id int64 2.74B 3.05B | title stringlengths 1 255 | user stringlengths 2 26 | state stringclasses 2
values | labels listlengths 0 24 | comments int64 0 206 | author_association stringclasses 4
values | body stringlengths 7 62.5k ⌀ | is_title bool 1
class |
|---|---|---|---|---|---|---|---|---|
3,021,264,655 | Fix broken URLs | shoumikhin | closed | [
"oncall: distributed",
"oncall: jit",
"module: cpu",
"module: mkldnn",
"Merged",
"NNC",
"ciflow/trunk",
"release notes: quantization",
"release notes: releng",
"ciflow/mps",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"ciflow/linux-aarch64"
] | 3 | CONTRIBUTOR | cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @mingfeima @XiaobingSuper @ashokei @jingxu10 @jerryzh168 @gujinghui @PenghuiCheng @jianyuh @min-jean-cho @yanbing-j @Guobing-Chen @Xia-Weiwen @snadampal @voznesenskym @penguinwu @zhuhaozhe @blzheng @jiayisunx... | true |
3,021,262,427 | At least one of ROCM_HOME or CUDA_HOME must be None | jithunnair-amd | open | [
"module: rocm",
"open source",
"topic: not user facing",
"ciflow/rocm"
] | 3 | COLLABORATOR | Copied description by @hj-wei from
https://github.com/ROCm/pytorch/pull/1809
> Hi all, I manually generating nvcc to bypass NVIDIA component
checks(Megatron-LM),
see
https://github.com/NVIDIA/Megatron-LM/blob/2da43ef4c1b9e76f03b7567360cf7390e877f1b6/megatron/legacy/fused_kernels/__init__.py#L57
> but it can l... | true |
3,021,246,238 | [CUDA][SDPA] bump fudge factor in `test_sdpa` in `test_nestedtensor` | eqy | closed | [
"module: cuda",
"open source",
"module: nestedtensor",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: sdpa"
] | 6 | COLLABORATOR | Small mismatches on e.g., 4090, A6000/A40
cc @ptrblck @msaroufim @jerryzh168 @cpuhrsch @jbschlosser @bhosmer @drisspg @soulitzer @davidberard98 @YuqingJ | true |
3,021,244,180 | _get_total_norm should use float64 to avoid rounding errors | RishabhSaini | open | [
"triaged",
"open source",
"topic: not user facing"
] | 7 | NONE | When a _NormPartial is Reduced, rounding errors can cause the resulting Tensor to have inconsistent results.
Example:
```
>>> import torch
>>> print(f"{(torch.linalg.vector_norm(torch.tensor([1.0, 1.0]))**2.0 + torch.linalg.vector_norm(torch.tensor([2.0, 2.0]))**2.0)**(1/2):.10f}")
3.1622774601
>>> print(f"{torch... | true |
3,021,232,169 | ReducedPrecisionFloatGemvFastPathKernel: Correctly type parallel_for lambda arguments as int64_t | swolchok | closed | [
"module: cpu",
"Merged",
"ciflow/trunk",
"release notes: linalg_frontend"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152233
* #152232
This plus the previous irangeification PR seem like a better fix for #150637 than #150949 to me -- should make sure we are using 64-bit math for indexing everywhere.
cc @jgong5 @mingfeima @XiaobingSuper @sanchitinte... | true |
3,021,232,122 | irangeify ReducedPrecisionFloatGemvKernel.cpp | swolchok | closed | [
"module: cpu",
"Merged",
"release notes: linalg_frontend"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152233
* __->__ #152232
We should be using irange, especially because we had 32-bit overflow issues in this file recently.
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 | true |
3,021,212,542 | Fix: Consider input defined unbacked during inductor codegen for runtime asserts | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152231
So when we use mark_unbacked the graph will have an unbacked inputs symInt. Right now,
deferred runtime assertions that uses those is never generated.
This PR changes that, such that in the forward graph we consider tho... | true |
3,021,188,876 | [MPS/inductor] Adjust test_to_dtype_mps so that it works on the backend. | dcci | closed | [
"Merged",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 4 | MEMBER | float64 isnt' supported for MPS, but we can still test the functionality with another type.
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chau... | true |
3,021,177,394 | [BE] Migrate dtype_abbrs into one location | malfet | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"release notes: python_frontend",
"topic: bug fixes",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Namely `torch.utils._dtype_abbrs.dtype_abbrs`
Before that it was defined in various forms of completeness in
https://github.com/pytorch/pytorch/blob/c02edba86388d1f86a78bce99d16c5405b54086e/torch/fx/graph.py#L215,
https://github.com/pytorch/pytorch/blob/c02edba86388d1f86a78bce99d16c5405b54086e/torch/testing/_inte... | true |
3,021,166,911 | Add `padding="same"` for transposed convolution | Alvaro-Kothe | open | [
"module: cpu",
"triaged",
"open source",
"release notes: nn"
] | 6 | CONTRIBUTOR | This pull requests makes `ConvTranspose*d` and `conv_transpose*d` compatible with the argument `padding="same"`.
I tried to follow the current implementation of the `Conv*d` layer.
Closes #80301, Closes #3867
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 | true |
3,021,143,862 | [inductor][tests] don't test for cpu if you want to use triton backend | henrylhtsang | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/periodic",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152227
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,021,141,629 | NotImplementedError: Could not run 'aten::index.Tensor' with arguments from the 'SparseCUDA' backend. | ringohoffman | open | [
"module: sparse",
"triaged"
] | 3 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
I want to make vectorized selections on a sparse tensor, but it isn't implemented for the `SparseCUDA` backend.
```python
import torch
device = torch.device("cuda:0")
indices = torch.tensor(
[
[0, 1, 2, 3],
[1, 2, 3, 4],
[2, 3, 4, 5]
],
dev... | true |
3,021,132,371 | torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised: ModuleNotFoundError: No module named 'expecttest' | jjh42 | closed | [
"module: regression",
"better-engineering",
"oncall: pt2"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Unfortunately I don't have a clean reproduction but I'm hoping perhaps it might be obvious to someone the underlying change.
I upgrade pytorch nightlies (from 2.8.0.dev20250422+cu128 to 20250428) for some other bugfix reasons.
In pytorch.compile (I haven't managed to make a nice isolated case... | true |
3,021,106,186 | add xfail for distributed tests on Jetson | Fuzzkatt | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | We are hitting distributed import failures on Jetson in test/export/test_export.py tests in NVIDIA internal testing with the recent additions of https://github.com/pytorch/pytorch/pull/146050 and https://github.com/pytorch/pytorch/pull/147417. Instead of simply skipping these tests for Jetson, we are introducing an xfa... | true |
3,021,092,983 | Compute Capability Misrecognition on NVIDIA Force RTX 50Ge70 Ti (Blackwell Architecture) | kaworukevin | closed | [
"module: cuda",
"module: third_party"
] | 2 | NONE | ### 🐛 Describe the bug
Dear PyTorch Team,
I am encountering an issue with PyTorch where my GPU, an NVIDIA GeForce RTX 5070 Ti (Blackwell architecture, expected Compute Capability sm_90), is being misidentified as sm_120. This is causing compatibility issues when running applications like FramePack, resulting in th... | true |
3,021,077,739 | DISABLED test_remote_cache_load_function_device_cuda_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False (__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_remote_cache_load_function_device_cuda_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False&suite=TestFxGraphCache&limit=100) and the most recent trunk [workflow lo... | true |
3,021,077,684 | DISABLED test_pending_fusions_multiple (__main__.TestPrologueFusion) | 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_pending_fusions_multiple&suite=TestPrologueFusion&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41181061777).
Over the past 3 hours, it h... | true |
3,021,075,754 | [C10D] Allow NCCL single P2P ops to use parent/collective communicator | Edenzzzz | open | [
"oncall: distributed",
"triaged",
"module: nccl"
] | 2 | NONE | ### 🚀 The feature, motivation and pitch
As discussed in some previous PR/RFC (https://github.com/pytorch/pytorch/pull/129147, https://github.com/pytorch/pytorch/issues/129140), passing in `device_id` into `init_process_group` will eagerly init the parent NCCL communicator, and subsequent P2P calls will use that inste... | true |
3,021,066,167 | Have compiled autograd config API support nested compilation | xmfan | open | [
"triaged",
"oncall: pt2",
"module: compiled autograd"
] | 0 | MEMBER | ### 🐛 Describe the bug
e.g. in the modded-nanogpt speedrun, we have some custom op that has another torch.compile inside of it. This will raise `RuntimeError: compiled_autograd._enable() requires no threads in backwards()` if we use the config API. Using the context manager is fine in this case, because the nested co... | true |
3,021,060,951 | Require EasyCLA check even when force merging | ZainRizvi | closed | [
"topic: not user facing",
"test-config/xla"
] | 3 | CONTRIBUTOR | Always require EasyCLA to pass before merging | true |
3,021,053,662 | [not for land] functionalization hack to try making mutations on graph input slices more efficient | bdhirsh | open | [
"ciflow/inductor"
] | 2 | CONTRIBUTOR | not for land since this still has silent correctness problems
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152217
| true |
3,021,050,230 | [TF32][CUDA] account for TF32 in `test_linear_autograd` | eqy | closed | [
"module: cuda",
"open source",
"Merged",
"module: tf32",
"ciflow/trunk",
"topic: not user facing",
"matrix multiplication",
"Blackwell"
] | 3 | COLLABORATOR | Abate some more noise seen on blackwell
cc @ptrblck @msaroufim @jerryzh168 @zasdfgbnm | true |
3,021,050,001 | Improve error handling in CachingAutotuner for argument mismatches | ShreyRoy | open | [
"triaged",
"open source",
"module: inductor",
"release notes: inductor"
] | 3 | NONE | Fixes #147690
Adds a check in CachingAutotuner.run() to validate that the number of provided arguments matches the expected number of launcher arguments.
If there is a mismatch, a clear TypeError is raised, specifying the expected and actual argument counts.
This improves the debuggability of kernel launch fail... | true |
3,021,036,298 | [MPS/inductor] Fix the approximation of polygamma for n == 0. | dcci | closed | [
"Merged",
"module: mps",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | MEMBER | Fixes #152205
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,021,032,974 | Outdated install commands | mcandre | open | [
"module: docs",
"triaged",
"actionable"
] | 2 | NONE | Python now recommends using the pip module as opposed to the pip executable, which tends to integrate better with (virtualenv) isolated Python environment sandboxes.
The install commands that this documentation page generates:
https://pytorch.org/get-started/locally/
Should replace `pip3 install`... with `python3 -m... | true |
3,021,025,121 | Have cherry-pick bot always add the current release to the PR | ZainRizvi | open | [
"oncall: releng",
"module: ci",
"triaged"
] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Goal is to make sure that any PR someone attempts to cherry pick gets the release milestone added to it for tracking.
Whenever a cherry-pick is requested on a PR, we should first try to add the current release milestone before attempting the actual cherry-pick (do it in that o... | true |
3,020,997,121 | Mini tutorial for provenance tracking | yushangdi | open | [
"release notes: export"
] | 6 | CONTRIBUTOR | as title | true |
3,020,993,360 | Move mps_linear forward to use MPS kernels directly instead of MPSGraph | jhavukainen | open | [
"triaged",
"open source",
"module: mps",
"release notes: mps",
"ciflow/mps"
] | 1 | COLLABORATOR | This PR moves `mps_linear` to use MPSNDArrays and call into the MPS kernel directly instead of going through MPSGraph. It also adds a caching mechanism for reusing MPS kernels as there is also a small overhead attached to creating the kernel object.
The impact of the improvement is relatively more significant for sm... | true |
3,020,982,686 | [CI] docker images use tags instead of image name | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Change CI docker images to be `ci-image:<image name>-<folder sha>` instead of `<image name>:<folder sha>` so we never have to make a new ecr repo ever again
Pros:
never have to make a new ecr repo ever again
Cons:
if it aint broken, dont fix it?
Don't need to change linux-test images since they use the "full n... | true |
3,020,930,299 | Add support for torch.cuda.FloatTensor() | jijiew | open | [
"module: inductor",
"module: dynamo",
"release notes: dynamo"
] | 4 | CONTRIBUTOR | Fixes #130722
Add support for torch.cuda.FloatTensor()
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,020,906,468 | [invoke_subgraph] Use backward identifier for min-cut parititioning | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 12 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152494
* #152490
* #152384
* #152383
* #152357
* __->__ #152207
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,020,847,690 | [dynamo] remove dead code for DATA_PTR_MATCH | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Summary: Seems this guard is not created anywhere
Test Plan: CI
Differential Revision: D73682084
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,020,786,322 | [MPS/Inductor] polygamma is miscompiled for some inputs | dcci | closed | [
"triaged",
"module: mps",
"oncall: pt2",
"module: inductor"
] | 0 | MEMBER | ### 🐛 Describe the bug
Repro:
```
>>> import torch
>>> torch.special.polygamma(0, torch.tensor([2]))
tensor([0.4228])
>>> torch.special.polygamma(0, torch.tensor([2]).to('mps'))
tensor([0.4228], device='mps:0')
>>> torch.compile(lambda x: torch.special.polygamma(0, x))(torch.tensor([2], device='mps'))
tensor([-inf],... | true |
3,020,730,613 | [MPS] Fix ICE for entr bool instantiation on M1/M2 | malfet | closed | [
"Merged",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147893
* __->__ #152204
By instantiating it implicitly, otherwise attempts to run something like
```
% python3 -c "import torch; print(torch.special.entr(torch.testing.make_tensor(10, dtype=torch.bool, device='mps')))"
```
will fail with
``... | true |
3,020,703,805 | [CUDA][conv3d] bump tolerances for `test_variant_consistency_eager` `conv3d` `complex64` | eqy | closed | [
"module: cuda",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | ~1/1000 1.5e-5 mismatch on A100
cc @ptrblck @msaroufim @jerryzh168 | true |
3,020,698,823 | Speed-up time spent in generating shaped str keys | jhavukainen | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"module: mps",
"release notes: mps",
"ciflow/mps"
] | 3 | COLLABORATOR | Replaces the janky way of using the IntArrayRef to create an NSArray to ask for it to provide its contents in a string format with use of stringstream.
This speeds up the call for getting the key string for caching (or reading from cache) for shaped inputs by ~5x. While the actual wall time, depending on the number... | true |
3,020,693,469 | DISABLED test_reduce_stress_cuda (__main__.ProcessGroupGlooLazyInitTest) | jithunnair-amd | open | [
"module: rocm",
"triaged",
"skipped"
] | 1 | COLLABORATOR | Platforms: rocm
This test was disabled because it failed on the MI300 runners in [151368](https://github.com/pytorch/pytorch/pull/151368): https://github.com/pytorch/pytorch/actions/runs/14502441175/job/40686794743
The `stress_cuda` tests seem to be flaky.
cc @jeffdaily @sunway513 @pruthvistony @ROCmSupport @dllehr-... | true |
3,020,653,804 | [submodule] Update ONNX to 1.18 | cyyever | open | [
"oncall: jit",
"triaged",
"open source",
"NNC",
"ciflow/binaries",
"ciflow/trunk",
"release notes: onnx",
"ciflow/periodic"
] | 8 | COLLABORATOR | ONNX 1.18 is about to release soon. Its third-party module is now updated to RC2 to verify whether PyTorch can use it with necessary changes. After 1.18 has been released, it will be updated to that.
cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel | true |
3,020,642,426 | Synchronize mps backend in the timer | jhavukainen | open | [
"triaged",
"open source",
"release notes: benchmark"
] | 3 | COLLABORATOR | Add synchronization for the MPS op measurements with the timer class in benchmark utils. This enables measuring the true execution time when we wait for the GPU results.
Test output from calling linear op before the change (which ignores waiting for the GPU result):
```
torch.linear time: <torch.utils.benchmark.ut... | true |
3,020,603,537 | [inductor] propagate shapes in CSEVariable | isuruf | open | [
"open source",
"module: inductor",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152198
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,020,603,246 | Add detailed triton kernel logging to tlparse | jamesjwu | open | [
"Merged",
"Reverted",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: AO frontend",
"ci-no-td"
] | 14 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152197
This PR adds detailed logging of each triton kernel we compile, and its autotune result, to every kernel we compile with triton. We add these results to a global variable that we then clear after each triton kernel compile.
... | true |
3,020,548,187 | [ONNX] add converters for sym_min, sym_max | xadupre | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: improvements"
] | 3 | COLLABORATOR | Conversion of Phi4-multimodel-instruct fails because of missing converters for torch.sym_max, and torch.sym_min. | true |
3,020,467,918 | SAC: fix recompute tag propagation for ops with list[tensor] inputs | bdhirsh | closed | [
"Merged",
"ciflow/trunk",
"release notes: autograd",
"module: dynamo",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | There's an "are we compiling" check in SAC, which we rely on to know when to propagate recompute tags during tracing.
This check was a bit brittle, and missed cases where input ops accept list of tensors - I updated it to check if a `FunctionalTensorMode` is active, which should be a 100% reliable way to know if AOT... | true |
3,020,462,474 | SAC: fix recompute tag propagation for ops with list[tensor] inputs | bdhirsh | open | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,020,458,351 | SAC: fix recompute tag propagation for ops with list[tensor] inputs | bdhirsh | open | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,020,413,080 | xpu: get xpu arch flags at runtime in cpp_extensions | dvrogozh | open | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"keep-going",
"ciflow/xpu",
"release notes: xpu",
"module: xpu"
] | 9 | CONTRIBUTOR | This commit moves query for xpu arch flags to runtime when building SYCL extensions which allows to adjust `TORCH_XPU_ARCH_LIST` at python script level. That's handy for example in ci test which gives a try few variants of the list.
CC: @malfet, @jingxu10, @EikanWang, @guangyey
cc @gujinghui @EikanWang @fengyuan14 ... | true |
3,020,288,662 | [`Torch 2.7.0 x Py 3.9`] Incompatible dep versions with networkx | vasqu | closed | [
"triage review",
"oncall: releng",
"module: regression",
"module: third_party"
] | 16 | NONE | ### 🐛 Describe the bug
There seems to be a bug in the new release of torch (2.7.0) when using py 3.9. This is caused by the usage of `networkx` which is not pinned in the dependencies, while it has dropped the support for py 3.9. Example error log from https://github.com/huggingface/transformers/pull/37695
```
Fil... | true |
3,020,240,259 | HUD Dashboard sort by perf speedup doesn't do anything | zou3519 | open | [
"triaged",
"bug",
"module: devx"
] | 3 | CONTRIBUTOR | 
the up arrow next to "perf. speedup" lets me sort by asc or dsc but it doesn't actually change the chart
cc @ZainRizvi @huydhn @clee2000 @pytorch/pytorch-dev-infra | true |
3,020,240,127 | [BE]: Use typing.get_args in torch/types | Skylion007 | closed | [
"open source",
"topic: not user facing"
] | 2 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
3,020,239,775 | The input for layers other than the first layer should be the hidden state from the previous layer. | JinQi-Tang | open | [
"module: nn",
"module: rnn",
"triaged"
] | 0 | NONE | https://github.com/pytorch/pytorch/blame/134179474539648ba7dee1317959529fbd0e7f89/torch/nn/modules/rnn.py#L499
cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki | true |
3,020,212,746 | test(Conv3d): use correct class for `test_Conv3d_module_same_padding` | Alvaro-Kothe | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | The test for the class `Conv3d` is calling `Conv2d`. This PR just ensure that we are testing the correct module. | true |
3,020,205,467 | Unskip index_put in cudagraphs | eellison | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152186
The repro from the original skip in https://github.com/pytorch/pytorch/pull/105439 does not fail. unskip.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisu... | true |
3,020,202,368 | GroupNorm compilation errors on UNet-based architecture on torch >= 2.6.0 | GLivshits | open | [
"module: nn",
"triaged",
"module: norms and normalization",
"oncall: pt2"
] | 0 | NONE | ### 🐛 Describe the bug
New torch versions - new bugs! I've used to cope with compilation issues on the diffusion model architectures from 2.4.0 to 2.5.1 (on which it finally work with TORCHINDUCTOR_LAYOUT_OPTIMIZATION=0), for example https://github.com/pytorch/pytorch/issues/133571.
On 2.7.0 and 2.6.0 an error occurs... | true |
3,020,195,447 | [WIP] New Win Arm64 Runners - User pre installed Visual Studio | iremyux | open | [
"open source",
"topic: not user facing",
"ciflow/binaries_wheel",
"ciflow/binaries_libtorch"
] | 1 | COLLABORATOR | null | true |
3,020,123,984 | write a custom ViewAndMutationmeta.__repr__ | bdhirsh | open | [
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | `ViewAndMutationMeta` can hold a tensor subclass today, when torch.compile is used with tensor subclass graph inputs/outputs.
We also heavily log our `ViewAndMutationMeta` object during compilation when we are running compile with tlparse.
This can be a problem if the subclass we are tracing with either:
(1) does not... | true |
3,019,921,415 | GH200/GB200 NCCL Build Pytorch | johnnynunez | open | [
"module: build",
"triaged",
"module: nccl",
"module: third_party",
"has workaround"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
```bash
[879/3160] Building CXX object c10/test/CMakeFiles/c10_generic_math_test.dir/util/generic_math_test.cpp.o
[880/3160] Building CXX object c10/test/CMakeFiles/c10_tempfile_test.dir/util/tempfile_test.cpp.o
[881/3160] Building C object sleef/src/libm/CMakeFiles/sleefpurec_scalar.dir/sleefs... | true |
3,019,802,239 | IGNORE: Testing OIDC | zxiiro | open | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | This reverts commit 8313bc27f2e1625a16622cb1d88be40c163e4959.
Fixes #ISSUE_NUMBER
| true |
3,019,768,833 | Tighten tolerance of test_vmapvjp_linalg_tensorsolve_cpu_float32 | Flamefire | closed | [
"triaged",
"open source",
"topic: not user facing"
] | 11 | COLLABORATOR | With the optimzation of `solve` using a transposed input this test fails to meet these tolerances but passes without.
@pytorchbot topic: not user facing | true |
3,019,615,353 | [ROCm] Update CUDAPluggableAllocator.h | amd-sriram | closed | [
"oncall: distributed",
"module: rocm",
"module: cpu",
"module: mkldnn",
"open source",
"release notes: quantization",
"release notes: rocm",
"release notes: releng",
"fx",
"module: inductor",
"module: dynamo",
"release notes: inductor (aoti)"
] | 4 | 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 |
3,019,611,575 | Raise an Error when File Not Found in `torch.jit.load()` | ILCSFNO | open | [
"oncall: jit",
"module: error checking",
"actionable"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
The doc of [torch.jit.load()](https://pytorch.org/docs/stable/generated/torch.jit.load.html#torch-jit-load) shows its description as below:
https://github.com/pytorch/pytorch/blob/ad81eeb7c7c906e0cdd04a5cc8fdb9592281c317/torch/jit/_serialization.py#L105-L107
Tried repro below:
### Repro
```py... | true |
3,019,519,917 | Fix instantiate_device_type_tests() for 3rd-party devices | wizzniu | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | For 3rd-party devices now, `` instantiate_device_type_tests()`` with explicitly passing ``str`` obj (rather than `List[str]/Tuple[str]`) to argument ``only_for`` or ``except_for`` would causes unexpected results.
For example, if calling ``instantiate_device_type_tests(TestXXX, globals(), only_for="cpu")``, then it ... | true |
3,019,487,144 | Add description of several params in the basic usage of `torch.min()`, `torch.max()`, `torch.all()` and `torch.any()` | ILCSFNO | open | [
"module: docs",
"triaged",
"actionable"
] | 3 | CONTRIBUTOR | ### 📚 The doc issue
The doc of [torch.min()](https://pytorch.org/docs/stable/generated/torch.min.html#torch-min) shows its description as below three:
https://github.com/pytorch/pytorch/blob/f38dae76ee8dccd60f99bbddb48f2520f436fa1a/torch/_torch_docs.py#L7106-L7111
https://github.com/pytorch/pytorch/blob/f38dae76ee8... | true |
3,019,474,471 | [c10d] Allow split_group to work with non nccl backends | deepshah133 | open | [
"oncall: distributed",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 2 | CONTRIBUTOR | Summary:
Currently things are hardcoded to only work with nccl backend. Extend it
to allow NCCL + custom plugin backend.
The split-specific methods/attributes have not been added to the base
Backend and Options as some of them are specific to backend implementations.
Instead, explicit checks have been added to t... | true |
3,019,307,806 | [Docs] Add Description of `validate_args` for torch.distributions | shink | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"skip-url-lint"
] | 16 | CONTRIBUTOR | Fixes #152165
| true |
3,019,271,933 | `torch._inductor.exc.InductorError: CppCompileError: C++ compile error` after Torch 2.7 Release | BillHuang2001 | closed | [
"module: regression",
"oncall: pt2",
"oncall: cpu inductor"
] | 5 | NONE | ### 🐛 Describe the bug
Following the release of Torch 2.7, we are encountering errors in our CI pipeline.
<details>
<summary>CI history</summary>
Repo: https://github.com/EMI-Group/evox
Since: commit d62696a72e6c6ed161ad2ca840a7bf097d98a2d3, the day torch 2.7 released.
Raw log: [link](https://productionresultssa11... | true |
3,019,266,439 | /usr/local/lib/python3.11/dist-packages/torch/autograd/graph.py:825: UserWarning: grid_sampler_2d_backward_cuda does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True, warn_only=True)'. | flydragon2018 | open | [
"triaged",
"enhancement",
"module: determinism"
] | 0 | NONE | ### 🐛 Describe the bug
/usr/local/lib/python3.11/dist-packages/torch/autograd/graph.py:825: UserWarning: grid_sampler_2d_backward_cuda does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True, warn_only=True)'. You can file an issue at https://github.com/pytorch/pytorch/issue... | true |
3,019,260,888 | Generate test reports for pytest when option is given | Flamefire | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | COLLABORATOR | The argument needs to be appended when test reports should be generated. IS_CI is not necessarily set, so rather check TEST_SAVE_XML instead as in other places where test reports are conditionally enabled.
See also https://github.com/pytorch/pytorch/issues/126523 | true |
3,019,235,083 | DISABLED test_e2e_compile_True_model_type2 (__main__.TestE2ESaveAndLoad) | jithunnair-amd | open | [
"module: rocm",
"triaged",
"skipped"
] | 1 | COLLABORATOR | Platforms: rocm
This test was disabled because it's failing on the [MI300 runners](https://hud.pytorch.org/failure?name=periodic-rocm-mi300%20%2F%20linux-focal-rocm-py3.10%20%2F%20test%20(distributed%2C%201%2C%203%2C%20linux.rocm.gpu.mi300.4.test-2%2C%20module%3Arocm%2C%20oncall%3Adistributed)&jobName=linux-focal-rocm... | true |
3,019,231,126 | DISABLED test_e2e_compile_True_model_type0 (__main__.TestE2ESaveAndLoad) | jithunnair-amd | open | [
"module: rocm",
"triaged",
"skipped"
] | 1 | COLLABORATOR | Platforms: rocm
This test was disabled because it's failing on the [MI300 runners](https://hud.pytorch.org/failure?name=periodic-rocm-mi300%20%2F%20linux-focal-rocm-py3.10%20%2F%20test%20(distributed%2C%201%2C%203%2C%20linux.rocm.gpu.mi300.4.test-2%2C%20module%3Arocm%2C%20oncall%3Adistributed)&jobName=linux-focal-rocm... | true |
3,019,174,785 | Generate test reports for pytest when option is given | Flamefire | closed | [
"oncall: distributed",
"module: cpu",
"module: mkldnn",
"module: amp (automated mixed precision)",
"ciflow/trunk",
"release notes: quantization",
"release notes: releng",
"ciflow/mps",
"module: dynamo",
"ciflow/inductor",
"release notes: distributed (checkpoint)",
"ciflow/linux-aarch64"
] | 2 | COLLABORATOR | The argument needs to be appended when test reports should be generated. `IS_CI` is not necessarily set, so rather check `TEST_SAVE_XML` instead as in other places where test reports are conditionally enabled.
See also https://github.com/pytorch/pytorch/issues/126523
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz33... | true |
3,019,152,638 | Extend compute_global_tensor_shape to multi dimension sharding | dharakk | open | [
"oncall: distributed",
"topic: not user facing",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152166
* #152751
### Summary
`compute_global_tensor_shape` util all gathers shape of the local
tensors from all the ranks and then computes the shape of the global
DTensor based on the device mesh and the placements. Earlier th... | true |
3,019,002,411 | Add Description of `validate_args` in `torch.distributions.` | ILCSFNO | closed | [
"module: distributions",
"triaged"
] | 0 | CONTRIBUTOR | ### 📚 The doc issue
The doc of [torch.distributions.weibull.Weibull()](https://pytorch.org/docs/stable/distributions.html#torch.distributions.weibull.Weibull) shows its description as below:
https://github.com/pytorch/pytorch/blob/a936d596f6f7d2bc2dc47b4b2320208b4908e7f2/torch/distributions/weibull.py#L28-L31
But i... | true |
3,018,977,168 | Less Check on the triangular tensor of `L` in `torch.cholesky_solve()` | ILCSFNO | closed | [
"triaged",
"module: linear algebra"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
The doc of [torch.cholesky_solve()](https://pytorch.org/docs/stable/generated/torch.cholesky_solve.html#torch-cholesky-solve) shows its description as below:
https://github.com/pytorch/pytorch/blob/dda0c952e71a540f7ad8d040e35da727b4d91405/torch/_torch_docs.py#L2660-L2662
For L directly be a t... | true |
3,018,969,617 | [cutlass backend] add addmm and bmm for cutlass backend benchmark | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152163
Copying what @kadeng did.
```
FINAL results...
Experiment group: bmm (BS: 8, 1024x1024, 1024x1024) torch.float16
+-----------------------+--------------------+----------------------+---------------------+
| ... | true |
3,018,959,763 | torch.compile fails in FSDP due to .data assignment with different floating type | kbabiuchx | open | [
"triaged",
"module: fsdp",
"oncall: pt2",
"module: aotdispatch",
"module: dynamo",
"module: pt2-dispatcher"
] | 5 | NONE | ### 🐛 Describe the bug
When using torch.compile, a runtime error is raised:
`TorchRuntimeError: Failed running call_function <method 'set_' of 'torch._C.TensorBase' objects>(*(FakeTensor(..., size=(3,)), FakeTensor(..., size=(3,), dtype=torch.bfloat16)), **{}):
Could not set tensor of type c10::BFloat16 to a tensor... | true |
3,018,943,411 | Fix take_along_dim negative index handling (#146211) | KaaustaaubShankar | open | [
"triaged",
"open source",
"release notes: cpp"
] | 5 | NONE | Fixes: #146211
This PR fixes an issue with `torch.take_along_dim()` not correctly handling negative indices. Previously, using negative values in the `indices` tensor caused an out-of-bounds error. This update wraps indices correctly, matching Python-style indexing semantics.
### 🔧 Changes
- Modified `_take_alo... | true |
3,018,925,038 | [Kineto] Enable OOM observer | mzzchy | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 12 | CONTRIBUTOR | Summary:
# Context:
When memory leak happens, it usually trigger the OOM in the later iterations. The snapshot of full iteration will be huge and hard to interpret.
On CUDA side, they provide OOM observer which generates snapshot when OOM happens with latest 1,500,000 entries for debugging.
In this diff, we want to i... | true |
3,018,883,048 | Add dynamo config to HOP-ify context managers | soulitzer | open | [
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152159
* #152158
```
# Note [Hopifying Context Managers]
#
# If the context manager class has been added to a opt-in dynamo config,
# we will convert it into a generic context manager HOP. When the
# HOP is later called in AO... | true |
3,018,882,968 | Add AC_TRACER Infra TorchDispatchMode key | soulitzer | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152159
* __->__ #152158
Why we need an additional infra mode for the new version of AC?
- For the new version of AC, we want to trace a graph and then replay it (in pieces) during backward. We'd like this graph to have all the user modes ... | true |
3,018,839,573 | [Typing] Enable torch.types.IntLikeType / FloatLikeType / BoolLikeType | shink | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"suppress-bc-linter"
] | 3 | CONTRIBUTOR | ### Changes
Replace `Union[SymInt, int]` and `Union[int, SymInt]` with `IntLikeType`.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
3,018,819,854 | Note some limit in docstring of `padding` in Poolnd | ILCSFNO | closed | [
"module: docs",
"module: nn",
"triaged"
] | 1 | CONTRIBUTOR | ### 📚 The doc issue
The doc of [torch.nn.functional.avg_pool2d()](https://pytorch.org/docs/stable/generated/torch.nn.functional.avg_pool2d.html#torch-nn-functional-avg-pool2d) shows its description as below:
https://github.com/pytorch/pytorch/blob/7f28c03fac11dc3cf37da36def7e0857c331843d/torch/nn/functional.py#L396-... | true |
3,018,791,423 | torch.compile on MPS fails: generated Metal kernel uses loop-local variable out of scope | yusungsim | open | [
"triaged",
"module: mps",
"oncall: pt2"
] | 1 | NONE | ### 🐛 Describe the bug
I'm a total newcomer to PyTorch programming. I encountered this bug while trying to run the [example code for nari-labs/dia](https://github.com/nari-labs/dia) on my M2 Mac.
When I ran the example using torch.compile(...), I hit a compile-time error from TorchInductor's Metal backend. Since I w... | true |
3,018,788,020 | Some Performance Bug in `tol` of `torch.lobpcg()` | ILCSFNO | closed | [
"triaged",
"module: linear algebra"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Except some doc issues in #152107, there are something related to its performance.
The doc of [torch.lobpcg()](https://pytorch.org/docs/stable/generated/torch.lobpcg.html#torch-lobpcg) shows its description as below:
https://github.com/pytorch/pytorch/blob/d743a7bd85d2d793bc0e2a38d4538276ce06... | true |
3,018,782,757 | IGNORE: Test Bazel OIDC Failure | zxiiro | closed | [
"open source",
"release notes: releng",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,018,776,835 | padding_mode `reflect` works different from others in Conv | ILCSFNO | open | [
"module: nn",
"triaged",
"module: padding"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
The doc of [torch.nn.Conv3d()](https://pytorch.org/docs/stable/generated/torch.nn.Conv3d.html#conv3d) shows its description as below:
https://github.com/pytorch/pytorch/blob/7f28c03fac11dc3cf37da36def7e0857c331843d/torch/nn/modules/conv.py#L621
See repro below:
### Repro
```python
import torc... | true |
3,018,774,146 | [dynamic shapes] support SymInt inputs for kthvalue | pianpwk | closed | [
"Merged",
"ciflow/trunk",
"release notes: export"
] | 18 | CONTRIBUTOR | null | true |
3,018,722,338 | [Scaled MM] Update to support on B200 TN, NT, NN, TT Layouts are supported | drisspg | open | [
"module: performance",
"module: cuda",
"triaged",
"module: float8"
] | 0 | CONTRIBUTOR | # Summary
On Sm100 w/ cuda 12.8 cublas supports all 4 variants. We should update our PerTensor scaling kernel to allow for these layouts.
We can also update our recipes in TorchAO to not require this data transposition. Since the MMA atom supports TN,NN,NT,NN we should also update our rowwise scaling kernel to not re... | true |
3,018,707,359 | [audio hash update] update the pinned audio hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | COLLABORATOR | This PR is auto-generated nightly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/nightly.yml).
Update the pinned audio hash. | true |
3,018,702,480 | [Graph Partition] support ForeachKernelSchedulerNode | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | ForeachKernelSchedulerNode misses outputs_by_name when created with previous nodes. This PR fixes the issue.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,018,679,075 | Unify how we create random inputs for auto-tuning | masnesral | closed | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152502
* __->__ #152147
Summary: We're creating autotune inputs slightly differently when autotuning in-process vs. in a subprocess: One implementation is in TensorMeta.to_tensor() and another in AlgorithmSelectorCache.benchmark_example_val... | true |
3,018,678,657 | [dynamic shapes] guard_or_false for infer_size | pianpwk | open | [
"module: dynamo",
"ciflow/inductor",
"release notes: export"
] | 4 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,018,667,407 | Package const folded graph's cubin file | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: export"
] | 7 | CONTRIBUTOR | Summary: We need to pacakge const folded graph's cubin file into the final .pt2 package.
Fix https://github.com/pytorch/pytorch/issues/152067
Test Plan:
```
buck run fbcode//mode/dev-nosan //caffe2/test/inductor:test_aot_inductor -- -r test_constant_folding_cuda
```
Differential Revision: D73626480
... | true |
3,018,661,817 | WIP: divup op | msaroufim | open | [
"module: cpu",
"topic: new features",
"topic: not user facing"
] | 3 | MEMBER | Don't bother reviewing please, this code was not generated by humans and it's mostly for me to understand all the requirements of a new pytorch operator
```
################################################################################
# MEGA-PROMPT: How to Teach an LLM to Add **ANY** New Element-wise PyTorch Op... | true |
3,018,627,877 | Reducer: add check on received data to avoid segfault | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 3 | MEMBER | When ncclCommAbort is called it may return invalid/corrupted data to the reducer. This adds a check so we don't read past the end of the tensors leading to a segfault.
While this looks like it could be a security issue it actually isn't since we only read past the end of the buffer, not write.
Fixes #149418
Te... | true |
3,018,606,221 | [inductor] pass reduction idx to scan inner_fns | isuruf | closed | [
"open source",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152142
Closes https://github.com/pytorch/pytorch/pull/151931
Fixes https://github.com/pytorch/pytorch/issues/151738
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @j... | true |
3,018,557,123 | UserWarning: There is a performance drop because we have not yet implemented the batching rule for aten::scatter_reduce.two | aboubezari | closed | [
"module: performance",
"triaged",
"enhancement",
"module: vmap",
"module: functorch"
] | 3 | NONE | ### 🐛 Describe the bug
```
UserWarning: There is a performance drop because we have not yet implemented the batching rule for aten::scatter_reduce.two.
Please file us an issue on GitHub so that we can prioritize its implementation. (Triggered internally at ../aten/src/ATen/functorch/BatchedFallback.cpp:81.) ... | true |
3,018,518,193 | [CI][CD] Unify install_cuda and install_cuda_aarch64 scripts | clee2000 | closed | [
"Merged",
"ciflow/binaries",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Generalize install_cuda so it can also handle aarch64
Remove install_cuda_aarch64 since install_cuda can now handle it
Make install_cuda and install_cudnn functions in the install_cuda script because most of the code is the same
| true |
3,018,493,412 | Check integrity of bytes in AppendingByteSerializer | oulgen | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152139
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,018,419,873 | [ONNX] Add group_norm support from opset 21 | justinchuby | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: improvements"
] | 8 | COLLABORATOR | I didn't run the model in test because ORT doesn't have the op yet. Nevertheless it should be leveraged for newer opset versions. | true |
3,018,390,564 | [ca] expecttest and adjust a few tests | xmfan | open | [
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 2 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
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