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 |
|---|---|---|---|---|---|---|---|---|
2,950,254,513 | [aotd] Support saved tensors hooks in aot_autograd | IvanKobzarev | open | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: AO frontend"
] | 26 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150032
https://github.com/pytorch/pytorch/issues/148222
Goal:
At the moment autograd saved tensors hooks are run in eager after compiled forward.
They are executed at the same time for all saved tensors.
Hooks can be used... | true |
2,950,234,906 | Fixes detection of ArmPL on Linux platform | milpuz01 | closed | [
"triaged",
"open source",
"module: arm",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 16 | CONTRIBUTOR | On Linux it failed to detect that there is bin directory as it wasn't looking for armpl-info which is the only file that is in that directory on Linux and also adding link to math library as it is required to link against when checking for LAPACK functions.
Fixes #149610
cc @malfet @snadampal @aditew01 @nikhil-arm ... | true |
2,950,164,384 | [export] Save unflattened gm | angelayi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: export"
] | 5 | CONTRIBUTOR | Summary: Reland of D71082652
Test Plan:
https://www.internalfb.com/intern/testinfra/testrun/8444249558423545
https://www.internalfb.com/intern/testinfra/testrun/7318349652864293
https://www.internalfb.com/intern/testinfra/testrun/13229323980143778
https://www.internalfb.com/intern/testinfra/testrun/11540474119884081
... | true |
2,950,149,537 | [DRAFT] PR to regenerate docker images for nccl release | atalman | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | This PR should regenerate docker images
| true |
2,950,144,369 | [TD] Enable TD on distributed cpu | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Enable TD on distributed cpu, I think the only reason it's not is because I forgot to enable it
Get rid of some of the statements that are no ops:
* asan uses default shard
* nogpu got moved to periodic
* no windows cuda testing anymore
Only thing on pull and trunk that doesn't use TD is dynamo_wrapped but I t... | true |
2,950,135,729 | torch.nextafter(0, 1) returns 0 on MPS device | ogrisel | open | [
"module: printing",
"triaged",
"module: NaNs and Infs",
"module: third_party",
"module: mps"
] | 5 | NONE | ### 🐛 Describe the bug
The `torch.nextafter` function seems to return invalid results on the "mps" device using an Apple M1 processor on macOS 15.2 (24C101).
```python
>>> import torch
>>> torch.nextafter(torch.zeros(1, device="cpu"), torch.ones(1, device="cpu"))
tensor([1.4013e-45])
>>> torch.nextafter(torch.zeros(... | true |
2,950,069,930 | DISABLED test_foreach_check_stride_ignore_dims_of_one_cuda_float32 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 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_foreach_check_stride_ignore_dims_of_one_cuda_float32&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/3943160880... | true |
2,950,056,965 | Add a param for save format in Storage Writer | ankitageorge | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"release notes: distributed (checkpoint)"
] | 13 | CONTRIBUTOR | Summary: add a param to specify to the storage writer how to save tensors. Write now the only options are safetensors and torch.save.
Test Plan:
(lintrunner) [ankitageorge@devgpu003.cco3 /data/users/ankitageorge/fbsource/fbcode/caffe2 (1d57cb27b)]$ buck2 test 'fbcode//mode/opt' fbcode//caffe2/test/distributed/checkpoi... | true |
2,949,904,279 | [MPS] Preserve in/out dtypes in binary_op name | malfet | closed | [
"Merged",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150024
To be consistient with unary op and avoid silent correctness problems if someone will try to invoke the op with unexpected out dtype | true |
2,949,748,340 | Fix sparse CUTLASS-based kernels | alexsamardzic | closed | [
"module: sparse",
"module: cuda",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150023
* #149978
cc @nikitaved @pearu @cpuhrsch @amjames @bhosmer @jcaip @ptrblck @msaroufim @eqy | true |
2,949,678,966 | Dynamic Shapes with **kwargs | xadupre | open | [
"module: regression",
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 2 | COLLABORATOR | ### 🐛 Describe the bug
This used to work two weeks ago.
```python
import torch
class Model(torch.nn.Module):
def forward(self, **kwargs):
return kwargs["x"] + kwargs["y"]
x, y = torch.randn(2, 3), torch.randn(2, 3)
Model()(x=x, y=y)
ds = {
"kwargs": {
"x": {0: torch.export.Dim("batch")},
... | true |
2,949,571,244 | [ued] I want to see the full sizes/strides in TORCH_LOGS=recompiles | zou3519 | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"empathy-day"
] | 0 | CONTRIBUTOR | Sometimes I use the shapes of the Tensors to identify them. E.g.
```
DEBUG:torch._dynamo.guards.__recompiles:Recompiling function forward in /home/rzou/dev/kokoro/kokoro/kokoro/istftnet.py:378
triggered by the following guard failure(s):
- 10/1: tensor 'x' size mismatch at index 1. expected 512, actual 256
... | true |
2,949,361,493 | windows linker receives wrong non existent path | loscrossos | closed | [
"open source",
"release notes: python_frontend",
"topic: bug fixes"
] | 9 | NONE | Fix to issue #149889 where the windows linker receives a wrong path.
cc @malfet @seemethere @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremyux @Blackhex @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjame... | true |
2,949,334,597 | [Inductor] Inconsistency results after compilation with the inductor | Cookiee235 | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
model = torch.nn.Sequential(
torch.nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1),
torch.nn.ReLU(),
torch.nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=1),
).cuda()
inputs = torch.randn(1, 3, 32, 32, device='cuda')
res = model(inputs)
compiled_mod... | true |
2,949,295,748 | Allow TritonTemplate subclasses to override kernel type | ahmadsarvmeily | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor"
] | 4 | CONTRIBUTOR | Allows subclasses of `TritonTemplate` to override the kernel type, e.g.
```
class MyTritonTemplate(TritonTemplate):
kernel_type = MyTritonTemplateKernel
```
This means that all of the logic in `TritonTemplate` class doesn't need to be duplicated in subclasses if the only required change is the kernel type.
... | true |
2,949,264,564 | `__setitem__` with bool mask and dtype mismatch fails | crusaderky | open | [
"triaged",
"module: type promotion",
"module: advanced indexing"
] | 1 | NONE | ### 🐛 Describe the bug
`x[idx] = v` fails when
- `x` has ndim=0, and
- `idx` is a boolean mask (also with ndim=0), and
- `v` requires type promotion.
```python
import torch as xp
x = xp.asarray([0], dtype=xp.float64)
x[x==0] = xp.asarray(1, dtype=xp.float32) # OK
x = xp.asarray(0, dtype=xp.float64)
x[()] = xp.asa... | true |
2,949,227,009 | [ROCm] RuntimeError: HIPBLAS_STATUS_NOT_SUPPORTED in torch 2.6.0+rocm6.2.4 | zhaohm14 | closed | [
"high priority",
"module: nn",
"module: rocm",
"triaged"
] | 14 | NONE | I encountered a RuntimeError when performing a specific operation with PyTorch 2.6.0+rocm6.2.4 (and also 2.8.0.dev20250325+rocm6.3), while the same code works fine on PyTorch 2.5.1+rocm6.2. This appears to be a regression introduced in the newer version.
Here is the error message:
```log
File "/root/miniconda3/envs... | true |
2,949,187,514 | Refactor cudnn version check in smoke test for Windows | atalman | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | After https://github.com/pytorch/pytorch/pull/149885
I see failures on Window smoke test:
https://github.com/pytorch/test-infra/actions/runs/14069923716/job/39401550854
Due to fact that pypi packages such as cudnn and nccl are installed only on Linux. Hence this should resolve issue on Windows platform.
On win... | true |
2,949,169,514 | Test Github Runner behaviors | iremyux | closed | [
"open source",
"ciflow/binaries",
"topic: not user facing"
] | 3 | COLLABORATOR | Fake PR to test Github Runner behaviors | true |
2,949,074,618 | Add path used by pip's build isolation procedure to DLL search | Luthaf | open | [
"triaged",
"open source"
] | 2 | CONTRIBUTOR | Re-opening a new PR after #131340 and #140535 where closed for being stale without a review.
---
Without this, trying to `import torch` in a downstream `setup.py` file would result in
```
The specified module could not be found. Error loading "C:\...\pip-build-env-himl3xh3\normal\Lib\site-packages\torch\lib\s... | true |
2,948,895,924 | Inconsistent behavior of topk function when processing identical maximum tensor values | Topoer-seu | closed | [
"triaged",
"module: sorting and selection"
] | 1 | NONE | ### 🐛 Describe the bug
# Inconsistent behavior of topk function when processing identical maximum values in single vs batch mode
## Environment Information
- PyTorch version: 2.2.0
- CUDA version: 11.8
- cuDNN version: 8.7.0
- Python version: 3.8
## Problem Description
I've identified an inconsistency in the `topk`... | true |
2,948,810,336 | [Windows][CPU] 51 UT of inductor/test_torchinductor_opinfo.py failed with CPP wrapper | LifengWang | open | [
"module: windows",
"oncall: pt2",
"oncall: cpu inductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
51 UTs in inductor/test_torchinductor_opinfo.py met C++ compile error with CPP wrapper. The pytorch version used is 0324
[cpp_test_torchinductor_opinfo.log](https://github.com/user-attachments/files/19463359/cpp_test_torchinductor_opinfo.log)
nightly whl. Please take a look at the attached ... | true |
2,948,760,576 | [ROCm] Update CUDAPluggableAllocator.h (#1984) | amd-sriram | closed | [
"module: rocm",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: rocm",
"ciflow/periodic",
"ciflow/rocm",
"ciflow/inductor-rocm",
"ciflow/rocm-mi300"
] | 11 | CONTRIBUTOR | Altering the flag to use the correct streamType in CUDAPluggableAllocator class for ROCm gpu. The flag TORCH_HIP_VERSION does not work for ROCm as intended. This flag is replaced with USE_ROCM. This is impacting Distributed Fused Adam in Rocm/APEX when using nccl_ub feature. This has been tested with rocm/apex.
See ... | true |
2,948,528,314 | Missing detail explanation for `torch.Tensor.fill_` | zeshengzong | closed | [
"module: docs",
"triaged",
"module: python frontend"
] | 3 | CONTRIBUTOR | ### 📚 The doc issue
Usually there's a link in tensor ops to a detailed explanation like [torch.Tensor.floor](https://pytorch.org/docs/stable/generated/torch.Tensor.floor.html) has `See torch.floor()`
![Image](https://github.co... | true |
2,948,485,809 | Mutating a non-functional tensor with a functional tensor is not allowed. | liye0626 | open | [
"oncall: pt2",
"oncall: export"
] | 1 | NONE | ### 🐛 Describe the bug
```python
from torch.export import export_for_training
...
exported_module = export_for_training(
self.model,
self.example_inputs,
kwargs=self.example_kwarg_inputs,
dynamic_shapes=dynamic_shape,
)
# The line of related code in model forward
dim = -3
tgt = past_key_values_data... | true |
2,948,462,845 | torch.set_flush_denormal does not support float16 | sunjiabin17 | closed | [
"module: docs",
"module: cpu",
"triaged",
"module: correctness (silent)"
] | 3 | NONE | On the x86_64 architecture, running Ubuntu 22.04 with PyTorch v2.6.0, I conducted tests to evaluate the impact of set_flush_denormal on the float16 data type and observed no discernible effect.
```bash
>>> import torch
>>> torch.tensor(3e-5, dtype=torch.half)
tensor(2.9981e-05, dtype=torch.float16)
>>> torch.set_flush... | true |
2,948,359,403 | [S502778 ] Back out "[custom_ops][perf] Move expensive pytree traversals of tensors to C++ (#148555)" | yeqcharlotte | closed | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing"
] | 6 | NONE | Summary:
Original commit changeset: ce4bc74eaca5
Original Phabricator Diff: D71498751
Test Plan: Coming in S502778
Reviewed By: Jialin, jianyuh, ChenheliHua
Differential Revision: D71864977
| true |
2,948,353,436 | `torch.compile` errors on converting tensor subclass object into a sequence | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Repro:
```python
import torch
class Foo(torch.Tensor):
pass
torch._dynamo.config.traceable_tensor_subclasses.add(Foo)
#@torch.compile(fullgraph=True, backend="eager")
def f(x):
res = list(x)
return res
x = torch.ones(2).as_subclass(Foo)
res = f(x)
print(res)
# Eager prints: [Foo... | true |
2,948,334,268 | [DONT MERGE] customize win aot | chuanqi129 | closed | [
"open source",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 1 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,948,298,433 | Add min/max support in export | tugsbayasgalan | open | [
"fb-exported",
"module: dynamo",
"ciflow/inductor",
"release notes: export"
] | 7 | CONTRIBUTOR | Summary: Title
Test Plan: CI
I tried my best to replicate what dynamo does for min/max but had to omit some dynamo variables being handled because they are not applicable to non-strict export. I think this is ok because:
1. The original dynamo logic for handling min/max hasn't changed past 2 years so it is relat... | true |
2,948,215,021 | Support fp8 dtypes in assert_close | exclamaforte | closed | [
"Merged",
"module: testing",
"ciflow/trunk",
"release notes: python_frontend",
"topic: bug fixes",
"topic: not user facing"
] | 10 | CONTRIBUTOR | Fixes #135998
Adds support for fp8. These are compared bitwise, without atol and rtol. The implementation uses the same comparison functions, just with atol and rtol forced to zero. The error message is different from the default case; it only tells the user the first mismatch. This is to avoid triggering the error ... | true |
2,948,136,654 | [XPU] XPU build has been broken | chuanqi129 | closed | [
"needs reproduction",
"module: build",
"triaged",
"module: xpu"
] | 11 | COLLABORATOR | ### 🐛 Describe the bug
The XPU build crashed with below error message, it should be introduced by PR https://github.com/pytorch/pytorch/pull/149888
```
[5652/7734] Building SYCL (Device) object test_sycl_build_standalone_gen_simple_kernel.cpp.o
FAILED: test_sycl/CMakeFiles/test_sycl_build_standalone.dir/test_sycl_bu... | true |
2,948,120,854 | [BE] Use `auto` in MPS codebase more | malfet | closed | [
"Merged",
"ciflow/trunk",
"release notes: mps",
"ciflow/mps"
] | 6 | CONTRIBUTOR | Non-trivial (but still a no-op changes):
- Replace `[mpsGraph broadcastTensor:[mpsGraph constantWithScalar:1 dataType:MPSDataTypeInt32] toShape:inputTensor.shape name:nil]` with `[mpsGraph constantWithScalar:1 dataType:MPSDataTypeInt32 shape:inputTensor.shape]` | true |
2,948,115,896 | [CI] MacOS15-M2 runners are unstable | malfet | open | [
"module: ci",
"triaged",
"module: flaky-tests",
"unstable"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
Not sure if tests are exposing some sort of the problem, or we are doing something weird with infra, but
since https://github.com/pytorch/pytorch/pull/149900 was landed, about 5% of the runs finish prematurely with
runner lost communication with the server.
Examples on-trunk ([HUD link](https:/... | true |
2,948,115,404 | [WIP] rewrite pad_nd with guard_or_false | pianpwk | open | [
"release notes: fx",
"fx",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,948,108,677 | torch.compile does not support lambda error message arguments for torch._check | laithsakka | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | repo:
```
@torch.compile(fullgraph=True)
def f(a, b):
torch._check(True, lambda:f"hi")
return b*10
a = torch.ones(10, 10, device="cuda",dtype=torch.float64)
b = torch.torch.ones(10, 10, device="cuda",dtype=torch.float64)
f(a, b)
```
output
```
The above exception was the direct cause of the following except... | true |
2,948,089,653 | [TEST] | muchulee8 | closed | [
"fb-exported",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Differential Revision: D71857899
| true |
2,948,085,511 | [XPU] Linux CI/CD has been broken by the intel-deep-learning-essentials-2025.0 online installation | chuanqi129 | closed | [
"module: ci",
"triaged",
"module: regression",
"module: xpu"
] | 3 | COLLABORATOR | Recently, intel-deep-learning-essentials has release some new version packages which broken the 2025.0 clean installation, it led to the xpu build test build cpu-only pytorch in the past two days. Refer https://github.com/pytorch/pytorch/actions/runs/14053994965/job/39364027978#step:14:1789. And it block all XPU relate... | true |
2,948,070,345 | [inductor] make non-trivial tile ranges unbacked symint aware | ColinPeppler | closed | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 13 | CONTRIBUTOR | # New PR skipping this if unbackeds present: https://github.com/pytorch/pytorch/pull/150225
### Stacktrace
```
# If no fallback is provided then we'd see this.
File "/data/users/colinpeppler/pytorch/torch/_inductor/codegen/simd.py", line 1746, in tile_ranges
if V.graph.sizevars.atomically_apply_size_hint(
... | true |
2,948,043,588 | [inductor][triton 3.3] Fix cpp_wrapper w/ TMA in triton 3.3 | pytorchbot | closed | [
"open source",
"module: inductor",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149973
Fixes #148938
Context:
In triton 3.3, triton kernels expect a global scratch space arg to be passed in. This is fixed in #148051, which fixed most of the AOTI/cpp_wrapper failures; the fix is to inject a (null) global... | true |
2,948,036,274 | [inductor][triton 3.3] Fix cpp_wrapper w/ TMA in triton 3.3 (#149973) | davidberard98 | closed | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Fixes #148938
Context:
In triton 3.3, triton kernels expect a global scratch space arg to be passed in. This is fixed in #148051, which fixed most of the AOTI/cpp_wrapper failures; the fix is to inject a (null) global scratch space arg passed as an argument to all kernels.
But in the case of TMA, we need to ca... | true |
2,947,995,185 | Dynamo has limited support for `__instancecheck__` in meta types | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Repro:
```python
import torch
from torch.nn.parameter import Buffer
@torch.compile(fullgraph=True, backend="eager")
def f(buf):
return isinstance(buf, torch.nn.Buffer)
buf = Buffer(torch.ones(5))
res = f(buf)
# Eager: True
# Compiled: False
print(res)
```
I think we have all we ne... | true |
2,947,989,015 | [Async TP] all-gather-matuls not fusing properly when rowwise scales are used | danielvegamyhre | open | [
"oncall: distributed",
"triaged"
] | 17 | CONTRIBUTOR | ### 🐛 Describe the bug
## Summary
I recently implemented async TP support fusing scaled-matmul-reduce-scatter patterns with rowwise scales (https://github.com/pytorch/pytorch/pull/149247) as well as support for various AC settings which had become broken (no AC, per layer SAC, per op SAC with reduce_scatter saved) (h... | true |
2,947,987,803 | [dynamo][higher order ops] Make support_aliasing and support_input_mutation default to False | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
This PR https://github.com/pytorch/pytorch/pull/148953/files adds support for checking for input mutation and aliasing for HOPs. Currently, the default is that we expect all HOPs to support input mutation and aliasing. And then we set it to False just for invoke_subgraph.
But we should do othe... | true |
2,947,941,641 | [associative_scan] Fixes for assoc_scan testcases | bohnstingl | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 12 | COLLABORATOR | This PR fixes some issues with the testcases of `associative_scan`, in particular the problem where the compile_mode is inadvertently always set to `none`.
cc @ydwu4 | true |
2,947,901,476 | [ca] introduce RuntimeState to support c++ hooks via graph breaks | xmfan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 3 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150073
* #150074
* __->__ #149987
* #149897
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,947,842,991 | [ROCm] use magma-rocm tarball for CI/CD | jeffdaily | closed | [
"module: rocm",
"triaged",
"open source",
"Merged",
"topic: not user facing",
"ciflow/rocm"
] | 8 | COLLABORATOR | Follow-up to #149902.
cc @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,947,822,823 | gloo: update to latest version | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | MEMBER | This updates submodule Gloo to the latest version and brings a number of benefits:
* connection retries https://github.com/facebookincubator/gloo/commit/d2609ab5e8e06015c9184f6f29d702324709ef1c
* better error messages https://github.com/facebookincubator/gloo/commit/5ca057d6cc57f8b88db1adf56c63829ffe6f0558
* multi... | true |
2,947,814,348 | ncclSystemError: System call (e.g. socket, malloc) or external library call failed or device error | atalman | open | [
"oncall: distributed",
"triaged",
"module: nccl"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
Found followin nccl error when validating release 2.7 cherry-pick:
https://github.com/pytorch/pytorch/pull/149874
This is repro script:
https://gist.github.com/d4l3k/16a19b475952bc40ddd7f2febcc297b7
Running on g5.12xlarge machine.
Repro with Release 2.7 RC1 and nccl 2.25.1 :
Normally get... | true |
2,947,809,998 | [ROCm] Change LoadHIP to use find_file for rocm_version.h | naromero77amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 11 | COLLABORATOR | Fixes #149805
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang | true |
2,947,808,448 | request for faster inductor kernels for blockwise reduction across dim1 -> write | vkuzo | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
We should make the following kernel be fast in compile + inductor. This is important to be able to generate the dim1 cast to MX formats.
```
def scale_dim1_reference(x_hp: torch.Tensor, block_size) -> Tuple[torch.Tensor, torch.Tensor]:
# normalize across dim1
x_hp_d1 = x_hp.t().contigu... | true |
2,947,773,508 | Automate stable CUDA update and linter using min Python verison | pytorchbot | closed | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | 1. Fixes: https://github.com/pytorch/pytorch/issues/145571 . Cuda Stable is the same cuda version that is published to pypi, also used to set Metadata section in the rest of whl scripts and tag the docker releases with latest tag.
2. Updates min python version used in linter | true |
2,947,759,697 | Add inductor test for torchbind symint | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Summary: add test
Test Plan:
```
buck run //caffe2/test:test_export -- -r test_compile_custom_obj_unbacked_symint
```
Differential Revision: D71843179
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amja... | true |
2,947,660,286 | UNSTABLE inductor / linux-jammy-cpu-py3.9-gcc11-inductor / test (dynamic_cpu_inductor_torchbench) | yangw-dev | closed | [
"module: ci",
"oncall: pt2",
"unstable"
] | 3 | CONTRIBUTOR | > For example, DISABLED pull / win-vs2022-cpu-py3 / test (default). Once
> created, the job will be disabled within 15 minutes. You can check the
> list of disabled jobs at https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json
> If you need to get this out ASAP instead of waiting for 15 minutes,
> you can manually... | true |
2,947,657,102 | Refactor row-wise scaled MM | alexsamardzic | closed | [
"module: cuda",
"open source",
"Merged",
"ciflow/trunk",
"topic: improvements",
"topic: not user facing",
"module: float8"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150023
* __->__ #149978
1. Add config selection for SM89.
2. Only build kernels if compiling for given arch.
3. Factor out CMake code to enforce compiling for needed archs for individual files into a function.
cc @ptrblck @msaroufim @... | true |
2,947,653,227 | UNSTABLE inductor / linux-jammy-cpu-py3.9-gcc11-inductor / test (cpu_inductor_torchbench) | yangw-dev | closed | [
"module: ci",
"oncall: pt2",
"unstable"
] | 3 | CONTRIBUTOR | > For example, DISABLED pull / win-vs2022-cpu-py3 / test (default). Once
> created, the job will be disabled within 15 minutes. You can check the
> list of disabled jobs at https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json
> If you need to get this out ASAP instead of waiting for 15 minutes,
> you can manually... | true |
2,947,492,821 | [cuDNN][SDPA] abide by `enable_gqa` convention in cuDNN | eqy | closed | [
"module: cudnn",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: sdpa"
] | 18 | COLLABORATOR | long overdue
cc @csarofeen @ptrblck @xwang233 | true |
2,947,471,155 | Tensor subclass type not preserved across tensor ops on intermediate tensors under compile | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
## Repro
```python
import torch
class Foo(torch.Tensor):
pass
torch._dynamo.config.traceable_tensor_subclasses.add(Foo)
@torch.compile(fullgraph=True, backend="eager")
def f():
x = torch.ones(10).as_subclass(Foo)
y = x.new_ones((1, 2))
return y
# Eager: Foo([[1., 1.]])
# C... | true |
2,947,463,002 | [MPS] Fix metal ops with different dtypes | malfet | closed | [
"Merged",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149974
By implementing `_cast_` flavors of both dense and strided ops. Add regression tests that tests `fmax`/`fmin` for mixed dtypes.
Been dreaded to write this PR for a while, as it end up to be pretty bulky:
- Adds 1C10_... | true |
2,947,461,232 | [inductor][triton 3.3] Fix cpp_wrapper w/ TMA in triton 3.3 | davidberard98 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/rocm",
"module: aotinductor"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149973
Fixes #148938
Context:
In triton 3.3, triton kernels expect a global scratch space arg to be passed in. This is fixed in #148051, which fixed most of the AOTI/cpp_wrapper failures; the fix is to inject a (null) global... | true |
2,947,447,795 | sync fork | alexanderlerner | closed | [
"module: rocm",
"release notes: releng"
] | 2 | NONE | Fixes #ISSUE_NUMBER
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,947,437,669 | [ued][deepssek-vl2] builtin operator hash on type GenerationConfig | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Doc - https://docs.google.com/document/d/1Zm9TkApcQFpZ5CjwO6-8PEAGXAUwrE0MzKZQgXScHhQ/edit?tab=t.0
```
torch._dynamo.exc.Unsupported: Failed to trace builtin operator
Explanation: Dynamo does not know how to trace builtin operator `hash` with argument types ['GenerationConfig'] (has_kwargs F... | true |
2,947,436,091 | [ued][deepssek-vl2] Graph break on copy.deepcopy | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Doc - https://docs.google.com/document/d/1Zm9TkApcQFpZ5CjwO6-8PEAGXAUwrE0MzKZQgXScHhQ/edit?tab=t.0
```
torch._dynamo.exc.Unsupported: copy.deepcopy UserDefinedObjectVariable(GenerationConfig)
from user code:
File "/data/users/pianpwk/pytorch/torch/_dynamo/external_utils.py", line 70, in i... | true |
2,947,413,322 | [ued][qwen] Recompilations because of ID_MATCH on mod.forward | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Doc - https://docs.google.com/document/d/18DOOgTJRrDUb34G6yHcSl5NCM377CfFz2bnv-NaW-2M/edit?tab=t.0
### Error logs
_No response_
### Versions
NA
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgon... | true |
2,947,400,869 | [ued][qwen][dynamo] inspect.signature with non-constant function | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Graph break - https://www.internalfb.com/phabricator/paste/view/P1760735285
Doc - https://docs.google.com/document/d/18DOOgTJRrDUb34G6yHcSl5NCM377CfFz2bnv-NaW-2M/edit?tab=t.0
### Error logs
_No response_
### Versions
NA
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Ch... | true |
2,947,396,054 | [inductor] Fix mm logging for `torch._scaled_.mm` | YUNQIUGUO | open | [
"fb-exported",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"not4land",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 7 | CONTRIBUTOR | Summary:
This pr is just for recreation of the original pr: https://github.com/pytorch/pytorch/pull/149769
Fix for `torch._scaled_mm` op mm logging, which breaks the original brittle underscore parsing
assumptions.
Test Plan: CI
Differential Revision: D71828732
cc @voznesenskym @penguinwu @EikanWa... | true |
2,947,395,016 | test_pointwise_xlog1py/test_pointwise_zeta regressed for MPS inductor | dcci | closed | [
"module: mps",
"oncall: pt2",
"module: inductor"
] | 2 | MEMBER | ### 🐛 Describe the bug
```
_____________________________________________________________________________ MPSBasicTests.test_pointwise_zeta __________________
____________________________________________________________
Traceback (most recent call l... | true |
2,947,339,395 | [aoti] Better error message when torchbind object is used as a graph input in AOTI | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: export"
] | 6 | CONTRIBUTOR | Summary: Given an explicit error when torchbind object is used as input to AoTI
Test Plan:
```
buck run fbcode//mode/dev-nosan //caffe2/test/inductor:torchbind -- -r test_torchbind_input
```
Differential Revision: D69490915
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @bl... | true |
2,947,337,634 | [ued][wan][Dynamo] Graph break on tensor slicing | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Doc - [docs.google.com/document/d/1Mx90_1BSc_t12vIhw4eApMMiwvmzZKNShPGXUcjMU-o/edit?tab=t.0#heading=h.143elfb7ki36](https://docs.google.com/document/d/1Mx90_1BSc_t12vIhw4eApMMiwvmzZKNShPGXUcjMU-o/edit?tab=t.0#heading=h.143elfb7ki36)
![Image](https://github.com/user-attachments/assets/5ba0df5a-... | true |
2,947,329,717 | [ued][wan] nonstrict_trace does not support None inputs | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: aotdispatch",
"module: pt2-dispatcher"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Doc - [docs.google.com/document/d/1Mx90_1BSc_t12vIhw4eApMMiwvmzZKNShPGXUcjMU-o/edit?tab=t.0#heading=h.143elfb7ki36](https://docs.google.com/document/d/1Mx90_1BSc_t12vIhw4eApMMiwvmzZKNShPGXUcjMU-o/edit?tab=t.0#heading=h.143elfb7ki36)
![Image](https://github.com/user-attachments/assets/da73255b-... | true |
2,947,326,744 | [ued][wan] Dynamic shape issue with tolist | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Doc - https://docs.google.com/document/d/1Mx90_1BSc_t12vIhw4eApMMiwvmzZKNShPGXUcjMU-o/edit?tab=t.0#heading=h.143elfb7ki36
I tried this manual - https://docs.google.com/document/d/1HSuTTVvYH1pTew89Rtpeu84... | true |
2,947,255,042 | AOTI freezing: fix test issues and enable by default | benjaminglass1 | open | [
"open source",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149961
* #148773
* #144293
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,947,229,679 | attn_implementation="eager" Buggy on Blackwell | Oseltamivir | closed | [
"high priority",
"triage review",
"needs reproduction",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 4 | NONE | ### 🐛 Describe the bug
```
tokenizer, model, image_processor, max_length = load_pretrained_model(
pretrained_model, None, model_name, device_map=device_map, attn_implementation="eager",
)
```
Causes model(LLaVA-Video-7B-Qwen2) to output "!!!!!!!" tokens
Fixed with `attn_implementation="spda"`
### Vers... | true |
2,947,217,636 | [inductor] Add more typing to _inductor/ir.py | rec | closed | [
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149959
* #149958
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,947,217,398 | [inductor] Add typing to _inductor/ir.py | rec | open | [
"oncall: distributed",
"module: rocm",
"module: cpu",
"open source",
"NNC",
"ciflow/trunk",
"release notes: quantization",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: distributed (checkpoint)",
"module: compiled autograd"... | 25 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149958
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd @jgong5 @mingfeima @XiaobingSuper @sanchiti... | true |
2,947,186,512 | [ued] Prohibitive warm start latency | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: inductor",
"module: compile-time"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
We observed many models with large warm compile time latency. This is bad for users who are not using inference servers like LLM, and run queries on a new process everytime.
* Flux - https://docs.google.com/document/d/1tKg4JQQchFfAStjvV9EpZq-VEiUUmf5GvS4VHh9pDOI/edit?tab=t.0
* Seen in https://... | true |
2,947,179,705 | [ued][flux][dynamo] Wrong error message with dynamo.disable | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Even when user decorates a function with disable, Dynamo gives wrong error message. Should be easy to repro.
UED Model doc - https://docs.google.com/document/d/1tKg4JQQchFfAStjvV9EpZq-VEiUUmf5GvS4VHh9pDO... | true |
2,947,123,596 | [MPS][BE] Add `c10/metal/common.h` | malfet | closed | [
"Merged",
"topic: not user facing",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149955
That could be shared between host and metal code
So far put only one constant, which is a maximum number of tensor dimentions | true |
2,947,122,254 | Skip cxxabi check for s390x | AlekseiNikiforovIBM | closed | [
"open source",
"Merged",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 3 | COLLABORATOR | On s390x gcc 14 is used because it contains fix for interaction between precompiled headers and vectorization builtins. This fix is not available in earlier gcc versions. gcc-14 uses ABI19, but check still fails, so skip it for now.. | true |
2,947,112,001 | `RuntimeError: UR error` with XPU | idkSeth | open | [
"module: binaries",
"triaged",
"module: xpu"
] | 29 | NONE | ### 🐛 Describe the bug
Tried with the current stable version `torch 2.6.0+xpu` and latest nightly `torch 2.8.0.dev20250321+xpu`.
I get `RuntimeError: UR error` whenever I try to use XPU for various tasks.
Minimal code to reproduce:
```
import torch
t = torch.tensor([0], device="xpu")
t.to(torch.float16)
```
Error... | true |
2,947,063,623 | Removing doc references to PRE_CXX11_ABI. | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | Fixes #149550
cc @svekars @sekyondaMeta | true |
2,947,063,502 | [MPS] `torch.fmax`/`torch.fmin` produce garbage for mixed dtypes | malfet | closed | [
"triaged",
"module: correctness (silent)",
"module: mps"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
For example see
```
%python -c "import torch;print(torch.rand(3, device='mps').fmax(torch.arange(3., device='mps', dtype=torch.half)))"
tensor([0.8821, 0.9714, 0.2126], device='mps:0')
% python -c "import torch;print(torch.rand(3, device='mps').fmax(torch.arange(3., device='mps', dtype=torch.fl... | true |
2,947,035,476 | Use statically known true in should_decompose_mm | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149950
This meta function is causing recompiles for large ads runs due to overguarding: https://www.internalfb.com/ai_infra/job_inspector/guided/pt2_compile?jobName=aps-ig_fm_v4_pt2_on-6e0a734dcc&jobVersion=0&jobAttempt=0
If we... | true |
2,947,029,419 | [TESTING] triton WS version ee6a03d19db0de2148c2604994e0256eeaefc5bc | davidberard98 | open | [
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"ciflow/inductor-periodic"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149949
| true |
2,947,011,516 | Test whether origin/main CI is broken | ahmadsharif1 | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
2,946,957,897 | Dont exclude constant_pad_nd in prologue fusion | eellison | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149947
Originally, I excluded constant_pad_nd from fusing to be conservative on compilation time. But, on benchmarking, you do occasionally get speedups by fusing it. Also includes a fix for making single, contiguous dep for prologu... | true |
2,946,891,679 | [Async TP] Fuse matmul-reduce-scatters when reduce scatters have multiple users, and save fused node for backward instead of reduce_scatter node | danielvegamyhre | closed | [
"oncall: distributed",
"Merged",
"release notes: distributed (pipeline)",
"ciflow/mps",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 4 | CONTRIBUTOR | Fixes #149876
## Stack
- [previous PR in stack] https://github.com/pytorch/pytorch/pull/149247
## TL;DR
This PR implements support in async TP for saving the reduce-scatter result for backward, which previously would break the torchtitan AC policies: no AC, per op SAC, and per layer SAC.
## Context
In torch... | true |
2,946,725,309 | Add triton as dependency to CUDA aarch64 build | pytorchbot | closed | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Aarch64 Triton build was added by: https://github.com/pytorch/pytorch/pull/148705
Hence add proper contrain to CUDA 12.8 Aarch64 build
Please note we want to still use:
```platform_system == 'Linux' and platform_machine == 'x86_64'```
For all other builds.
Since these are prototype binaries only used by cuda 1... | true |
2,946,698,348 | include cudagraph skip reasons in tlparse output | bdhirsh | open | [
"triaged",
"module: cuda graphs",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | here's a repro:
```
import torch
torch._dynamo.config.capture_dynamic_output_shape_ops = True
@torch.compile(mode='reduce-overhead')
def f(x):
y = x.nonzero()
return y
x = torch.randn(16, device='cuda')
out = f(x)
```
and the corresponding tlparse: https://manifold.edge.x2p.facebook.net/v0/read/tree/logs/hir... | true |
2,945,929,668 | [BE] Replace XPU support packages installation to offline mode in Linux CI/CD | pytorchbot | closed | [
"open source",
"topic: not user facing",
"ciflow/xpu"
] | 6 | COLLABORATOR | To ensure the build environment is stable | true |
2,945,783,704 | Add `load_state_dict` hint doc about invoke order work with lr_scheduler | zeshengzong | open | [
"triaged",
"open source",
"release notes: optim"
] | 3 | CONTRIBUTOR | Fixes #119168
## Test Result
| true |
2,945,675,646 | SEGV in static destructors when Vulkan is enabled | yurivict | open | [
"needs reproduction",
"module: crash",
"triaged",
"module: vulkan"
] | 2 | NONE | ### 🐛 Describe the bug
SEGV in the end when torch.is_vulkan_available() is called.
Crash is in static destructors:
```
(gdb) bt
#0 0x000000008f16daa0 in ?? ()
#1 0x000000002c678124 in __cxa_finalize (dso=dso@entry=0x0) at /disk-samsung/freebsd-src/lib/libc/stdlib/atexit.c:237
#2 0x000000002c6786bc in exit (status... | true |
2,945,577,481 | [ONNX] Export generates unnecessary _aten_layer_norm_onnx wrapper for LayerNorm operation | novikov-alexander | closed | [
"module: onnx",
"triaged"
] | 3 | NONE | When attempting to convert a PyTorch model containing the `torch.nn.LayerNorm` operation to ONNX format, I observed different graph representations depending on the value of the `dynamo` parameter in `torch.onnx.export`.
**Expected behavior:**
- When `dynamo=False`, the exported ONNX graph correctly represents the `La... | true |
2,945,548,056 | Make `Adam`, `AdamW` work with nonzero-dim Tensor betas | zeshengzong | open | [
"triaged",
"open source",
"release notes: optim"
] | 1 | CONTRIBUTOR | Fixes #147921
## Changes
- Convert tensor `betas` using `_to_scalar`
- Change annotation of `betas` param
- Change param type in docs
## Test Result
```bash
pytest -s test/test_optim.py -k test_tensor_lr -vv
```
![image](https://github.com/user-attachments/assets/312ee045-1e8b-4789-aa6e-ba63e6df7e81... | true |
2,945,542,651 | there is some confusion of when the parameters of module have grad, before execute the function register_full_backward_hook or after it | l1351868270 | closed | [] | 1 | NONE | ### 🐛 Describe the bug
I write some code to test the register_full_backward_hook, according to my understanding. after backward, the register function of register_full_backward_hook will execute. But, when i write some test code, the result conflict my understood.
```
import torch
import torch.nn as nn
batch = 1
in... | true |
2,945,540,112 | torch.inverse can't export onnx opset16 | Lucky-BenXie | open | [
"needs reproduction",
"module: onnx",
"triaged"
] | 4 | NONE | ### 🐛 Describe the bug
torch.inverse can't export onnx when opset_version == 16
### Versions
111 | true |
2,945,488,946 | refresh results of benchmarks | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149936
while the test was disabled, I put a fix but another win change landed before the test was restored
to it stayed disabled.
<img width="698" alt="Screenshot 2025-03-24 at 6 26 36 PM" src="https://github.com/user-attachments... | true |
2,945,451,498 | update aotinductor doc for XPU support | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | as title. Since the AOTInductor feature starting from 2.7 works on Intel GPU, add the related contents into its doc. | true |
2,945,443,564 | inconsistant behavior to pass tensor/tensor_list from torch.distributed module to cpp API | sanshang-nv | open | [
"oncall: distributed",
"triaged"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
Inconsistant behavior to pass tensor/tensor_list from `torch.distributed` module to cpp implementation. Some wrap tensor/tensor list with one more list, but some don't. This causes inconsistant format in dumped Execution Trace.
For example:
https://github.com/pytorch/pytorch/blob/5a7588f1832a8... | true |
2,945,442,115 | Add XPU and SYCL Merge Patterns | EikanWang | closed | [
"open source",
"Merged",
"topic: not user facing"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149933
As the title
| true |
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