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 |
|---|---|---|---|---|---|---|---|---|
3,044,797,354 | [Dynamo] Replace `unimplemented` with `unimplemented_v2` in `torch/_dynamo/variables/misc.py` [2/2] | shink | open | [
"triaged",
"open source",
"topic: not user facing",
"module: dynamo"
] | 6 | CONTRIBUTOR | Part of #147913
Follow up: #152274
Replace `unimplemented` with`unimplemented_v2` in `torch/_dynamo/variables/misc.py`
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,044,749,011 | Add CUDA support for Adagrad(fused=True) | MeetThePatel | open | [
"triaged",
"open source",
"release notes: optim"
] | 4 | CONTRIBUTOR | This PR adds CUDA support for Adagrad(fused=True) optimizer, along with 3 minor changes:
- Add a TensorLR variant for CPU Adagrad(fused=True).
- Fix error message in `test/test_optim.py`, where the incorrect optimizer name was being printed.
- Fix an error message in FusedSGD, where it was giving incorrect informati... | true |
3,044,663,148 | Allow zero sized dimensions in padding operations | sladyn98 | open | [
"open source",
"topic: not user facing"
] | 4 | NONE | Previously, the padding implementation in PadNd.cpp required all output dimensions to be strictly positive (> 0), which caused errors when padding tensors with zero-sized dimensions even when the padding for that dimension was also zero.
This change relaxes the constraint to allow non-negative (>= 0) output dimensio... | true |
3,044,623,989 | fix test | yf225 | closed | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153036
* #152775
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,044,617,968 | Add Split Softmax | AMindToThink | open | [
"module: nn",
"triaged",
"needs research"
] | 2 | NONE | Transformer models often forget their system prompts when processing long text due to the long distances between the source of the information and its destination.
The Split Softmax function is a modification of softmax for use in attention that promotes the model to keep paying attention to the system prompt. It was ... | true |
3,044,611,322 | WIP: Fix caching when output has unbacked | aorenste | open | [
"release notes: fx",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153034
| true |
3,044,594,141 | missalignment with differenet shape in F.linear with bf16 dtype | likelyzhao | open | [
"needs reproduction",
"triaged",
"module: bfloat16",
"module: linear algebra",
"module: padding"
] | 1 | NONE | ### 🐛 Describe the bug
For the F.linear function, when constructing matrix multiplications of varying dimensions via zero-padding, output consistency cannot be guaranteed under bf16 precision (outputs are consistent for some dimensions but inconsistent for others).
```python
import torch
import torch.nn.functional ... | true |
3,044,591,634 | DISABLED test_hook_with_closure (__main__.HooksTests) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 2 | NONE | Platforms: asan, linux, mac, macos, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_hook_with_closure&suite=HooksTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41763750570).
Over the past 3 h... | true |
3,044,591,578 | DISABLED test_comprehensive_svd_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_svd_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41765230283).
Over the past... | true |
3,044,591,521 | DISABLED test_comprehensive_amin_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 4 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_amin_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41762952404).
Over the pas... | true |
3,044,591,468 | DISABLED test_comprehensive_asinh_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 4 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_asinh_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41765095197).
Over the pa... | true |
3,044,587,182 | [Typing] Improve device typing for `torch.set_default_device()` | shink | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 12 | CONTRIBUTOR | Part of: #152952
Here is the definition of `torch.types.Device`:
https://github.com/pytorch/pytorch/blob/ab997d9ff584e8623de146b6eb9c9074081b045b/torch/types.py#L74
So `_Optional[_Union["torch.device", str, builtins.int]]` is equivalent to it.
cc: @Skylion007 | true |
3,044,564,077 | [Typing] Apply `torch.types.Device` in `torch/cuda/memory.py` | shink | open | [
"triaged",
"open source",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Part of: #152952
Here is the definition of `torch.types.Device`:
https://github.com/pytorch/pytorch/blob/ab997d9ff584e8623de146b6eb9c9074081b045b/torch/types.py#L74
It contains `int`, so the `int` in `Union[Device, int]` is redundant.
cc: @Skylion007
| true |
3,044,559,891 | remove register_fake | yf225 | closed | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153026
* #152775
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,044,513,586 | Multiple CUDA graphs utilizing multiple CUDA GPUs encounter illegal memory access during replay | Atream | open | [
"triaged",
"module: cuda graphs"
] | 3 | NONE | ### 🐛 Describe the bug
When capturing multiple CUDA graphs that use multiple CUDA GPUs, only the buffers related to the last captured CUDA graph are retained. As a result, only the last captured CUDA graph can be replayed successfully, while replaying other CUDA graphs leads to illegal memory access.
Testing revealed... | true |
3,044,502,694 | [RFC] Enable XPU+FlexAttention on Intel GPU | liangan1 | open | [
"triaged",
"enhancement",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: xpu",
"module: flex attention"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
## Motivation
The Attention has been the critical performance bottleneck in the current LLM models, and FlexAttention is a good choice to cover the broad variants in the transformers series models. With FlexAttention, it is easy for us to enable the paged attention and fused S... | true |
3,044,480,415 | Fix Codegen.cmake warning | cyyever | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | Fix
```
CMake Warning (dev) in cmake/Codegen.cmake:
A logical block opening on the line
/var/lib/jenkins/workspace/cmake/Codegen.cmake:393 (if)
closes on the line
/var/lib/jenkins/workspace/cmake/Codegen.cmake:401 (endif)
with mis-matching arguments.
```
by removing the condition in `endi... | true |
3,044,472,261 | XPU inference output abnormal with device 'XPU:1' | maxwell-zhengxu | open | [
"high priority",
"triage review",
"triaged",
"module: xpu"
] | 4 | NONE | ### 🐛 Describe the bug
Two intel GPUs environment with work well environment, the inference output is always correct for device 'xpu:0' while random output abnormal for device 'xpu:1'
```python
import torch
import torchvision.models as models
torch.manual_seed(0)
model = models.resnet50(weights="ResNet50_Weights.D... | true |
3,044,465,268 | Adding a generic attribute for easier checkpoint discrepancy debugging. | githubsgi | open | [
"triaged",
"open source"
] | 5 | CONTRIBUTOR | Adding a generic attributed called layer_id for the object that recompute_fn is a method of. This ties the checkpointing saved and recompute discrepancies to a layer in the model.
topic: not user facing
| true |
3,044,464,840 | Add a project section to pyproject.toml, making uv sync work | ezyang | open | [
"topic: not user facing"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153020
With this change, I can now run `uv sync -v` and get all dependencies I need and then trigger build of PyTorch. (The `-v` is good because the build takes a long time and uv hides progress by default.)
Signed-off-by: Edwa... | true |
3,044,455,802 | [RFC][API-Unstable]Enable A16W4 on XPU Device | liangan1 | open | [
"triaged",
"module: xpu"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
## Motivation
As you know, the generation task with LLM is autoregressive and the GEMM computation of the decoding stage for the next token is memory bound. The weight only quantization with A16W4 has been widely adopted by the LLM inference, especially for the client GPU with... | true |
3,044,434,059 | DISABLED test_comprehensive_scatter_xpu_bool (__main__.TestInductorOpInfoXPU) | chuanqi129 | closed | [
"triaged",
"skipped",
"module: xpu"
] | 1 | COLLABORATOR | Platforms: linux
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A%3ATestInductorOpInfoXPU%3A%3Atest_comprehensive_scatter_xpu_bool'%2C%20'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A... | true |
3,044,432,643 | DISABLED test_comprehensive_scatter_xpu_int64 (__main__.TestInductorOpInfoXPU) | chuanqi129 | closed | [
"triaged",
"skipped",
"module: xpu"
] | 1 | COLLABORATOR | Platforms: linux
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A%3ATestInductorOpInfoXPU%3A%3Atest_comprehensive_scatter_xpu_bool'%2C%20'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A... | true |
3,044,429,040 | inconsistent grads between two types of `allgather`s | gameofdimension | open | [
"oncall: distributed",
"module: autograd"
] | 0 | NONE | ### 🐛 Describe the bug
I've observed a gradient discrepancy between two PyTorch all-gather implementations: one using the DTensor API, and the other using all_gather_tensor_autograd. My goal is to implement a correct autograd-compatible all-gather operation, but I'm unsure which implementation (if either) produces th... | true |
3,044,413,527 | c10d/gloo: add ibverbs backend | d4l3k | open | [
"oncall: distributed",
"fb-exported",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 5 | MEMBER | Summary:
X-link: https://github.com/pytorch/gloo/pull/437
This provides a new "UnboundBuffer" implementation for Gloo ibverbs backend so it can be used with PyTorch.
This currently is passing basic tests such as `reduce_test` and `send_recv_test` but there are a number of failures. Putting this up for review so the f... | true |
3,044,402,645 | Operations on different precision tensors in CPU lead to different outputs | Redempt1onzzZZ | closed | [
"module: cpu",
"triaged",
"module: edge cases"
] | 3 | NONE | ### 🐛 Describe the bug
A similar finding with [https://github.com/pytorch/pytorch/issues/152294](#152294), the bug also consist in "torch.addcdiv", it seems that using only number (65536) as input, it will be transform to inf, however when using array ([65536]), the calculation will run normally.
```
import torch
inp... | true |
3,044,401,500 | [Lint] Add install command for GHA step | malfet | closed | [
"Merged",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152719
* __->__ #153013
Otherwise, it fails to run the script | true |
3,044,401,411 | [Testing] Add logic for running MPS tests | malfet | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #153013
* #152719
* __->__ #153012
Prep change for getting rid of `_mac-test-mps.yml`
A complete no-op for now, but will be used by PR above the stack, but they should be landed few days apart to avoid forcing lots of people to rebase thei... | true |
3,044,392,004 | [WIP][dynamic shapes] unbacked safer cat, repeat | pianpwk | open | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | With https://github.com/pytorch/pytorch/pull/150483, for https://github.com/pytorch/pytorch/issues/152473
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,044,379,231 | Detect NVSHMEM location | kwen2501 | closed | [
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153010
### Changes
- Detect NVSHMEM install location via `sysconfig.get_path("purelib")`, which typically resolves to `<conda_env>/lib/python/site-packages`, and NVSHMEM include and lib live under `nvidia/nvshmem`
- Added link dir... | true |
3,044,337,298 | DISABLED test_comprehensive_scatter_xpu_bool (__main__.TestInductorOpInfoXPU) | etaf | open | [
"triaged",
"skipped",
"module: xpu"
] | 1 | COLLABORATOR | Platforms: <fill this in or delete. Valid labels are: asan, linux, mac, macos, rocm, win, windows.>
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A%3ATestInductorOpInfoXPU%3A%3Atest_comp... | true |
3,044,335,974 | DISABLED test_comprehensive_scatter_xpu_int64 (__main__.TestInductorOpInfoXPU) | etaf | open | [
"triaged",
"skipped",
"module: xpu"
] | 1 | COLLABORATOR | Platforms: <fill this in or delete. Valid labels are: asan, linux, mac, macos, rocm, win, windows.>
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A%3ATestInductorOpInfoXPU%3A%3Atest_comp... | true |
3,044,318,690 | Remove redundant type aliases of _device_t for torch.Device (#152952) | sanjai-11 | open | [
"oncall: distributed",
"module: cpu",
"triaged",
"module: mkldnn",
"open source",
"module: amp (automated mixed precision)",
"release notes: quantization",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"release notes: distributed (checkpoint)",
"suppress-bc-linter",
"module... | 3 | NONE | Fixes #152952
This PR removes redundant type aliases for `_device_t` and replaces them with `torch.types.Device` where applicable, to make the typing system more consistent across PyTorch.
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei... | true |
3,044,295,252 | [cutlass backend] Use src code to generate cutlass gemm name | henrylhtsang | open | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153006
* #152580
Differential Revision: [D74288965](https://our.internmc.facebook.com/intern/diff/D74288965/)
This shaves off 40s for at least small cases, since we don't have to recompile the kernel again.
cc @voznesenskym... | true |
3,044,256,520 | [autograd][docs] Add more details on why save_for_backward is important in extending autograd note | soulitzer | open | [
"release notes: autograd"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #153094
* __->__ #153005
cc @stas00 | true |
3,044,255,324 | [WIP][Inductor-CPU] int8 WoQ concat linear | sanchitintel | open | [
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | COLLABORATOR | WIP
- [ ] Add UT corresponding to torchao pattern
- [ ] Add perf data
- [ ] Refactor
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,044,226,030 | [cutlass backend] Skip cuda lib path if it is torch/lib | 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):
* __->__ #153003
Differential Revision: [D74284808](https://our.internmc.facebook.com/intern/diff/D74284808/)
This is a bit risky for cutlass backend, so decided to separate it out. Tested offline.
cc @voznesenskym @penguinwu @EikanWa... | true |
3,044,220,979 | [CI] Use sccache installed in docker image in xla build | clee2000 | open | [
"topic: not user facing",
"ciflow/pull"
] | 2 | CONTRIBUTOR | The edited comment should have the info
Sccache stopped working on xla at some point near dec 17 2023. I am not sure what commit caused it. I think it was having trouble writing to the cache.
Either way, there is an sccache already installed on the docker image, so we should use that instead of a binary from s3... | true |
3,044,212,130 | [cutlass backend][test] re-enable test_cuda_compile_command for fbcode | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153001
Differential Revision: [D74284047](https://our.internmc.facebook.com/intern/diff/D74284047/)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chen... | true |
3,044,159,796 | [export] Unflatten None | angelayi | open | [
"ciflow/trunk",
"release notes: export"
] | 3 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
3,044,149,425 | `lintrunenr init` fails | malfet | open | [
"module: lint",
"triaged",
"module: devx"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Attempting to run `lintrunner init` fails
```
% lintrunner init --take FLAKE8
Warning: Could not find a lintrunner config at: '.lintrunner.private.toml'. Continuing without using configuration file.
[2025-05-06T22:17:48Z INFO lintrunner::linter] Initializing linter: 'FLAKE8'
[2025-05-06T22:17:4... | true |
3,044,141,928 | [Dynamo][trace_rules] Add torch.distributed.fb.simple_fsdp to LEGACY_MOD_INLINELIST | yf225 | closed | [
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Functions / modules in `torch.distributed.fb.simple_fsdp` are guaranteed to be traceable, and inlining into them is prerequisite for having both pre-forward / post-forward hooks to be in the same graph as forward for SimpleFSDP modules.
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __... | true |
3,044,135,504 | [Testing] Add copysign from scalar regression test | malfet | closed | [
"Merged",
"release notes: python_frontend",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152997
But instead of adding it just for MPS backend, add it to OpInfo
Fixes https://github.com/pytorch/pytorch/issues/152582 | true |
3,044,082,824 | DISABLED test_comprehensive_rsub_cuda_float64 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_rsub_cuda_float64&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41741925240).
Over the pas... | true |
3,044,071,880 | [inductor] dtype promotion error in cat decomp | pianpwk | open | [
"ciflow/trunk",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: inductor",
"merging"
] | 4 | CONTRIBUTOR | cloning single tensor wasn't following dtype promotion rules
for SAM model: https://github.com/pytorch/pytorch/issues/152606
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,044,034,530 | [dynamo] Actually support functools.lru_cache | williamwen42 | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-functools"
] | 0 | MEMBER | Followup to https://github.com/pytorch/pytorch/issues/146598
Currently, when Dynamo traces a `lru_cache`d function, we simply trace the underlying function. This is not sound when the underlying function depends on state outside that function (e.g. globals, cells).
Fully supporting the cache lookup involved in `lru_... | true |
3,044,025,410 | [inductor] Fix ModularIndexing assumptions | isuruf | open | [
"module: cpu",
"open source",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"merging"
] | 4 | COLLABORATOR | Fixes https://github.com/pytorch/pytorch/issues/151198.
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152993
Since the result of ModularIndexing can be zero due to the modulo
operation, we should not make any assumption about ModularIndexing
being positive
cc @jgong5 ... | true |
3,044,012,443 | conv2d with int8 on CUDA: GET was unable to find an engine to execute this computation | c-f-h | open | [
"module: cuda",
"module: convolution",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
The following script works fine if I switch to CPU, or change the tensor dtypes to float32. Otherwise, see the error below.
```py
import torch
device = torch.device("cuda") # works fine with "cpu"
print(f"Using device: {device}")
# works fine if both are float32
input = torch.randin... | true |
3,043,985,559 | [FrozenSet] Fixes for FrozenSet | guilhermeleobas | open | [
"open source",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152991
* #152990
* #152908
* #152907
* #152989
* #152906
* #152905
* #152903
* #152902
* #152901
* #152904
* #152988
* #152987
* #150792
* #152900
* #153070
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSupe... | true |
3,043,985,422 | [Set] Raise TypeError if set is called with the wrong number of arguments | guilhermeleobas | open | [
"open source",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152991
* __->__ #152990
* #152908
* #152907
* #152989
* #152906
* #152905
* #152903
* #152902
* #152901
* #152904
* #152988
* #152987
* #150792
* #152900
* #153070
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSupe... | true |
3,043,985,252 | [Set] Update `set.union` and `set.update` to support *args | guilhermeleobas | open | [
"open source",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152991
* #152990
* #152908
* #152907
* __->__ #152989
* #152906
* #152905
* #152903
* #152902
* #152901
* #152904
* #152988
* #152987
* #150792
* #152900
* #153070
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSupe... | true |
3,043,984,885 | [Set] Raise `TypeError` if argument is unhashable | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152991
* #152990
* #152908
* #152907
* #152989
* #152906
* #152905
* #152903
* #152902
* #152901
* #152904
* __->__ #152988
* #152987
* #150792
* #152900
* #153070
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSupe... | true |
3,043,984,736 | [Set] Handle exception in ConstantVariable operation | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152991
* #152990
* #152908
* #152907
* #152989
* #152906
* #152905
* #152903
* #152902
* #152901
* #152904
* #152988
* __->__ #152987
* #150792
* #152900
* #153070
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSupe... | true |
3,043,976,311 | [WIP] Add XPU support for FlightRecorder | frost-intel | open | [
"oncall: distributed",
"open source",
"ciflow/trunk",
"release notes: distributed (c10d)",
"topic: not user facing"
] | 2 | COLLABORATOR | This is the first part of bringing XPU/XCCL support for FlightRecorder.
`AcceleratorEvent` is a generic interface for CUDAEvent and XPUEvent, which is used in FlightRecorder to work with both XCCL and NCCL.
Since the actual instantiation of the FlightRecorder and DebugInfoWriter objects happens in ProcessGroupNCC... | true |
3,043,971,158 | `torch.load` can't deserialize `datetime` objects, even with the appropriate `safe_globals` | gtebbutt | open | [
"module: serialization",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
Spent a while chasing this one down on the assumption that a custom class from my code was being inadvertently saved, especially with the earlier message requiring `getattr` to be added to `safe_globals`, but it turns out it'll happen on any output containing a `datetime` object:
```python
im... | true |
3,043,958,275 | [hop_schema] support gen_schema for invoke_subgraph | ydwu4 | open | [
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152984
* #152974
* #151067
| true |
3,043,956,173 | compile_fx: make a compile event that corresponds to the fx_compile waitcounter | c00w | open | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152983
This is a pretty minor change, but by having exact correspondence, we can
easily confirm data differences between perfetto and wait counters
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaoz... | true |
3,043,912,132 | [torch][ao] Properly strip tracking stats in _fold_conv_bn_qat for 1D | JakeStevens | open | [
"fb-exported",
"release notes: quantization",
"release notes: AO frontend"
] | 5 | NONE | Summary: _fold_conv_bn_qat has logic to remove the tracking stats. Currently, this includes a check that includes only torch.nn.modules.batchnorm.BatchNorm2d. As a result, the tracking stats are not properly removed when 1D is used. This diff updates to fix this.
Test Plan:
Run N7113483 without this fix.
{F1977726982... | true |
3,043,888,333 | Catch TypeError from ValueRanges | jansel | open | [
"module: cpu",
"fb-exported",
"ciflow/trunk",
"release notes: inductor"
] | 3 | CONTRIBUTOR | Summary: This is a possible workaround to https://fb.workplace.com/groups/1075192433118967/permalink/675836685333300/
Test Plan: Ask poster to confirm fix
Differential Revision: D74268733
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 | true |
3,043,887,194 | Fix `'TensorBox' object has no attribute 'is_input_buffer'` | jansel | open | [
"fb-exported",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 4 | CONTRIBUTOR | Summary: Fix for https://fb.workplace.com/groups/1075192433118967/permalink/1664491270855744/
Test Plan: Used reproducer from D74262030
Differential Revision: D74270090
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kaden... | true |
3,043,823,259 | FPE when using `torch.lcm_` with int32 tensor and int16 scalar | SilentTester73 | open | [
"module: crash",
"module: cpu",
"module: error checking",
"triaged",
"module: edge cases"
] | 3 | NONE | ### 🐛 Describe the bug
### Description
When using `torch.lcm_` in-place operation between a large int32 tensor and an int16 scalar, the program crashes with a floating point exception. The operation works fine with smaller tensors, but fails with a specific large tensor containing various integer values.
### Steps ... | true |
3,043,782,002 | [Pytorch] Add `torch.cuda.streams.Event` to save torch functions list | dongji-gao | open | [
"fb-exported"
] | 4 | CONTRIBUTOR | Summary: TSIA
Test Plan: WIP
Differential Revision: D74266940
| true |
3,043,769,613 | [MegaCache] Make MegaCache generic to allow external plugins registration | tbohutyn | open | [
"triaged",
"open source",
"topic: not user facing",
"module: inductor",
"module: dynamo"
] | 4 | CONTRIBUTOR | Implements #152976
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @oulgen | true |
3,043,763,742 | Refactor MegaCache to make it generic | tbohutyn | open | [
"oncall: pt2"
] | 0 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Refactoring MegaCache to make it generic would allow for external plugins' caches to register in MegaCache. It would also remove specific cache logic from it.
Related to https://github.com/pytorch/pytorch/pull/143341
Proposed PR https://github.com/pytorch/pytorch/pull/152977
... | true |
3,043,748,868 | [dtensor] Extend Partial partition of replicated tensor for min/max reduce | BowenBao | open | [
"oncall: distributed",
"triaged",
"open source",
"topic: improvements",
"ciflow/inductor",
"release notes: distributed (dtensor)"
] | 2 | COLLABORATOR | cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,043,721,503 | [hop_schema] add HopSchemaGenerator to make it easier to create hop schema | ydwu4 | open | [
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152984
* __->__ #152974
* #151067
| true |
3,043,701,258 | Adding XPU support to DTensor examples. | githubsgi | open | [
"oncall: distributed",
"triaged",
"open source",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Adds XPU support to visualize_sharding_example.py and comm_mode_features_example.py .
topic: not user facing
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,043,700,902 | avoid falling back to as_strided for non-contiguous in-place reshape. | laithsakka | open | [
"oncall: pt2"
] | 0 | CONTRIBUTOR | When non-contiguous tensor reshape operates has unbacked symbols, there is a very high probability of hitting data dependent errors if we call view_symint, hence instead we call as_strided instead. We could have cloned as well, but as_strided sounds more efficient.
```
if (!self.sym_numel().has_hint() || !produc... | true |
3,043,698,093 | DISABLED test_comprehensive_scatter_xpu_int32 (__main__.TestInductorOpInfoXPU) | chuanqi129 | open | [
"triaged",
"skipped",
"module: xpu"
] | 1 | COLLABORATOR | Platforms: linux
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A%3ATestInductorOpInfoXPU%3A%3Atest_comprehensive_scatter_xpu_int32'%22%5D)).
cc @gujinghui @EikanWang @fengyuan14 @guangy... | true |
3,043,694,521 | DISABLED test_comprehensive_gather_xpu_int64 (__main__.TestInductorOpInfoXPU) | chuanqi129 | open | [
"triaged",
"skipped",
"module: xpu"
] | 1 | COLLABORATOR | Platforms: linux
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Finductor%2Ftest_torchinductor_opinfo.py%3A%3ATestInductorOpInfoXPU%3A%3Atest_comprehensive_gather_xpu_int64'%22%5D)).
cc @gujinghui @EikanWang @fengyuan14 @guangye... | true |
3,043,681,942 | [nativert] Move GraphSignature to pytorch core | yiming0416 | open | [
"fb-exported",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Summary:
Torch Native Runtime RFC: https://github.com/pytorch/rfcs/pull/72
An in-memory representation of `GraphSignature` for graph specs of an exported program, which will be consumed by the runtime.
Test Plan: Added tests under `test/cpp/nativert/test_graph_signature.cpp`
Differential Revision: D73895378
| true |
3,043,660,961 | [inductor] Generate synthetic offsets appropriately for autotuning _scaled_grouped_mm | bertmaher | open | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152968
Summary: The autotuner is using zero-filled tensors to autotune
_scaled_grouped_mm and that's not appropriate for the offsets tensor, since it
essentially corresponds to "no input" and thus yields invalid perf results.
... | true |
3,043,651,973 | [ATen][CUDA] Optimize 128 bit vectorization | pytorchbot | closed | [
"open source",
"release notes: cuda"
] | 1 | COLLABORATOR | Fixes #147376.
As per request: https://github.com/pytorch/pytorch/pull/145746#pullrequestreview-2642118301
This PR omits sm80 or older of using vec8 kernels due to long compilation and large binary size.
cc @ptrblck @msaroufim @eqy @jerryzh168 @manuelcandales @SherlockNoMad @angelayi | true |
3,043,651,250 | [Memento] On-demand mode using without torch api | mzzchy | open | [
"fb-exported",
"topic: not user facing"
] | 11 | CONTRIBUTOR | Differential Revision: D74179606
| true |
3,043,618,388 | WIP so many changes to generate non-as strided view | laithsakka | open | [
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152965
* #152722
* #148872
| true |
3,043,614,211 | [FSDP2] need dummy forward/backward to stay SPMD | weifengpy | open | [
"oncall: distributed",
"triaged"
] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
FSDP2 assumes SPMD on every rank, meaning every rank needs to call forward/backward to issue all-gather / reduce-scatter
However, user reported two cases that some rank might be skipping forward/backward
* torchtune might mask all the activations. they have to create a dummy i... | true |
3,043,598,064 | DTensor support for dynamic shapes is soft | bdhirsh | open | [
"oncall: distributed",
"oncall: pt2"
] | 1 | CONTRIBUTOR | The state of DTensor + compile + dynamic shapes today is roughly:
(1) for generic "pt2-friendly" tensor subclasses, we support compiling them with dynamic shapes. This includes cases where both the outer subclass shape and it's inner tensor shape(s) vary independently.
(2) At the same time, dynamic shapes support imp... | true |
3,043,571,434 | TestNestedTensorOpInfoCUDA.test_compile_backward_matmul_cuda_float32 Test Failure | nWEIdia | open | [
"module: tests",
"triaged",
"module: nestedtensor"
] | 3 | COLLABORATOR | ### 🐛 Describe the bug
Steps to Reproduce: please see https://github.com/pytorch/pytorch/issues/152962#issuecomment-2859328199
`Traceback (most recent call last):
File "/usr/lib/python3.12/unittest/case.py", line 58, in testPartExecutor
yield
File "/usr/lib/python3.12/unittest/case.py", line 539, in subTest... | true |
3,043,543,233 | [Dynamo] Remove unused guard PYMODULE_MATCH | jbschlosser | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152729
* __->__ #152961
* #152872
* #152865
* #152730
* #152728
* #152727
* #152725
Not used anywhere: https://www.internalfb.com/code/search?q=repo%3Afbcode%20PYMODULE_MATCH
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @X... | true |
3,043,469,694 | Change aoti cpp tests to run serially within file | yushangdi | open | [
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"skip-url-lint"
] | 7 | CONTRIBUTOR | Fixes #152674
https://github.com/pytorch/pytorch/issues/152889
https://github.com/pytorch/pytorch/issues/152888
https://github.com/pytorch/pytorch/issues/152891
`--dist=loadfile` ensures all tests in the same source file run in the same worker.
Tests like `FreeInactiveConstantBufferRuntimeConstantFoldingCud... | true |
3,043,427,737 | docs: Improve documentation for NCCL timeout / watchdog variables | booxter | open | [
"oncall: distributed",
"triaged",
"open source",
"release notes: distributed (c10d)"
] | 2 | NONE | cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,043,403,327 | Follow up to #152209, remove compat patch | clee2000 | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Remove compat patch that lets PRs that haven't rebased base #152209 still have docker images.
Merge this next week | true |
3,043,388,225 | [CI] Upgrade sccache to 0.10.0 | clee2000 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Newest release handles cuda better, and I think this fixes the cases I saw where some cuda related builds weren't being cached correctly | true |
3,043,298,872 | [ROCm] unkip test_non_standard_bool except for failings ops | pragupta | open | [
"module: rocm",
"open source",
"ciflow/rocm",
"ciflow/inductor-rocm"
] | 2 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
3,043,285,407 | UNSTABLE pull / linux-docs / build-docs-functorch-false | malfet | closed | [
"module: docs",
"module: ci",
"triaged",
"unstable"
] | 2 | CONTRIBUTOR | Jobs fails with infinite redirects, likely due to the changes happening to the doc website, see https://github.com/pytorch/pytorch/actions/runs/14862967281/job/41733878657
cc @svekars @sekyondaMeta @AlannaBurke @seemethere @pytorch/pytorch-dev-infra | true |
3,043,272,004 | DTensor placement propagation for `slice` fails during recompile due to SymInts | lw | open | [
"oncall: distributed",
"oncall: pt2"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
This code fails:
```py
import torch
import torch.distributed
torch.distributed.init_process_group(backend="nccl", rank=0, world_size=1, device_id=torch.device("cuda", 0), init_method="tcp://127.0.0.1:2743")
device_mesh = torch.distributed.device_mesh.DeviceMesh.from_group(torch.distributed.gro... | true |
3,043,159,561 | [nativert] Move Placement to pytorch core | yushangdi | open | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing"
] | 13 | CONTRIBUTOR | Summary:
Move Placement to pytorch core.
Using `torch::nativert::isSameDevice` explicitly in code to avoid confusion with the `isSameDevice` in torch namespace.
Test Plan:
```
buck run fbcode//mode/dev-nosan //caffe2/test/cpp/nativert:placement_test
./bin/test_nativert
```
OSS and internal CI
Diffe... | true |
3,043,123,452 | Remove redundant type aliases of _device for torch.Device | Skylion007 | open | [
"good first issue",
"triaged",
"actionable"
] | 5 | COLLABORATOR | ### 🚀 The feature, motivation and pitch
We should remove redundant type aliases for `_device_t` and replace with `torch.types.Device` where appropriate to make the typing system a bit more consistent.
#152935 is a good step in that direction
### Alternatives
_No response_
### Additional context
_No response_ | true |
3,043,119,298 | [ROCm] Ck gemm architecture guard | alugorey | open | [
"module: rocm",
"triaged",
"open source"
] | 2 | CONTRIBUTOR | Prevents CK gemms from being built unless explicitly specified. USE_ROCM_CK_GEMM controls the build, on by default on ROCm platform
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
3,043,110,284 | Add NestedTensorHPU to to_padded_tensor in native_functions.yaml | sfraczek | open | [
"triaged",
"open source",
"ciflow/xpu",
"release notes: xpu"
] | 5 | NONE | null | true |
3,043,004,042 | [dtensor] add privateuse1 SDPA op support to DTensor | 1274085042 | open | [
"oncall: distributed",
"triaged",
"open source"
] | 2 | CONTRIBUTOR |
**Summary**
This PR adds _scaled_dot_product_fused_attention_overrideable and _scaled_dot_product_fused_attention_overrideable_backward to DTensor ops
@drisspg @fegin @d4l3k @wanchaol @albanD
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,042,998,223 | [Linter] Add linter to detect device-bias hard code in test cases. | etaf | open | [
"open source",
"topic: not user facing"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152948
* #152945
Since XPU does not gate community pull requests, we’ve observed that contributors often hardcode "cuda" in functions decorated with @requires_gpu() when adding new test cases. This causes the tests to fail on XPU an... | true |
3,042,984,947 | Clean up of CUTLASS_VERSION | narekmalk | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 10 | CONTRIBUTOR | Fixes #152847
| true |
3,042,957,740 | [dtensor] add privateuse1 SDPA op support to DTensor | 1274085042 | closed | [
"oncall: distributed",
"open source"
] | 3 | CONTRIBUTOR | **Summary**
This PR adds _scaled_dot_product_fused_attention_overrideable and _scaled_dot_product_fused_attention_overrideable_backward to DTensor ops
@drisspg @fegin @d4l3k @wanchaol @albanD
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,042,791,350 | [Break XPU] Fix XPU UT failures introduced by community. | etaf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"keep-going",
"ciflow/xpu"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152948
* __->__ #152945
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,042,756,025 | DISABLED test_compiler_collectives_automatic_dynamic_tensor (__main__.TestMultiProc) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 2 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_compiler_collectives_automatic_dynamic_tensor&suite=TestMultiProc&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41701856727).
Over th... | true |
3,042,755,895 | DISABLED test_comprehensive_ormqr_cuda_float64 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_ormqr_cuda_float64&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41707147808).
Over the pa... | true |
3,042,748,855 | aten._scaled_dot_product_efficient_attention returns LSE padded to next highest multiple of 32 | a-r-r-o-w | open | [
"module: cuda",
"triaged",
"module: sdpa"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Hi! This is less of a bug report and more of an ask of why the behaviour is this way.
With the following code to obtain LSE from efficient attention backend, the shape of the LSE tensor is `[1, 2, 32]`. It is expected that the size in dim=2 should match the sequence length, which is `8` in thi... | true |
3,042,681,757 | ROCm: no HIP device available if device is already initialized | stefanozampini | open | [
"module: rocm",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
If I first initialize the HIP environment from `cupy`, `torch` does not detect it
```
$ python -c 'import cupy; print(cupy.cuda.is_available()); import torch; print(torch.cuda.is_available())'
True
False
```
However, as can be seen below, it should
```
$ python -c 'import cupy; print(cupy.cuda.... | true |
3,042,513,699 | [Don't merge] Debug | mengfei25 | open | [
"triaged",
"open source",
"module: dynamo"
] | 3 | CONTRIBUTOR | cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
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