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 |
|---|---|---|---|---|---|---|---|---|
2,986,662,759 | [map] make proxy mode re-dispatch to fake key | ydwu4 | open | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ci-no-td"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150971
* __->__ #151034
* #150962
| true |
2,986,643,209 | [Inductor] add support for disabling atomic adds | mlazos | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 6 | CONTRIBUTOR | As title
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,986,530,792 | make einsum unbacked friendly | ColinPeppler | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 14 | CONTRIBUTOR | cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,986,472,721 | Reapply "ProcessGroupGloo: support lazy_init (#150801)" | d4l3k | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 7 | MEMBER | This reverts commit 73f3d6d9aaa128d9917e8b3790933ba2855066cc.
Reapplies #150801
Test plan:
See #150801
submodule
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab | true |
2,986,466,721 | Unexpected memory usage in FSDP 2 Hybrid Sharding (HSDP) | Craigacp | open | [
"oncall: distributed",
"triaged",
"module: fsdp"
] | 0 | NONE | ### 🐛 Describe the bug
FSDP 2 & torch.distributed.checkpoint has unexpected additional memory usage when saving, which caused our jobs to fail. I'm not clear if this is something I've misconfigured (our stack is built on pytorch & HuggingFace but we're not using HF's trainer or accelerate), or if this is intended beh... | true |
2,986,432,635 | [fx] Filter stacktrace | angelayi | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Filtering out the stacktrace so that the stacktrace on nodes when using fx.Tracer looks nicer. I just copied the filtering we have in [proxy_tensor.py](https://github.com/pytorch/pytorch/blob/6720d2396966c815463d90dd24fcae50b8f7fa2f/torch/fx/experimental/proxy_tensor.py#L1903-L1931).
Previously the stacktrace looked... | true |
2,986,428,845 | Allow OpaqueTensorImpl to be used for views | PatriceVignola | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Summary:
When creating an `OpaqueTensorImpl`, currently there's only an option to create it for a non-view tensor, but it can be useful to create one for view tensors as well.
View tensors should contain the same autograd parameters as the original tensor, whereas non-view tensors get created with whatever `inference_... | true |
2,986,392,927 | Add size/strides/alignment assertions for cpp_wrapper | shunting314 | open | [
"triaged",
"oncall: pt2",
"module: inductor",
"oncall: export",
"module: aotinductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
_No response_
### Error logs
_No response_
### Versions
Inductor generates size/strids/alignement assertions in the generated code to make sure the assumption made at compile time is met at runtime. (check [source code](https://github.com/pytorch/pytorch/blob/1250106630f1ba430de937b5606367... | true |
2,986,375,337 | Back out "[AOTI] Always use oss schema for ExternKernelNodes serialization" | yiming0416 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: export"
] | 6 | CONTRIBUTOR | Summary: Revert for FC breaking
Test Plan: CI
Differential Revision: D72802075
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,986,368,181 | [easy] Add cache bypass traceback information to cache_info on autograd_cache_bypass | jamesjwu | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 12 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151025
This will help us better debug pickling errors, etc, in internal models | true |
2,986,366,101 | [ONNX] Add asdict method to VerificationInfo class | justinchuby | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: improvements"
] | 4 | COLLABORATOR | This pull request introduces a new method to convert `VerificationInfo` objects to dictionaries and includes a corresponding test to ensure the method works correctly.
| true |
2,986,255,318 | Do not generate long log messages for suppressed data dependent errors. | laithsakka | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor",
"ci-no-td"
] | 48 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151023
TORCH_LOGS="all" python test/test_dynamic_shapes.py -k test_guard_or_true
before:
<img width="1065" alt="Screenshot 2025-04-10 at 9 55 27 AM" src="https://github.com/user-attachments/assets/3ee20de0-2902-4eb1-8ab0-... | true |
2,986,238,947 | Add basic unit test and noop config | Lucaskabela | closed | [
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150978
* #150885
* __->__ #151022
Tidy tests:
Adding initial config option
lintrunner
Minor renaming
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kad... | true |
2,986,197,476 | Add `pad_to_multiple_of` to `pad_sequence` (C++ only) | ringohoffman | open | [
"triaged",
"open source",
"release notes: cpp"
] | 2 | CONTRIBUTOR | Related:
* https://github.com/pytorch/pytorch/issues/150989
`pad_to_multiple_of=8` should be used to create sequences that take advantage of NVIDIA Tensor Cores when using mixed precision on GPUs with compute capability >= 7.5 (Volta).
| true |
2,986,133,165 | [logging] Separate cuda synchronize overhead in autotuning | masnesral | closed | [
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151020
Summary: In order to more accurately debug the overhead of autotuning (and pad_mm), explicity do a cuda.synchronize before benchmarking and time that.
Test Plan: See internal test plan here: https://fburl.com/f365xfcj
cc @vo... | true |
2,986,108,133 | DISABLED test_parity__foreach_acos_fastpath_inplace_cuda_float64 (__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_parity__foreach_acos_fastpath_inplace_cuda_float64&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40312895319)... | true |
2,986,722,431 | [release] CPU perf benchmark latency increase for 2.6->2.7 on c5.24xlarge and A100 instances | atalman | open | [
"module: performance",
"oncall: releng",
"module: cpu",
"triaged",
"module: intel",
"topic: performance"
] | 8 | CONTRIBUTOR | Running torchbench userbenchmarks for CPU I see following results from different runs:
On C5.24xlarge CPU latency increase 10-30% . Please note we have to up to ~8% for noise. However looks like the signal we are getting is clear.
Running workflow:
https://github.com/pytorch/benchmark/blob/perf-release-2.7/.github/w... | true |
2,986,031,995 | [inductor] Triton generated kernel int -> float8 fails | IvanKobzarev | open | [
"triaged",
"oncall: pt2",
"module: inductor",
"module: float8"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```
import torch
def fn(x):
return x.to(torch.float8_e5m2)
x = torch.ones(16, dtype=torch.int, device="cuda")
torch.compile(fn)(x)
```
### Error logs
```
ERROR: Triton compilation failed: triton_poi_fused__to_copy_0
def triton_poi_fused__to_copy_0(in_ptr0, out_ptr0, xnumel, XBLOCK : tl.... | true |
2,986,023,152 | [ONNX] Simple torch.nn.Identity onnx export with dynamo=True does not load | knowicki-nvidia | open | [
"module: onnx",
"triaged",
"onnx-triaged"
] | 15 | NONE | ### 🐛 Describe the bug
I got a simple test, where I try to export a simple model to ONNX using Dynamo and load it. Test works on 2.6, but it stopped working on `pytorch:25.03-py3`
```python
import torch
# creating onnx with dynamo
model = torch.nn.Identity()
x = torch.randn(1, 1)
exported_model = torch.onnx.expor... | true |
2,985,973,930 | [Dynamo][Export] Untraceable issues when exporting the Stable Diffusion 3.5 model | YufengShi-dudu | open | [
"oncall: pt2",
"module: dynamo",
"export-triaged",
"oncall: export"
] | 6 | NONE | ### 🐛 Describe the bug
We encountered some untraceable issues when exporting the stable diffusion model.
The package being used is [diffusers library](https://github.com/huggingface/diffusers/tree/main)
The model we are trying to export comes from [StableDiffusion3Pipeline](https://github.com/huggingface/diffusers/b... | true |
2,985,965,664 | update user defined triton kernel table to include strict vs non-strict difference | zou3519 | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"module: user triton"
] | 0 | CONTRIBUTOR | https://pytorch.org/tutorials/recipes/torch_compile_user_defined_triton_kernel_tutorial.html#composability
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @amjames @oulgen @aakhundov @davidberard98 | true |
2,985,882,746 | Propagate callable parameter types using ParamSpec (#142306) | tommyadams5 | closed | [
"oncall: distributed",
"module: typing",
"triaged",
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"release notes: python_frontend",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"suppress-bc-linter",
"release notes: distributed (torchelastic)"
] | 8 | CONTRIBUTOR | Partially addresses #142306
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @ezyang @malfet @xuzhao9 @gramster @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauha... | true |
2,985,795,621 | Revert two recent prologue prs | eellison | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151013
These were landed in a bit of a rush to try to make the release.. Reverting, then will re-land with https://github.com/pytorch/pytorch/pull/151009 applied, and do full benchmark run with max-autotune.
cc @voznesenskym @p... | true |
2,985,787,373 | [Inductor UT] Generalize device-bias code in `test_flex_decoding.py` | anmyachev | closed | [
"triaged",
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/xpu"
] | 3 | COLLABORATOR | cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov
Part of https://github.com/pytorch/pytorch/pull/143553
@etaf @davidberard98 @hoshibara could you take a look? | true |
2,985,777,346 | [Inductor XPU][Quantization] NotImplementedError: 'onednn::qconv_pointwise' | etaf | closed | [
"triaged",
"module: xpu"
] | 2 | COLLABORATOR | ### 🐛 Describe the bug
The quantized conv now does not work on XPU after #150751 landed. The PR renamed the `qconv2d_pointwise` to `qconv_pointwise`.
To reproduce:
```
python test/inductor/test_mkldnn_pattern_matcher.py TestPatternMatcher.test_qconv2d_xpu
```
@ZhiweiYan-96 please fix this issue.
### Versions
pytor... | true |
2,985,690,299 | [torch.export] Exported LSTM cannot be move on CUDA device | Eldalie | closed | [
"oncall: pt2",
"oncall: export"
] | 3 | NONE | ### 🐛 Describe the bug
The following script raises:
```
RuntimeError: Input and hidden tensors are not at the same device, found input tensor at cuda:0 and hidden tensor at cpu
```
except to work without exception.
It is expected to work without raising an exception.
The script exports an LSTM using torch.export, t... | true |
2,985,664,562 | Fix index broadcast | eellison | open | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151009
* #150697
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,985,538,698 | [dynamo] Deprecate enable_cpp_framelocals_guard_eval config variable - default: True | BartlomiejStemborowski | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 9 | CONTRIBUTOR | [dynamo] Deprecate enable_cpp_framelocals_guard_eval config variable - default: True
Reading the feature enabling param `enable_cpp_framelocals_guard_eval `at the CPP level is time consuming and slows down the operation of the dynamo as it is done every time the function using this param is called. Reading the value... | true |
2,985,535,200 | [Openreg][PrivateUse1] Enable CI for openreg | FFFrog | closed | [
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ci-no-td"
] | 28 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151091
* __->__ #151007
Changes:
- move test_openreg.py from test/cpp_extensions/open_registration_extension/ to test/
- update README.md for openreg
- enable CI | true |
2,985,275,083 | [OpenReg][PrivateUse1] Refactoring the csrc files of pytorch_openreg | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"merging"
] | 16 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151091
* #151007
* __->__ #151005
As the title stated.
**Changes:**
- Remove unnecessary header file
- Remove unnecessary registry logic about PrivateUse1HooksRegistry，such as TORCH_DECLARE_REGISTRY, C10_DEFINE_REGISTRY, etc,.
- using stat... | true |
2,985,274,739 | [Openreg][PrivateUse1] Refactor csrc files of Pytorch_openreg | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151091
* #151007
* #151005
* __->__ #151004
* #151000
I want to format and refactor the csrc file of pytorch_openreg. To make the code review clearer and easier to understand, I divide the code refactoring into two parts:
- Part 1: Code fo... | true |
2,985,090,157 | DISABLED test_parity__foreach_acos_fastpath_inplace_cuda_float32 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_acos_fastpath_inplace_cuda_float32&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40300344818)... | true |
2,985,003,477 | NCCL Upgrade to 2.26.2.post1 for CUDA 12 for blackwell support | tinglvv | closed | [
"triaged",
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 13 | COLLABORATOR | Update NCCL for CUDA 12.8 to 2.26.2.post1 for Blackwell support. It's the same 2.26.2 release plus sm_100 and sm_120 support.
Updating for CUDA 12.6 as well since NCCL download now uses one common version read from .ci/docker/ci_commit_pins/nccl-cu12.txt.
Need to upload build to https://download.pytorch.org/whl... | true |
2,984,930,052 | [PT2] Model Functional Regression due to _insert_aten_to_metadata_assert_pass | leslie-fang-intel | closed | [
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 4 | COLLABORATOR | ### 🐛 Describe the bug
Met a functional regression, after searching the guilty commit, we found it's due to https://github.com/pytorch/pytorch/pull/149235
Here is a mini-repro
```
import torch
from torch.export import export_for_training
class Model(torch.nn.Module):
def __init__(self):
super(Model, sel... | true |
2,984,896,184 | [Openreg][PrivateUse1] Improve openreg module capabilities | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 8 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151091
* #151007
* #151005
* #151004
* __->__ #151000
----
- Add more functionalities for openreg in openreg module
- Remove related functionalities from test_cpp_extensions_open_device_registration.py | true |
2,984,894,723 | [XPU] skip a subprocess UT for Windows | LuFinch | closed | [
"open source",
"Merged",
"module: testing",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu",
"module: xpu"
] | 25 | CONTRIBUTOR | This case creates subprocess in a subprocess. In Windows it can't load function at this scenario hence I have to skip it
```
File "C:\ProgramData\miniforge3\envs\lfq\lib\multiprocessing\spawn.py", line 116, in spawn_main
exitcode = _main(fd, parent_sentinel)
File "C:\ProgramData\miniforge3\envs\lfq\lib\multip... | true |
2,984,871,857 | Unsupported operand 118 | radna0 | open | [
"needs reproduction",
"module: serialization",
"triaged"
] | 1 | NONE | This happens when doing `full_model = torch.load(model_path, map_location="cpu", weights_only=True)`
```
File "/home/kojoe/.local/lib/python3.10/site-packages/torch/serialization.py", line 1548, in load
raise pickle.UnpicklingError(_get_wo_message(str(e))) from None
_pickle.UnpicklingError: Weights only load failed... | true |
2,984,817,372 | [OpenReg][PrivateUse1] add device context for OpenReg Module | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151091
* #151007
* #151005
* #151004
* #151000
* __->__ #150997
Add device context support for OpenReg Module, which is depended by
some tests such as ``torch.serialization.default_restore_location`` | true |
2,984,782,985 | [Intel GPU] Avoid using fp32 in sdp math path when benchmark performance. | jianyizh | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 7 | CONTRIBUTOR | sdp on xpu will fallback to math path in some cases (i.e. training). In dynamo benchmark, we prefer to use fp16 for better performance. Although `allow_fp16_bf16_reduction_math_sdp` is under backends.cuda, its implementation is for all device.
I didn't add if device == xpu here, I suppose cuda devices will not run ... | true |
2,984,781,163 | `torch.nn.functional.ctc_loss` inconsistent implementation and docs | zeshengzong | closed | [
"module: nn",
"triaged"
] | 0 | CONTRIBUTOR | ### 📚 The doc issue
When fixing #150835 find out here's an inconsistency between doc and test of `torch.nn.functional.ctc_loss`.
The [doc](https://pytorch.org/docs/stable/generated/torch.nn.functional.ctc_loss.html) describe `targets` param `cannot be blank`
![Image](https://github.com/user-attachments/assets/f80ab... | true |
2,984,768,876 | `torch.export` and `torch.compile` in torch 2.7 RC fails some cases that work with torch 2.6 | ydshieh | closed | [
"triage review",
"module: regression",
"has workaround",
"oncall: pt2",
"module: dynamo",
"oncall: export"
] | 10 | NONE | ### 🐛 Describe the bug
Originally discussed [in transformers](https://github.com/huggingface/transformers/issues/32253#issuecomment-2784714535).
@tugsbayasgalan mentioned it might be a regression of torch 2.7.
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng ... | true |
2,984,686,892 | torch.compile can compile the model that is not runnable under eager mode | syheliel | open | [
"module: error checking",
"triaged",
"oncall: pt2",
"module: fakeTensor",
"module: pt2-dispatcher"
] | 2 | NONE | ### 🐛 Describe the bug
in eager mode, following model will throw `RuntimeError: expected scalar type Float but found Half`. But it will run normally under torch.compile
```
import torch
import math
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
self.query = torch.nn.Linear(64... | true |
2,984,662,402 | [Intel GPU] Enable GQA and different head_dim of value for SDPA | LuFinch | open | [
"module: cpu",
"open source",
"topic: not user facing"
] | 3 | CONTRIBUTOR | In OneDNN v3.7, SDPA doesn't support num_head_q != num_head_kv (aka GQA) and head_dim_qk != head_dim_v.
In OneDNN v3.8, SDPA supports these two scenarios. Enable them in this PR. SDPA UTs pass in local test.
This PR is pending on OneDNN v3.8 upgrade, don't merge now.
cc @jgong5 @mingfeima @XiaobingSuper @san... | true |
2,984,634,503 | DISABLED test_cache_load_function_device_cuda_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True (__main__.TestFxGraphCache) | pytorch-bot[bot] | open | [
"module: rocm",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | Platforms: rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_cache_load_function_device_cuda_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True&suite=TestFxGraphCache&limit=100) and the most recent trunk [workflow l... | true |
2,984,627,482 | Add `pad_to_multiple_of` to `pad_sequence` | ringohoffman | open | [
"open source",
"release notes: cpp"
] | 3 | CONTRIBUTOR | Fixes #150989
`pad_to_multiple_of=8` should be used to create sequences that take advantage of NVIDIA Tensor Cores when using mixed precision on GPUs with compute capability >= 7.5 (Volta).
| true |
2,984,613,544 | Add `pad_to_multiple_of` to `torch.nn.utils.rnn.pad_sequence` | ringohoffman | open | [
"module: nn",
"triaged"
] | 0 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Hugging Face tokenizers support [`pad_to_multiple_of`](https://huggingface.co/docs/transformers/en/main_classes/tokenizer#transformers.PreTrainedTokenizerFast.__call__.pad_to_multiple_of), which allows you to pad your sequence's length to a multiple of a number. This comes from... | true |
2,984,538,852 | Support C shim for customized OP | Valentine233 | open | [
"module: cpp",
"triaged",
"module: custom-operators",
"oncall: pt2",
"module: pt2-dispatcher"
] | 7 | COLLABORATOR | ### 🚀 The feature, motivation and pitch
### Feature
Request the support of C shim for customized OPs defined in non-PyTorch libraries, e.g., TorchAO, TorchVision.
If we run a model with a customized OP using CPP wrapper, the model needs to go from CPP to Python, and then from Python to CPP in order to call this OP, w... | true |
2,984,516,880 | [c10d][tcp_store] Fix connection reset caused by wrong socket close | fduwjj | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150987
While fixing the memory leak in https://github.com/pytorch/pytorch/pull/145757, we accidentally close the socket for the case when nread == 0 and thought it is the case when connection is closed. This is not true. According... | true |
2,984,385,718 | Onnx Export failure : op for aten::full | kraza8 | closed | [
"module: onnx",
"triaged",
"onnx-triaged"
] | 2 | NONE | ### 🐛 Describe the bug
Running into this issue when attempting to export this model into onnx. Model is downloaded from huggingface.
model: "openvla/openvla-7b"
onnx_model_path = "/onnx/model.onnx"
torch.onnx.export(model, (inputs["input_ids"], inputs["attention_mask"], inputs["pixel_values"]), onnx_model_path, in... | true |
2,984,369,390 | DISABLED test_parity__foreach_acos_fastpath_inplace_cuda_float16 (__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_parity__foreach_acos_fastpath_inplace_cuda_float16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40285852744)... | true |
2,984,357,967 | Clean up duplicated code in lr_scheduler | zeshengzong | closed | [
"open source",
"Merged",
"ciflow/trunk",
"suppress-bc-linter",
"release notes: optim"
] | 9 | CONTRIBUTOR | ## Changes
- Remove duplicated code in `ReduceLROnPlateau`
- Remove redundant `noqa` comment
## Test Result
```bash
pytest test/optim/test_lrscheduler.py
```
| true |
2,984,348,065 | [Test CI] Xccl cmake bak | Chao1Han | open | [
"open source",
"ciflow/xpu"
] | 4 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
2,984,336,367 | [CI][CUDA] xfail grouped gemm unit tests on blackwell | nWEIdia | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | COLLABORATOR | On SM100OrLater, Expect failures like:
RuntimeError: torch._grouped_mm is only supported on CUDA devices with compute capability = 9.0
To execute this test, run the following from the base repo dir:
python test/test_matmul_cuda.py TestMatmulCudaCUDA.test_grouped_gemm_3d_2d_strided_False_a_row_major_True_b_r... | true |
2,984,320,853 | Add check for ctc_loss targets param | zeshengzong | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: nn"
] | 11 | CONTRIBUTOR | Fixes #150835
## Test Result
```python
# cuda
>>> import torch
>>> import torch.nn.functional as F
>>> device = "cuda" # "cpu" is fine
>>> num_classes = 4
>>> log_probs = torch.rand(0, 0, num_classes, device=device)
>>> targets = torch.tensor([], device=device, dtype=torch.long)
>>> input_lengths = to... | true |
2,984,317,658 | Torch compile issue, AttributeError: 'NoneType' object has no attribute 'store_cubin' | shahizat | open | [
"triaged",
"oncall: pt2",
"module: inductor",
"Blackwell"
] | 4 | NONE | ### 🐛 Describe the bug
Hello,
I successfully built the sgl-kernel(https://github.com/sgl-project/sglang/tree/main/sgl-kernel) with sm_120 (NVIDIA RTX 50 series) and CUDA 12.8, but encountered the following issue when running sglang.launch_server command using `--enable-torch-compile`. Please help.
Suspicious log
... | true |
2,984,308,251 | [CI][CUDA][UCC] Update test_c10d_ucc.py - remove xfailIfLinux because it now succeeds | nWEIdia | open | [
"oncall: distributed",
"open source",
"ciflow/trunk",
"topic: not user facing"
] | 2 | COLLABORATOR | pytest -v test/distributed/test_c10d_ucc.py -k test_save_load
============================================================================================== test session starts ==============================================================================================
platform linux -- Python 3.12.3, pytest-8.1... | true |
2,984,265,452 | Turn on for export and add export specific tests | Lucaskabela | closed | [
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150978
* #150885
* #151022
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,984,225,742 | Gracefully handle optree less than minimum version | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150956
Summary:
- We are saying the minimum version of pytree that PyTorch can use is
0.13.0
- If a user imports torch.utils._cxx_pytree, it will raise an
ImportError if optree doesn't exist or exists and is less than the
minim... | true |
2,984,216,294 | [export] check tuple length mismatch for dynamic_shapes spec | pianpwk | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: export"
] | 4 | CONTRIBUTOR | Summary: weren't checking this
Test Plan: test_export
Differential Revision: D72761995
| true |
2,984,214,323 | Fix `torch.autograd.backward` `inputs` validation | ValerianRey | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: autograd",
"module: dynamo"
] | 23 | CONTRIBUTOR | - Fixes #150883
- Fixes #70504
This is my first PR to pytorch, so please tell me if I'm forgetting anything.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,984,212,598 | feature: tlparse summary | zou3519 | open | [
"module: logging",
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | I was debugging https://github.com/pytorch/pytorch/issues/150714. I wanted to know "what custom operators does deepseek-v3 x sglang use?"
My [tlparse](https://manifold.edge.x2p.facebook.net/v0/read/tree/logs/.tmpE6JVUu/rank_7/index.html?bucketName=tlparse_reports&apiKey=tlparse_reports-key&withPayload=1&timeoutMsec=10... | true |
2,984,197,278 | [cutlass backend] Add and fix logs, fix types, and make cutlass generator only generate GEMM | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150973
Differential Revision: [D72760205](https://our.internmc.facebook.com/intern/diff/D72760205/)
We hardcoded to only use GEMM anyway.
This also raises the problem with high instantiation level. As the instantiation level ... | true |
2,984,191,248 | Escape hatch: way to dynamically add or remove tags from custom operators | zou3519 | open | [
"triaged",
"module: custom-operators",
"oncall: pt2",
"module: pt2-dispatcher",
"internal ramp-up task"
] | 1 | CONTRIBUTOR | this is extremely useful during debugging and as a general workaround tool for when you cannot touch the definition of the custom operator or its usage in a model
cc @chauhang @penguinwu @bdhirsh @BoyuanFeng | true |
2,984,135,073 | [map] add inductor support by lowering to while_loop | ydwu4 | open | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150971
* #151034
* #150962
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,984,128,354 | [CUDA][TF32] Account for TF32 in `test_alexnet_prefix` | eqy | closed | [
"module: cuda",
"open source",
"Merged",
"module: tf32",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Mainly seems to be an issue on Blackwell with e.g.,
```
Mismatched elements: 1 / 746496 (0.0%)
Greatest absolute difference: 0.005461275577545166 at index (2, 32, 11, 9)
```
cc @ptrblck @msaroufim @zasdfgbnm @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @j... | true |
2,984,125,894 | c10d/Store: add queues | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 8 | MEMBER | This adds queue operations as described in https://github.com/pytorch/pytorch/issues/150943.
This works by adding two new operations `queue_push` and `queue_pop`. The semantics are designed to be blocking with a timeout. Pushing will always succeed as the queue is infinite size. Popping will first call `wait` until ... | true |
2,984,125,231 | move set_rotate_method to public namespace | XilunWu | open | [
"oncall: distributed",
"ciflow/inductor",
"module: context parallel",
"release notes: context parallel"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150968
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,984,082,159 | [MPS] `where`: silent incorrectness when cond is not contiguous | qqaatw | closed | [
"triaged",
"module: correctness (silent)",
"module: mps"
] | 4 | COLLABORATOR | ### 🐛 Describe the bug
```python
device = "mps"
diff = torch.tensor([[True, True], [True, True]], dtype=torch.bool)
diff = diff.T
target = torch.tensor([[0, 0], [0, 1]])
rcpu = torch.where(diff, target, 0)
diffmps = diff.to(device)
targetmps = target.to(device)
rmps = torch.where(diffmps, targetmps, 0)
print(rc... | true |
2,984,024,907 | c10d/Store: add clone feature | d4l3k | closed | [
"oncall: distributed",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: distributed (c10d)",
"ci-no-td"
] | 8 | MEMBER | This adds a new `clone()` method to Store which will return a new Store instance that can be used from a different thread.
This is intended to better support multiple threads with stores such as when ProcessGroupNCCL needs a store to do error propagation.
Related issue: https://github.com/pytorch/pytorch/issues/1... | true |
2,984,009,422 | [dynamo] unpack sequence lazily for list extend/deque extendleft | williamwen42 | closed | [
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150965
Fixes https://github.com/pytorch/pytorch/issues/133063.
We were unpacking generators/iterators eagerly when we should be unpacking them one-by-one.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingS... | true |
2,983,997,133 | Add additional MacOS test runners for MPS | skotapati | open | [
"triaged",
"open source",
"topic: not user facing",
"module: mps",
"ciflow/mps"
] | 11 | COLLABORATOR | Add additional Mac MPS test runners, as part of an effort to eventually add all supported Mac configs
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen | true |
2,983,973,843 | [ued] `torch.compile` yields lower latency when compiling transformer blocks only for ComfyUI GGUF Flux | StrongerXi | open | [
"triaged",
"oncall: pt2",
"empathy-day"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Repro is a bit hard since ComfyUI is a GUI. I'll look into this.
### Error logs
_No response_
### Versions
main.
cc @chauhang @penguinwu | true |
2,983,972,431 | [map] always turn on dynamo for map | ydwu4 | closed | [
"Merged",
"Reverted",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"keep-going",
"ci-no-td"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150971
* #151034
* __->__ #150962
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,983,971,050 | [ued] `torch.compile` cause more than 2x slow down with HF diffuser GGUF Auraflow | StrongerXi | open | [
"triaged",
"oncall: pt2",
"empathy-day"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Repro:
```python
import torch
from diffusers import (
AuraFlowPipeline,
GGUFQuantizationConfig,
AuraFlowTransformer2DModel,
)
transformer = AuraFlowTransformer2DModel.from_single_file(
"https://huggingface.co/city96/AuraFlow-v0.3-gguf/blob/main/aura_flow_0.3-Q2_K.gguf",
qu... | true |
2,983,970,321 | DISABLED test_parity__foreach_acos_fastpath_inplace_cuda_complex64 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_acos_fastpath_inplace_cuda_complex64&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40274150586).
O... | true |
2,983,970,118 | DISABLED test_linalg_solve_triangular_large_cuda_complex128 (__main__.TestLinalgCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"module: linear algebra",
"skipped"
] | 2 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_linalg_solve_triangular_large_cuda_complex128&suite=TestLinalgCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40265201646).
Ove... | true |
2,983,924,193 | [graph partition] support graphsafe_run_with_rng_state | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Prior to this PR, `rng_state` is in `V.graph.graph_inputs` but not in read_writes of any IRNode. As a result, it is not identified as a partition inputs:
```python
def partition_0(args):
primals_2, primals_1 = args
...
buf0 = torch.ops.higher_order.graphsafe_run_with_rng_state(torch.ops.aten.rand.defau... | true |
2,983,877,925 | [profiler] don't disable CUPTI_LAZY_REINIT for cuda >= 12.6 | davidberard98 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: profiler",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150957
Credit to @mgmtea who wrote the initial version of this PR: https://github.com/pytorch/pytorch/pull/146604
Context: CUPTI is the NVIDIA library that Kineto uses for collecting GPU-side info during profiling. The intended u... | true |
2,983,877,314 | Gracefully handle optree less than minimum version | zou3519 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"topic: binaries"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150956
Summary:
- We are saying the minimum version of pytree that PyTorch can use is
0.13.0
- If a user imports torch.utils._cxx_pytree, it will raise an
ImportError if optree doesn't exist or exists and is less than the
minim... | true |
2,983,837,988 | Fix issue in optimized_add issue: make_optimized should be called on non args only | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150955
PR https://github.com/pytorch/pytorch/pull/149665 did a change to the optimized_add that is causing an issue internally.
In general make_optimized should be only be called with valid new_args, new_args can become None
whe... | true |
2,983,765,030 | [dynamo][fsdp] Do not consider fsdp modules as specialized | anijain2305 | open | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | As Title
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,983,754,063 | Update triton wheel build, setuptools pin | pytorchbot | closed | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Observing failure in release workflow:
https://github.com/pytorch/pytorch/actions/runs/14346340202/job/40216804374
```
Traceback (most recent call last):
File "/opt/python/cp311-cp311/lib/python3.11/site-packages/wheel/bdist_wheel.py", line 11, in <module>
from setuptools.command.bdist_wheel import bdist_w... | true |
2,983,749,759 | Add some autograd producer consumer stream sync tests | soulitzer | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151079
* __->__ #150952
Thanks @ngimel and @albanD for some ideas on test cases
cc @majing921201 @gujinghui @guangyey
| true |
2,983,724,403 | [Feature Request] Implement complex.pow(2) as complex * complex on GPU | kheyer | open | [
"triaged",
"module: complex",
"enhancement"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
To compute powers of complex numbers on GPU, pytorch [currently uses](https://github.com/pytorch/pytorch/blob/d3a2872c676b1c67ee47170422f247d429e22241/aten/src/ATen/native/cuda/PowKernel.cu#L32) the identity `pow(a, b) = exp(log(a) * b)`.
This can lead to numeric issues. For e... | true |
2,983,711,701 | [ONNX] Migrate DORT to use the new exporter | justinchuby | open | [
"open source",
"release notes: onnx"
] | 1 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,983,662,018 | Fix 32-bit indexing overflows in ReducedPrecisionGemV | malfet | closed | [
"module: cpu",
"Merged",
"ciflow/trunk",
"release notes: linalg_frontend"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150949
By chaining `lda` type from `int` to ~~`long`~~ `int64_t`
Add regression test (but probably restrict it to CPUs (or may be skip float32 testing on GPUs)
Fixes https://github.com/pytorch/pytorch/issues/150637
cc @jgo... | true |
2,983,617,659 | Add real_tensor to the FakeTensor in node.meta["val"] | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: export"
] | 7 | CONTRIBUTOR | Summary: We need real_tensor on the FakeTensor in node.meta["val"] in order to aot_compile the draft exported programs. Otherwise, we cannot propagate real tensors even when fake_mode.propagate_real_tensors = True.
This also fixes real tensor propagation in `run_decomposition()`.
Test Plan:
```
buck2 run @mode... | true |
2,983,614,783 | Add complex logaddexp2 | zklaus | open | [
"module: cpu",
"open source",
"topic: not user facing"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150947
* #150946
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,983,614,589 | Add complex logaddexp | zklaus | open | [
"open source",
"topic: not user facing"
] | 3 | COLLABORATOR | This aims to fill a gap in the cuda coverage for complex dtypes, namely it adds an implementation of the complex `logaddexp` operator.
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150947
* __->__ #150946
| true |
2,983,589,839 | Torch nightly install fails. | crinard | closed | [
"needs reproduction",
"module: binaries",
"triaged"
] | 3 | NONE | ### 🐛 Describe the bug
Trying to install pytorch nightly on blackwell inside a venv using command
```
pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128 --no-cache-dir --force-reinstall
```
When doing so, I get the following error:
```
pip3 install --pre torch ... | true |
2,983,522,196 | Update auto-tuning support for _scaled_grouped_mm | alexsamardzic | open | [
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150944
1. Enable strided inputs
2. Implement "2d/2d", "3d/2d" and "3d/3d" combinations of inputs
3. Fix non-TMA load variant
4. Replace experimental_device_tensormap_create2d with _experimental_make_tensor_descriptor
5. Fix case... | true |
2,983,510,450 | [RFC][TCPStore] advanced store operations (queues, pub/sub) | d4l3k | open | [
"oncall: distributed",
"feature",
"triaged",
"module: c10d"
] | 0 | MEMBER | TCPStore (and the Store abstraction) currently is a very basic KV store and still provides significant value for doing things like distributed barriers, metadata exchange, etc.
Redis -- a very popular KV store -- has a number of additional operations that allow for making some very complex applications. We want to inc... | true |
2,983,468,823 | all_reduce autograd | jinyouzhi | open | [
"oncall: distributed",
"triaged",
"open source",
"release notes: distributed (c10d)"
] | 3 | CONTRIBUTOR | This adds `all_reduce_autograd` to the functional_collectives library and follows #123599 & #123989, which is motivated by https://github.com/pytorch/pytorch/issues/58005#issuecomment-2670227180.
Test plan:
```
pytest test/distributed/test_functional_api.py -k Autograd
```
cc @H-Huang @awgu @wanchaol @fegin @f... | true |
2,983,450,220 | [BC-breaking] Set NonStrict as default for export_for_training | gmagogsfm | closed | [
"module: bc-breaking",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: bc breaking",
"release notes: export"
] | 6 | CONTRIBUTOR | Summary:
- Flip default value of `strict` argument from True to False on torch.export.export_for_training API
- All callsites have been updated to provide this argument explicitly to avoid behavior change.
- If you see any breakages, that means you may have a new callsite that is missed, please set `strict=True` explic... | true |
2,983,440,132 | [ONNX] Improve dynamic_axes to dynamic_shapes conversion in exporter | titaiwangms | open | [
"module: onnx",
"triaged",
"onnx-triaged"
] | 0 | COLLABORATOR | To improve the backward compatibility of torch.onnx.export dynamo=True/False (torchscript-based and torch.export-based), dynamic_axes needs to be converted to dynamic_shapes.
ONNX has a naive approach to convert dynamic_axes to dynamic_shapes.
https://github.com/pytorch/pytorch/blob/6fb089f2a2eea75a45ac2340f0e68736524... | true |
2,983,332,113 | [ONNX] Cannot export Depth-Anything-v2 (likely `interpolate_pos_encoding_new` function) | FabianSchuetze | closed | [
"module: onnx",
"triaged",
"oncall: pt2"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
I'm trying to export the depth anything model and made a few changes to the codebase. One main problem that I identified was the `interpolate_pos_encoding` function, https://github.com/DepthAnything/Depth-Anything-V2/blob/main/depth_anything_v2/dinov2.py#L179 . I have replaced that with a varia... | true |
2,983,292,932 | Turn optree warning into error | atalman | open | [
"release notes: devx"
] | 2 | CONTRIBUTOR | Related to: https://github.com/pytorch/pytorch/issues/150889
| true |
2,983,280,432 | update benchamark result due to <1% regression | laithsakka | open | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150937
<img width="1503" alt="Screenshot 2025-04-09 at 9 07 13 AM" src="https://github.com/user-attachments/assets/e16f31b0-c5dc-4dd6-8adb-aac11ed988db" />
PR https://hud.pytorch.org/pr/148104
which is acceptable but we have t... | true |
2,983,270,831 | [dynamo] Allow guards to be dropped with custom filter functions. | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 10 | CONTRIBUTOR | Summary: A follow up of https://github.com/pytorch/pytorch/pull/150689.
Test Plan: test_dynamo -k test_guard_filter_fn
Differential Revision: D72722322
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,983,262,608 | [async TP] Fix handling of case where scatter dim = 0 for 2D output tensor | danielvegamyhre | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | ## Summary of changes
1. Change assertion to a warning, when no all gather or reduce scatter patterns are found, and remove the corresponding unit test. It seems some valid TP graphs may not have any pattern matches, from what I can see.
2. Fix wrong variable name being referenced (`A_with_scatter_dim_0` instead o... | true |
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