) outputs incorrect result (-inf), and this API outputs correct result (0.4228) in eager mode.
Here is the code to reproduce:
```
import torch
i... | true |
2,752,719,521 | A very weird bug involving ddp | Wongboo | open | [
"oncall: distributed",
"module: ddp"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
A very weird bug involving ddp. After exchange order of train code and eval code, the program hangs forever
```python
# eval
@torch.no_grad()
def estimate_loss():
out = {}
model.eval()
for split in ['val']:
losses = torch.zeros(eval_iters)
for k in range(ev... | true |
2,752,631,036 | Getting "Could not initialize NNPACK! Reason: Unsupported hardware." warning even though NNPACK is enabled | kirillmeisser | open | [
"needs reproduction",
"triaged",
"module: nnpack"
] | 3 | NONE | ### 🐛 Describe the bug
Hi everyone,
I am trying to deploy EasyOCR (an OCR library built with PyTorch) locally on a VM. When executing the following lines:
```
import easyocr
reader = easyocr.Reader(['en'], gpu=False)
result = reader.readtext('test.png')
```
I get the following warning: "Could not initial... | true |
2,752,630,203 | typo? Update RELEASE.md | andife | closed | [
"topic: not user facing"
] | 3 | NONE | Fixes #ISSUE_NUMBER
| true |
2,752,569,220 | Wrong log_softmax output on cuda device float64 torch>=2.4.1 | jchacks | closed | [
"module: cuda",
"triaged",
"module: correctness (silent)"
] | 4 | NONE | ### 🐛 Describe the bug
I checked the other issues but not sure if they are fully related:
https://github.com/pytorch/pytorch/issues/140222
When applying `F.log_softmax` (and taking the exponential) or `F.softmax` over a large-ish dimension 517 (the size matters) on a cuda device (1080 Ti) using f64 dtype, the r... | true |
2,752,560,865 | Full bfloat16 ONNX export fails | umarbutler | closed | [
"module: onnx",
"triaged"
] | 3 | NONE | ### 🐛 Describe the bug
When running the below code:
```python
import torch
import onnxruntime
from transformers import AutoTokenizer, AutoModelForSequenceClassification
# BEGIN CONFIG #
MODEL_DIR = f'roberta-base'
# END CONFIG #
model = AutoModelForSequenceClassification.from_pretrained(MODEL_DIR, attn_... | true |
2,752,498,999 | Fix the build errors in ONEDNN+BLIS Path | phanicoder | open | [
"triaged",
"open source",
"release notes: build"
] | 5 | NONE | Summary:
These changes fix the errors caused while building with ONEDNN+BLIS libblis.so is a single threaded library. IntraOp Parallelism is not realized using this library. Changes are done using to link against libblis-mt.so, which is a multithreaded library.
When the following build options are issued to build P... | true |
2,752,459,860 | Non_blocking copy behavior on non-cuda/non-privateuse1 accelerator might be unexpected | albanD | closed | [
"triaged",
"module: xpu",
"module: accelerator"
] | 4 | COLLABORATOR | The implementation in https://github.com/pytorch/pytorch/blob/487873f7cafeb0fd390eaefe40496b804bceabbd/aten/src/ATen/native/TensorConversions.cpp#L341-L342 only uses pinned memory for these two devices while I would expect all accelerator to want to do that.
cc @gujinghui @EikanWang @fengyuan14 @guangyey @guangy10 in ... | true |
2,752,428,601 | Unable to export RoBERTa to ONNX | umarbutler | closed | [
"module: onnx",
"triaged"
] | 3 | NONE | ### 🐛 Describe the bug
When I try exporting a RoBERTa model with torch dynamo, I get this error:
```
Some weights of RobertaForSequenceClassification were not initialized from the model checkpoint at roberta-base and are newly initialized: ['classifier.dense.bias', 'classifier.dense.weight', 'classifier.out_proj.... | true |
2,752,311,937 | Fix unused-variable issues in caffe2 | r-barnes | closed | [
"fb-exported",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: sparse",
"ci-no-td"
] | 30 | CONTRIBUTOR | Summary:
LLVM-15 has a warning `-Wunused-variable` which we treat as an error because it's so often diagnostic of a code issue. Unused variables can compromise readability or, worse, performance.
This diff either (a) removes an unused variable and, possibly, it's associated code or (b) qualifies the variable with `... | true |
2,752,242,541 | [inductor] [cpp] Support vectorization for score and mask in FlexAttention CPU | chunyuan-w | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143638
## Description
We generate vectorized kernel for score and mask in FlexAttention with this PR.
## Modification
The main change include:
- For the input and output buffer to the mask and score function, instead of passin... | true |
2,752,143,348 | [Easy] Fix todo by enable tests for cuda | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Fix TODO in `test_tensor_creation_ops.py` file:
```python
# TODO: update to work on CUDA, too
```
**Test Result**
```bash
$ pytest test/test_tensor_creation_ops.py
```
```bash
$ lintrunner
```
![image](https:... | true |
2,752,090,735 | Add where_ ops | zeshengzong | open | [
"open source"
] | 6 | CONTRIBUTOR | Fixes #28329
| true |
2,752,084,307 | [Inductor][CPP] Fix bitwise shift with corner inputs | leslie-fang-intel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143635
**Summary**
Fix issue https://github.com/pytorch/pytorch/issues/143555 and https://github.com/pytorch/pytorch/issues/143566, we can align the implementation with Eager: https://github.com/pytorch/pytorch/blob/29b586bbad98dbc... | true |
2,752,044,098 | Add mps to GPU_TYPES | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Because it is a GPU, but don't require a triton, as it does not need one
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,752,028,982 | log more context to anomaly nan checks | yunjiangster | closed | [
"fb-exported",
"Stale",
"topic: not user facing"
] | 7 | NONE | Test Plan: buck tests
Differential Revision: D67321092
| true |
2,752,014,181 | Compiled forward pass output corrupted when using @torch.no_grad | ae99 | closed | [
"oncall: pt2"
] | 1 | NONE | ### 🐛 Describe the bug
Minimal reproduction:
```
import torch
import torch.nn as nn
class Model(nn.Module):
def __init__(self, n_state: int = 8):
super().__init__()
self.embed = nn.Embedding(32, n_state)
def forward(self, inputs):
padding = torch.zeros((1, 1), device=i... | true |
2,751,992,173 | [wip] kick off kernel compile early | eellison | closed | [
"Stale",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143631
* #143408
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aak... | true |
2,751,959,756 | Attempt to speed up MPS getTensorStringKey | swolchok | closed | [
"fb-exported",
"Stale",
"ciflow/trunk",
"release notes: mps",
"ciflow/mps"
] | 4 | CONTRIBUTOR | I saw while profiling torchchat's MPS mode that this function was unexpectedly hot. It does a bunch of unnecessary allocation, so let's try fixing that.
Unfortunately I have not tested this; I was able to debug it causing a crash, but I can't complete MPS inference (with the new torchao quantized mps ops) without a ... | true |
2,751,955,158 | Add support for bfloat16 atomic adds in fbcode | mlazos | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 6 | CONTRIBUTOR | Reland https://github.com/pytorch/pytorch/pull/141857 and fallback on A100 which doesn't have bfloat16 atomic add instrs.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desert... | true |
2,751,941,732 | Fix false positive from f-strings in set_linter | jansel | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143628
This linter was going crazy in python 3.12, example:
```py
$ python3 tools/linter/adapters/set_linter.py torch/_inductor/runtime/triton_heuristics.py
torch/_inductor/runtime/triton_heuristics.py:192:25: Builtin `set` is ... | true |
2,751,922,300 | [caffe2] Add AVX512 support for box_cox operator | efiks | closed | [
"caffe2",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Summary:
Reuse templetized implementation of box_cox caffe2 operator.
* Duplicate .cc file of AVX2
* change intrinsics functions to use AVX512 instructions
* override templates
* extend the caller to use new methods
* guard AVX512 with a gflag to allow smooth transition
Differential Revision: D67433457
| true |
2,751,885,587 | [dynamo] Add types to exc.py | jansel | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143626
* #143610
* #143552
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,751,863,593 | fix typo in autocast header | williamwen42 | closed | [
"module: amp (automated mixed precision)",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143625
* #143592
cc @mcarilli @ptrblck @leslie-fang-intel @jgong5 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,751,860,673 | pytorch v2.5.1 build for nvidia jetson orin nano 8GB | lida2003 | closed | [
"module: build",
"module: cuda",
"triaged",
"module: jetson"
] | 3 | NONE | ### 🐛 Describe the bug
pytorch v2.5.1 build for nvidia jetson orin 8GB
- Previous discussion here FYI: https://forums.developer.nvidia.com/t/request-build-script-for-pytorch-or-up-to-date-pytorh-binary-release-supporting-jetson-boards-running-l4t35-6-ubuntu20-04/316972
```
Software part of jetson-stats 4.2.1... | true |
2,751,854,398 | Revert "refactor tensorify restart logic to use sources (#141517)" | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"topic: not user facing",
"fx",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143623
This reverts commit 30d8b30db7eaaa254d97077ac6515cdc4568fd6d.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @chenyang78 @kadeng @... | true |
2,751,835,609 | [triton pin 3.2] Cherry pick additional device context fix | bertmaher | closed | [
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143622
Summary:
* https://github.com/triton-lang/triton/pull/5276 | true |
2,751,834,296 | [inductor][cpu]text-classification+albert-base-v1 failure in prepare_pt2e | zxd1997066 | closed | [
"oncall: quantization"
] | 11 | CONTRIBUTOR | ### 🐛 Describe the bug
After changing to torch.export.export_for_training from capture_pre_autograd_graph, the following failure occurs.
```
Traceback (most recent call last):
File "/workspace/pytorch/./transformers/examples/pytorch/text-classification/run_glue.py", line 652, in <module>
main()
File "/wo... | true |
2,751,821,390 | Apply clang-format for ATen/core/dispatch headers | zeshengzong | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Code change via add path config in `.lintrunner.toml` file and running
```bash
$ lintrunner -a --take CLANGFORMAT --all-files
```
cc @ezyang | true |
2,751,801,509 | Revert D67066706 | bobrenjc93 | closed | [
"fb-exported",
"release notes: fx",
"fx",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Summary:
This diff reverts D67066706
verified that this causes divergence in S477892
Test Plan: NA
Differential Revision: D67499773
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,751,795,868 | [caffe2] Add ISA selection | efiks | closed | [
"caffe2",
"fb-exported",
"Stale"
] | 5 | CONTRIBUTOR | Differential Revision: D67499220
| true |
2,751,772,874 | [Inductor] Constrain the shape of other tensor for Conv/Linear + broa… | jiayisunx | closed | [
"module: cpu",
"open source",
"module: inductor",
"ciflow/inductor"
] | 1 | COLLABORATOR | …dcast add fusion. (#141759)
Fix https://github.com/pytorch/pytorch/issues/141671.
Summary:
The performance regression of these two timm_models is caused by Conv/Linear + broadcast add fusion run into oneDNN ref path. This PR constrains the shape of other tensor for Conv/Linear + broadcast add fusion to fix this... | true |
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