id int64 2.74B 3.05B | title stringlengths 1 255 | user stringlengths 2 26 | state stringclasses 2
values | labels listlengths 0 24 | comments int64 0 206 | author_association stringclasses 4
values | body stringlengths 7 62.5k ⌀ | is_title bool 1
class |
|---|---|---|---|---|---|---|---|---|
2,945,404,232 | add loop mm benchmark | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149910
* __->__ #149932
results:
compile time instruction count for iteration 4 is 67947323682
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @... | true |
2,945,379,474 | [Minimizer] Better debugging message | sweetStreet | open | [
"fb-exported",
"release notes: fx",
"fx"
] | 6 | NONE | Summary:
This diff tries to have better report message for Minimizer
1. Fix Minimizer block mode to handle case where no culprits are found between start and end indices, preventing out-of-range exception at https://fburl.com/code/r9w0xurj
2. Instead of directly converting the list to set that lost the order of nodes, ... | true |
2,945,359,632 | [ROCm][TunableOp] TunableOp Context Manager for unit tests | naromero77amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm-mi300"
] | 3 | COLLABORATOR | This PR is cleanup only. There are no feature changes or bug fixes.
We create a TunableOp context manager for setting up and cleanup. We re-write TunableOp unit tests in terms of this context manager. Ultimately reduces the amount of copy-paste code.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSup... | true |
2,945,345,172 | [ued][whisper][dynamo] Graph break on cached_property | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```
torch._dynamo.exc.Unsupported: 'inline in skipfiles: cached_property.__get__ | __get__ /home/lsakka/.conda/envs/user-empathy/lib/python3.11/functools.py, skipped according trace_rules.lookup SKIP_DIRS'
from user code:
File "/home/lsakka/whisper/whisper/decoding.py", line 40, in torch_dy... | true |
2,945,337,747 | [MPS/Inductor] Add support for chebyshev_polynomial_t. | dcci | closed | [
"Merged",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | MEMBER | 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 |
2,945,321,480 | add weight 2D tensor for xpu | sunjiweiswift | open | [
"triaged",
"open source",
"topic: not user facing"
] | 3 | NONE | Intel xpu kernel uses 2D int4 weight | true |
2,945,317,598 | [Intel GPU] trigger tf32 no-gpu warn only when setting true | ZhiweiYan-96 | closed | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu"
] | 21 | COLLABORATOR | Fix issue #149829
# Detail
In `torch.export` initialization stage, the context variable of `torch.backends.mkldn` would be initialized at function `_ignore_backend_decomps` in `torch/export/_trace.py`.
It should be wrong to trigger no-gpu warning when trying to setting the value to `False` in a CPU-Only enviro... | true |
2,945,273,469 | Replace c10::guts::is_fundamental with std::is_fundamental | cyyever | open | [
"triaged",
"open source",
"topic: not user facing"
] | 2 | COLLABORATOR | c10::guts::is_fundamental was introduced as a workaround to MSVC bug for at::Half.
| true |
2,945,175,106 | Delegate torch.accelerator.device_count to torch.xxx.device_count for multi-process usage | guangyey | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: python_frontend",
"module: accelerator"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149924
* #147507
# Motivation
Adapt `torch.accelerator.device_count` for multi-process usage. For example, `torch.cuda.device_count` avoids poisoning fork, then `torch.accelerator.device_count` should meet the same requirement.
Now ... | true |
2,945,163,889 | Enable move warnings for torch targets | cyyever | closed | [
"oncall: jit",
"open source",
"Merged",
"NNC",
"ciflow/trunk",
"release notes: jit",
"ciflow/periodic"
] | 6 | COLLABORATOR | This PR enables more move warnings for torch targets and fixes some code.
cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel | true |
2,945,160,284 | [CI][BE] Update other actions | malfet | closed | [
"Merged",
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149919
* __->__ #149922
* #149918
* #149917
Discovered by actionlint-1.7.7:
- `actions/checkout@v3`->`actions/checkout@v4`
- `actions/setup-python@v4` -> `actions/setup-python@v5` | true |
2,945,147,607 | [ued][whisper][dynamo] Graph break - setattr on class object | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```
File "/home/lsakka/.conda/envs/user-empathy/lib/python3.11/site-packages/torch/_dynamo/exc.py", line 317, in unimplemented
raise Unsupported(msg, case_name=case_name)
torch._dynamo.exc.Unsupported: builtin: setattr [<class 'torch._dynamo.variables.user_defined.UserDefinedClassVariable'... | true |
2,945,143,417 | [ued][whisper][dynamo] Graph break on a unsupported dict key | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```
raph break in user code at /home/lsakka/.conda/envs/user-empathy/lib/python3.11/site-packages/regex/regex.py:503
Reason: Unsupported: Dict key of type <class 'torch._dynamo.variables.lazy.LazyVariableTracker'>. Key: TupleVariable(length=6)
User code traceback:
File "/home/lsakka/whisper/w... | true |
2,945,135,804 | [BE][CI] Update actionlint to 1.7.7 | malfet | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149919
* #149922
* #149918
* #149917
- fix anti-pattern started by https://github.com/pytorch/pytorch/pull/81922 when x86 actionlint binaries were placed in Linux-arm64 folder
- Fix renaming lint violations, namely
```
>>> L... | true |
2,945,135,718 | [BE][CI] Update configure-aws-credential to v4 | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149919
* #149922
* __->__ #149918
* #149917
Prerequisite for update to actionlint-1.7.7 | true |
2,945,135,645 | [BE] Add Mac ARM64 actionlint binary | malfet | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149919
* #149922
* #149918
* __->__ #149917
Downloaded from https://github.com/rhysd/actionlint/releases/tag/v1.6.21 | true |
2,945,106,410 | Enable XPU distributed test for PT2.8 | daisyden | open | [
"oncall: distributed",
"open source",
"release notes: distributed (fsdp)",
"module: inductor",
"module: dynamo"
] | 3 | NONE | Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @kwen2501 @c-p-i-o | true |
2,944,963,660 | Change to default backend | drisspg | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149915
| true |
2,944,956,529 | [Test] Add simple MPS op benchmarks | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149914
Lots of benchmark tests has been posted in PRs, but they might get lost over time
So let's create a benchmark and populate it with results (preferably from the run on CI machine) | true |
2,944,909,501 | support scalar tensor for functional all_gather | yuguo68 | open | [
"oncall: distributed",
"release notes: distributed (c10d)",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149913
* #149912
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,944,909,421 | add a util function _make_all_gather_out_tensor to reduce code duplication | yuguo68 | open | [
"oncall: distributed",
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149913
* __->__ #149912
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,944,860,475 | [dynamo] `torch.compile` doesn't respect `GradTrackingTensor`'s data attribute mutation check | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
This is a bug exposed after #149482 opens up tensor attribute mutation for newly constructed tensor objects inside `torch.compile` region. Specifically the PR results in error of the following test
```
$ PYTORCH_TEST_WITH_DYNAMO=1 python test/functorch/test_ops.py TestOperatorsCPU.test_data_wri... | true |
2,944,833,904 | cache loaded python modules | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149910
* #149932
I am splitting caching the loading of modules from the caching the codegen since its trivial and much easier.
Module loading is 50% of the cost, and codegen is 50% of maybe_append choice on full graph model. which ... | true |
2,944,821,618 | [ued][kokoro] RNN/LSTMS do not work with torch.compile | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
As title.
### Error logs
_No response_
### Versions
NA
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @amjames | true |
2,944,802,836 | [ued][ChatTTS][guards] Too many recompilations | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
<img width="1755" alt="Image" src="https://github.com/user-attachments/assets/dcd5d85d-bce4-4657-a35f-ae9f6365fa7d" />
Some notes
* The dispatch key failure seems to be something we should look at.
* Is there a way to avoid the %8 guard?
* Can we use mark_dynamic to handle other recompiles?
W... | true |
2,944,795,204 | [ued][chatTTS][dynamo] Graph break on x.transpose_ | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
This might be a fundamental graph break. So, we might need to suggest a workaround.
<img width="1109" alt="Image" src="https://github.com/user-attachments/assets/57050dff-7c69-4c84-91ec-87f45c3be4de" />
Full tlparse - [https://manifold.edge.x2p.facebook.net/v0/read/tree/logs/.tmpZEpwwY/index.... | true |
2,944,789,684 | [ued][chatTTS][dynamo] graph break on should_compile_partial_graph=False | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
tlparse link - https://manifold.edge.x2p.facebook.net/v0/read/tree/logs/.tmpZEpwwY/-_15_0_0/dynamo_graph_break_reason_162.txt?bucketName=tlparse_reports&apiKey=tlparse_reports-key&withPayload=1&timeoutMsec=10000
Full tlparse - https://manifold.edge.x2p.facebook.net/v0/read/tree/logs/.tmpZEpwwY... | true |
2,944,787,571 | [Inductor] track block shape of intermediary variables | eellison | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
During codegen each we track the dtype and value range of each intermediary variable we emit in trition. See [CSEVariable](https://github.com/pytorch/pytorch/blob/23855391f1a17f7145885b5ef977547a70819505/torch/_inductor/codegen/common.py#L1669-L1680).
Dtype was recently added... | true |
2,944,757,872 | [cuDNN][SDPA] cuDNN SDPA supports `head_dim <= 256` on `sm90` and `sm100` as of `9.5.1+` | eqy | closed | [
"module: cudnn",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: sdpa",
"Blackwell"
] | 3 | COLLABORATOR | gqa check PR will go next...
cc @csarofeen @ptrblck @xwang233 | true |
2,944,756,827 | Fix non-strict export doesn't turn on dynamo for hop | ydwu4 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149903
Somehow the torch._dynamo.is_compiling is changed to torch.compiler.is_compiling(), which also checks whether we're exporting. This is not caught by cI because we don't have an export test for scan.
Changing to torch.... | true |
2,944,749,520 | [ROCm] build magma rocm and upload tarball | jeffdaily | closed | [
"module: rocm",
"open source",
"Merged",
"Reverted",
"release notes: releng",
"ciflow/rocm",
"ci-no-td"
] | 8 | COLLABORATOR | This will improve docker image build times by not having to rebuild magma rocm for unrelated changes. This PR is step 1 of 2. The next step is a second PR to modify the docker image builds to use the magma tarball that this PR will produce.
cc @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jata... | true |
2,944,733,767 | [ONNX] Supporting different opset versions for torchlib registry | shubhambhokare1 | closed | [
"module: onnx",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: new features"
] | 15 | COLLABORATOR | - Allows opset_version to determine which onnx decomposition to choose
- Adds a cleanup function to modify the registry after it is built
| true |
2,944,716,409 | [CI] Add MacOS-M2-15 as MPS test target on trunk | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Now that we have runners allocated by AWS
| true |
2,944,669,413 | [WIP] no normalizations abstractions | laithsakka | open | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149899
* #149267
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,944,663,202 | canary basic normalization | bobrenjc93 | closed | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149898
* #149415
This change was motivated by internal use case (https://fb.workplace.com/groups/1553867532149891/?multi_permalinks=1708481206688522&comment_id=1711739699696006¬if_id=1742399826944239¬if_t=work_feedback_reac... | true |
2,944,654,850 | [ca] support anomly mode nan checks with different semantics than eager | xmfan | closed | [
"Merged",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"module: compiled autograd"
] | 2 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150073
* #150074
* #149987
* __->__ #149897
see note in code
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhan... | true |
2,944,653,832 | canary to not do max | bobrenjc93 | closed | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149898
* __->__ #149896
* #149415
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,944,642,077 | [Dynamo] Cannot instantiate class if `__getattribute__` is defined | guilhermeleobas | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
Reproducer:
```python
import torch
class Foo():
def __init__(self, a):
self.a = a
def __getattribute__(self, name):
return super().__getattribute__(name)
@torch.compile(backend="eager", fullgraph=True)
def fn(t):
f = Foo(3)
return t.sin()
t = torch.randn(2)... | true |
2,944,631,630 | [ued][f5-tts][dynamo] `torch.compile` changes state dict | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Applying torch.compile to a model changes the state dict, and breaking loading of existing state dict checkpoints.
This issue is to figure out how to instruct users on avoiding this issue.
### Error logs
_No response_
### Versions
N/A
cc @chauhang @penguinwu @voznesenskym @EikanWang @jg... | true |
2,944,599,187 | DRAFT: Add TMA opt for concat function target hopper and blackwell arch | Mengran-nvidia | open | [
"triaged",
"open source",
"release notes: cuda"
] | 18 | NONE | Optimize the torch.cat() function targeting the hopper and Blackwell arch, by leveraging the TMA.
TODO: need to add logic to support concat along different dim in the tma_fast version. And some configurations need to be adjusted a little bit to achieve the peak perf.
| true |
2,944,567,485 | [draft] Add support in Flex for non-contiguous NJT | ani300 | open | [
"open source",
"module: nestedtensor",
"release notes: nested tensor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149892
* #145778
Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>
cc @cpuhrsch @jbschlosser @bhosmer @drisspg @soulitzer @davidberard98 @YuqingJ | true |
2,944,564,039 | [export] refactor _Dim into Dim | pianpwk | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"fx",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Summary: forward fix T218515233
Test Plan: test_export
Differential Revision: D71769231
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,944,561,841 | Fix autotune pool shutdown | masnesral | 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):
* __->__ #149890
* #149700
Summary: A couple follow-ups noted in review from https://github.com/pytorch/pytorch/pull/149700:
1. Make sure we correctly signal _all_ subproces to shutdown, even in the case where some processes are currently benc... | true |
2,944,560,722 | [windows] Linker receives wrong (non existent path) (solution path included) | loscrossos | closed | [
"module: windows",
"triaged",
"oncall: pt2"
] | 4 | NONE | ### 🐛 Describe the bug
@xuhancn @shunting314
this is a follow up bug to https://github.com/pytorch/pytorch/issues/149310#issuecomment-2745707169
I just came to test the change in https://github.com/pytorch/pytorch/commit/bc1b8730a45e659dca83ec83995c17d4eec9c869 as torch was built on nightly yesterday but torcha... | true |
2,944,545,391 | [Build] Remove pre-CXX11 ABI logic from build script | malfet | closed | [
"Merged",
"ciflow/trunk",
"release notes: build",
"topic: bc breaking",
"topic: improvements"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149888
Only keep one in check_binary_symbols to make sure there are no pre-CXX11 ABI symbols in the library | true |
2,944,545,267 | [CD] Check that nightly x86 binaries are build with gcc-11 | malfet | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149888
* __->__ #149887
Though they should have been with gcc-14, per https://github.com/pypa/manylinux?tab=readme-ov-file#manylinux_2_28-almalinux-8-based | true |
2,944,490,870 | TransformerDecoder produces identical outputs regardless of input | nicolacalzone | closed | [
"module: nn",
"triaged"
] | 1 | NONE | ### 🐛 Describe the bug
I'm building a decoder-only transformer using TransformerDecoder and TransformerDecoderLayer classes from the PyTorch library.
The model consistently produces the same output tensor regardless of the input, also with all rows in the output being identical.
### My environment:
```
Python 3.10.... | true |
2,944,487,821 | Add smoke test to validate pypi env version vs torch complied and installed versions of nccl and cudnn | atalman | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Followup after nccl update to validate both cudnn and nccl versions in nightly and release pipelines.
Tested on local dev machine, output.
Success:
```
Found matching cudnn. Torch: 9.5.1 PyPI 9.5.1.17
Found matching nccl. Torch: 2.25.1 PyPI 2.25.1
```
Failure:
```
Traceback (most recent call last):
File... | true |
2,944,482,017 | Update SGD documentation to match implementation | dscamiss | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: optim"
] | 14 | CONTRIBUTOR | Fixes #149476
This PR updates the pseudocode description of the SGD optimizer to better match the implementation.
Updated pseudocode:
 | true |
2,944,457,013 | [ROCm] missing AT_CUDA_CHECK for cub and SoftMax | ethanwee1 | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda",
"topic: not user facing",
"ciflow/rocm"
] | 3 | CONTRIBUTOR | cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,944,442,719 | [Bugfix] Add handling for buffer overrides | Lucaskabela | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Fixes #139167
This PR:
* uses `named_buffers` to mark static
* Checks that `named_buffers` is of expected type (callable, iterator) before trying to iterate over; if not, we skip this pass
These changes fix the previous errors in dynamo causing to crash (as shown in issue above)
### Unit Test
```
python ... | true |
2,944,420,703 | Dynamo `as_python_constant()` infinite recursion | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Repro:
```
import torch
@torch.compile(fullgraph=True, backend='eager')
def f(x):
l = []
l.append(l)
return l, x + 1
print(f(torch.ones(5)))
```
The reason is pretty simple, our `as_python_constant` implementations never took cycles into considerations:
https://github.com/pytorc... | true |
2,944,416,235 | from_blob does not recognize device | brccabral | closed | [
"module: cpp",
"triaged"
] | 1 | NONE | ### 🐛 Describe the bug
I my case this does not work
```cpp
std::array<int, 3> values={1,2,3};
auto ten = torch::from_blob(values.data(), {values.size()}, torch::kCUDA);
```
but this does
```cpp
auto ten2 = torch::from_blob(values.data(), {values.size()});
ten2 = ten2.to(torch::kCUDA);
```
Other issues I think are re... | true |
2,944,382,339 | Inductor Pattern Matcher's register_replacement function only works with functional `search_fn`s | zou3519 | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 4 | CONTRIBUTOR | it does an implicit DCE [here](https://github.com/pytorch/pytorch/blob/main/torch/_inductor/pattern_matcher.py#L2005) where it is constructing a graph structure and only cares about nodes that are "reachable" from the outputs
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhao... | true |
2,944,380,565 | Fix atomic operation compatibility for ARMv8-A (Raspberry Pi 4) by adjusting compilation flags | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | **Issue:**
* The ldaddal instruction is an AArch64 atomic operation available from ARMv8.1-A onwards.
* Raspberry Pi 4 (Cortex-A72) is ARMv8-A, which does not support ldaddal, leading to failures when running PyTorch built with march=armv8.2-a+sve
* This led to an issue when running PyTorch on ARMv8-A (Raspberry Pi ... | true |
2,944,329,205 | (Maybe unnecessary) FunctionCtx appears in dynamo graph in the presence of custom autograd functions | jamesjwu | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
FunctionCtx appears in dynamo graphs with custom autograd functions, but is immediately set to None (as far as I can tell, this happens every single time).
@zou3519 mentioned that this is not expected, and dynamo shouldn't be including these in the graph. Filing this issue to track this. It's... | true |
2,944,326,712 | [Async TP] Activations not cleared after backward when reduce_scatter_tensor saved for backward by per op SAC | danielvegamyhre | closed | [
"oncall: distributed",
"module: activation checkpointing",
"module: autograd"
] | 8 | CONTRIBUTOR | ### 🐛 Describe the bug
## Context
This is a follow up to the discussion here: https://github.com/pytorch/torchtitan/pull/965#issuecomment-2744476861
## Summary
After using the partitioner change which removes saved collective results which are not actually used for backward (https://github.com/pytorch/pytorch/pul... | true |
2,944,321,405 | [Async TP] Fuse matmul-reduce-scatters when reduce scatters have multiple users, and save fused node for backward instead of reduce_scatter node | danielvegamyhre | closed | [
"oncall: distributed",
"release notes: distributed (pipeline)",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Fixes #149876
## Stack
- [previous PR in stack] https://github.com/pytorch/pytorch/pull/149247
## TL;DR
This PR implements support in async TP for saving the reduce-scatter result for backward, which previously would break the torchtitan AC policies: no AC, per op SAC, and per layer SAC.
## Context
In torch... | true |
2,944,294,045 | ci/docker: use NCCL 2.26.2-1 | pytorchbot | closed | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Related to #149153
This updates some build scripts to hopefully fix the nightly builds which are somehow building against nccl 2.25.1 and using 2.26.2 from pip.
Test plan:
After merging rerun nightly linux jobs and validate that nccl version matches | true |
2,944,291,943 | add bobren and laithsakka as ds owners | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149873
| true |
2,944,252,269 | Do all lazy imports for torch.compile in one place? | zou3519 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 2 | CONTRIBUTOR | When benchmarking torch.compile with warm start, I noticed 2s of time in the backend before pre-grad passes were called. Upon further investigation I discovered this is just the time of lazy imports.
Lazy imports can distort profiles and hide problems, especially when torch.compile behavior changes on the first iterat... | true |
2,944,248,714 | Add release branch push triggers to inductor-rocm-mi300.yml | pytorchbot | closed | [
"module: rocm",
"open source",
"topic: not user facing",
"ciflow/rocm"
] | 1 | COLLABORATOR | In similar vein as https://github.com/pytorch/pytorch/pull/149517
When we added the rocm-mi300.yml earlier this year, we had lower capacity and we were just pipecleaning the workflow, so we set the trigger to only respond to pushes to main branch. But now we have more stability as well as capacity, and we would real... | true |
2,944,217,919 | Use variadic length tuple for `torch.masked.DimOrDims` | ringohoffman | closed | [
"open source",
"Merged",
"module: masked operators",
"ciflow/trunk",
"release notes: python_frontend"
] | 14 | CONTRIBUTOR | `tuple[int]` means only a tuple of length 1, which is not what was intended.
```python
loss = torch.masked.mean(loss, mask=mask, dim=(-1, -2)) # Argument of type "tuple[Literal[-1], Literal[-2]]" cannot be assigned to parameter "dim" of type "DimOrDims"
``` | true |
2,944,215,050 | ProcessGroupGloo: support reduce_scatter + update support chart | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | MEMBER | This adds a `reduce_scatter` implementation for ProcessGroupGloo. This is a pretty naive implementation as it does 1 allreduce per rank but may be useful for testing in FSDP etc. There was an existing implementation of reduce_scatter_tensor/reduce_scatter_tensor_coalesed that has a very similar implementation but requ... | true |
2,944,201,377 | [ROCm] fix uninitialized warning in BFloat16.h | ethanwee1 | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 3 | CONTRIBUTOR |
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,944,195,319 | Fix cusparseLt.so preload without nvidia directory | keith | closed | [
"triaged",
"open source",
"release notes: build",
"topic: bug fixes"
] | 4 | NONE | Since 2b241a8206843f43f0568b7b65473ebb593c4740, the `nvidia`
subdirectory existing is not enough to skip the rest of this logic since
other paths are now considered below.
| true |
2,944,190,402 | [MPS] tril op not handling infs correctly | Isalia20 | closed | [
"open source",
"Merged",
"topic: bug fixes",
"module: mps",
"release notes: mps",
"ciflow/mps"
] | 13 | COLLABORATOR | Fixes #149813
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen | true |
2,944,069,497 | Allow rebuild of triton on workflow_dispatch | atalman | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Allows to rebuild triton from main.
latest triton build failed : https://github.com/pytorch/pytorch/actions/runs/13984299781/job/39298288914
The cause PR was reverted: https://github.com/pytorch/pytorch/pull/148419
We need to rebuild the triton now
| true |
2,944,045,757 | [ONNX] Clean up the diagnostics module | justinchuby | closed | [
"module: onnx",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: onnx",
"topic: not user facing",
"skip-pr-sanity-checks",
"suppress-bc-linter",
"ci-no-td"
] | 11 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149864
Remove the diagnostics/SARIF module from ONNX exporter because it is obsolete unused.
cc @albanD | true |
2,944,030,253 | cd: Restore windows release builds for libtorch | seemethere | closed | [
"Merged",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing"
] | 5 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149863
These were accidentally deleted in the refactor of DEVTOOLSET +
cxx11abi.
This happened because the `build_environment` variable wasn't aware of the `build_variant` for libtorch and subsequently overwrote the original f... | true |
2,944,027,080 | [Inductor UT][Break XPU] Apply CUDA tolerances changes on XPU that introduced by #144579. | etaf | closed | [
"open source",
"Merged",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150830
* __->__ #149862
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,943,906,210 | Configure `cuda.cmake` to ensure consistent behavior downstream | jeongseok-meta | open | [] | 11 | CONTRIBUTOR | The current implementation of `cuda.cmake` relies on the option variable `USE_SYSTEM_NVTX`:
https://github.com/pytorch/pytorch/blob/9bae904cb47b2d896f4653f751f0526379823606/cmake/public/cuda.cmake#L173-L177
which is only set during the PyTorch build process:
https://github.com/pytorch/pytorch/blob/9bae904cb47b... | true |
2,943,748,727 | [MTIA] [Triton] Set codename of MTIA device in triton heuristics | PatriceVignola | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Summary: Triton-MTIA expects the codename of the device as the arch when querying the module map, not the compute capability. This diff gets rid of the following error: `No libdevice is provided for arch (0, 0)`
Test Plan: CI
Reviewed By: Myrthan
Differential Revision: D70072095
cc @voznesenskym @penguinwu @Eika... | true |
2,943,674,859 | DISABLED test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_int8 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 5 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_int8&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/p... | true |
2,943,674,718 | DISABLED test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_uint8 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 5 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_uint8&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/... | true |
2,943,589,643 | SDPA (`EFFICIENT_ATTENTION`) slower than torch.compile decomposition on `tf32` | abdulfatir | open | [
"triaged",
"oncall: pt2",
"module: sdpa"
] | 18 | NONE | ### 🐛 Describe the bug
**EDIT**: The core issue appears to be the use of `tf32`. Please see my comment: https://github.com/pytorch/pytorch/issues/149857#issuecomment-2753969061
I am running into an odd issue where SDPA efficient attention results in slower end to end training times compared to compiled manual attent... | true |
2,943,571,308 | Restore Missing Windows Libtorch Workflows | iremyux | closed | [
"triaged",
"open source",
"ciflow/binaries",
"release notes: build",
"topic: not user facing"
] | 2 | COLLABORATOR | After #149443, several Windows binary workflows were removed and replaced with new ones:
Removed Workflows:
.github/workflows/generated-windows-arm64-binary-libtorch-release-nightly.yml
.github/workflows/generated-windows-arm64-binary-libtorch-debug-nightly.yml
.github/workflows/generated-windows-binary-libtorch-... | true |
2,943,481,901 | [ROCm] Update libamd_comgr.so file in triton wheel build | ethanwee1 | closed | [
"module: rocm",
"open source",
"Merged",
"topic: not user facing",
"ciflow/rocm"
] | 3 | CONTRIBUTOR | In ROCm 6.4 and newer, when building Triton in the Triton-ROCm wheel build flow, newer releases of ROCm no longer have **libamd_comgr.so.2** as the .so file has been updated to **libamd_comgr.so.3** in ROCm 6.4 and newer. We conditionalize on which ROCm the wheel build is for, and choose the .so accordingly.
cc @j... | true |
2,943,322,634 | [Intel GPU][PT2E] Improve asymm qconv perf via weight prepack | ZhiweiYan-96 | open | [
"module: cpu",
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149854
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,943,309,899 | [nn] Implement PartialLinear module for structured sparsity | lakshminarasimmanv | closed | [
"feature",
"module: nn",
"triaged",
"open source",
"topic: not user facing"
] | 14 | NONE | Implements PartialLinear, a linear layer that maintains sparse connectivity by keeping only the top-k weights by magnitude for each output neuron.
- Adds new PartialLinear class to nn/modules/linear.py
- Supports dynamic connectivity updates during training
- Provides both masked-dense and pure-sparse computation ... | true |
2,943,234,790 | [DYNAMO] [BUG FIX] correct casting to boolean for TORCH_COMPILE_DISABLE | golkir | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Fixes #149840
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,943,066,881 | [Dynamo] Add easydict support | shink | open | [
"triaged",
"open source",
"topic: not user facing",
"module: dynamo"
] | 13 | CONTRIBUTOR | Fixes #149583
See: https://github.com/pytorch/pytorch/pull/149851#issuecomment-2782208670
## Test
```bash
python test/dynamo/test_dicts.py -k EasyDictTests
```
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauha... | true |
2,942,933,021 | Combine windows x64 and arm64 yaml template files | iremyux | closed | [
"module: windows",
"triaged",
"open source",
"Merged",
"ciflow/binaries",
"topic: not user facing",
"skip-pr-sanity-checks"
] | 10 | COLLABORATOR | While introducing Windows-Arm64 nightly workflows, we created a separate template file for win-arm64. This PR combines x64&arm64 and deletes the win-arm64 one.
Fixes #148776
cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @Blackhex @albanD | true |
2,942,765,182 | Fix #149550: Remove pre-cxx11 from documentation and tutorials | copley | open | [
"triaged",
"open source",
"topic: not user facing"
] | 12 | NONE | Fix #149550
This PR removes all occurrences of 'pre-cxx11' from the documentation in
docs/cpp/source/installing.rst and docs/source/cpp_index.rst.
| true |
2,942,618,711 | Refactoring FSDP2 (_composable/fsdp) test cases to be device agnostic | AnantGulati | open | [
"oncall: distributed",
"triaged",
"open source",
"topic: not user facing"
] | 22 | CONTRIBUTOR | The motivation for this PR is refactor existing test cases in the folder test/distributed/_composable/fsdp/ or fsdp2(as referred to in torch titan) to be device agnostic such that any accelerator type is supported (for eg. CUDA, HPU, XPU etc)
The changes are in line with previously merged changes for fsdp (present i... | true |
2,942,517,825 | Add SWA with a cyclical scheduler example | zeshengzong | open | [
"open source",
"release notes: optim"
] | 2 | CONTRIBUTOR | Fixes #74022
## Changes
- Add example of SWA with a cyclical scheduler
- Fix optional tag missing in params
| true |
2,942,328,240 | Memory leak in torch.save | cdzhan | open | [
"needs reproduction",
"module: memory usage",
"module: serialization",
"triaged"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
It seems that the storage of tensor was not released immediately after this #136034.
```python
>>> import torch
>>> import gc
>>> def test():
... a = torch.randn(3)
... torch.save(a, 'test.pt')
...
>>> gc.set_debug(gc.DEBUG_SAVEALL)
>>> test()
>>> gc.collect()
35
>>> a = gc.garbage
>>> a
[{... | true |
2,942,318,348 | CUDA error: no kernel image is available for execution on the device RTX5090D | yourbikun | open | [
"module: build",
"module: cuda",
"triaged"
] | 1 | NONE | ### 🐛 Describe the bug
I encountered problems when running PyTorch on an RTX 5090D in Ubuntu. I installed PyTorch (torch) and CUDA in a Conda environment, and the following issues occurred:
>>> import torch
>>> x = torch.tensor([0, 1, 1]).to(0)
>>> print(x.device)
cuda:0
>>> x != 0
Traceback (most recent call last):... | true |
2,942,310,108 | Update slow tests | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/slow",
"ci-no-td"
] | 3 | COLLABORATOR | This PR is auto-generated weekly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/weekly.yml).
Update the list of slow tests. | true |
2,942,168,842 | [BE] Replace XPU support packages installation to offline mode in Linux CI/CD | chuanqi129 | open | [
"triaged",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ci-no-td"
] | 20 | COLLABORATOR | To ensure the build environment is stable
Fixes #149995 | true |
2,942,035,920 | Implement aten.select.int sharding strategy | kkkkeeee | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"module: dtensor"
] | 15 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149842
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @tianyu-l @XilunWu | true |
2,941,958,016 | `weight` parameter on functional not in nn.Module | neosr-project | open | [
"module: nn",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
When using `nn` losses, the parameter `weight` is not supported, although added on their functional counterpart:
```python
import torch
loss = torch.nn.L1Loss(weight=0.5)
#Traceback (most recent call last):
# File "<stdin>", line 1, in <module>
#TypeError: L1Loss.__init__() got an unexpecte... | true |
2,941,903,562 | Export TORCH_COMPILE_DISABLE=0 continues to disable torch.compile | jerrychenhf | closed | [
"triaged",
"actionable",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Running the following program with export TORCH_COMPILE_DISABLE=0 will still disable torch.compile (cnt.frame_count is 0)
```
import torch
import torch._dynamo.testing
device = "cpu"
cnt = torch._dynamo.testing.CompileCounter()
def m(input):
for i in range(8):
input = input * 3
retu... | true |
2,941,851,469 | Custom Autograd Functions Don't Work in C++ if it takes Tensors[] as arguments | borisfom | closed | [
"module: cpp",
"module: autograd",
"triaged"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
This kind of custom operators don;t seem to work :
```
TORCH_LIBRARY_FRAGMENT(cuequivariance_ops_torch, m)
{
// Define an operator schema ... | true |
2,941,753,923 | Improve error message for CUDAGuardImpl, MPSGuardImpl, XPUGuardImpl | shink | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"release notes: mps",
"ciflow/mps",
"ciflow/xpu"
] | 16 | CONTRIBUTOR | Fixes #149822
Will get:
```
RuntimeError: t == DeviceType::CUDA INTERNAL ASSERT FAILED at "/home/jyh/workspace/pytorch/c10/cuda/impl/CUDAGuardImpl.h":28, please report a bug to PyTorch. CUDAGuardImpl initialized with non-CUDA DeviceType: cpu
``` | true |
2,941,720,234 | Intermittent "AssertionError: can only test a child process" Warning with PyTorch DataLoader on Colab | n3than | open | [
"module: multiprocessing",
"module: dataloader",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
Description
I'm encountering an intermittent warning when training a model on Colab using PyTorch. The warning arises during the shutdown of DataLoader worker processes and reads:
```
Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at ...>
...
AssertionError: can only te... | true |
2,941,472,558 | torch.hanning_window create values different from the formula | chinshou | closed | [] | 2 | NONE | ### 🐛 Describe the bug
```
window_length = 16
torch.hann_window(
window_length=window_length , periodic=True)
```
will create a value list with wrong value
0, 0.03806, ...., 0.1464, 0.03806,
`scipy.signal.windows.hann(window_length) `
will create a different value list
0, 0.0432272711, ...., 0.165434... | true |
2,941,468,028 | Clarified tensor definition in README | onepequity | closed | [
"open source",
"topic: not user facing"
] | 2 | NONE | Updated the tensor definition in the README for better clarity by replacing 'ndarray' with 'n-dimensional array'.
| true |
2,941,438,817 | `@torch.compile` and a nested `@torch.compiler.disable` leaks memory | koute | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | NONE | ### 🐛 Describe the bug
Consider the following code:
```python
import torch
import torch.nn as nn
class Inner(nn.Module):
@torch.compiler.disable
def forward(self, x, x0):
return x
class Outer(nn.Module):
def __init__(self):
super().__init__()
self.inner = Inner()
@torch.com... | true |
2,941,421,792 | Suppress more warnings | tugsbayasgalan | closed | [
"Merged",
"ciflow/trunk",
"fx",
"ciflow/inductor",
"release notes: export"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149833
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv
Differential Revision: [D71702307](https://our.internmc.facebook.com/intern/diff/D71702307) | true |
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