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 |
|---|---|---|---|---|---|---|---|---|
2,776,226,574 | Link to transformer tutorial in transformer docs | mikaylagawarecki | closed | [
"Merged",
"ciflow/trunk",
"release notes: nn",
"topic: docs"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144425
<img width="1045" alt="Screenshot 2025-01-08 at 4 50 20 PM" src="https://github.com/user-attachments/assets/05adfecb-8a23-4c48-9a2c-50c5b3f886b0" />
| true |
2,776,181,971 | Implement `generator.throw(exception)` | guilhermeleobas | closed | [
"open source",
"Merged",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #142513
* #145223
* #144420
* __->__ #144424
* #144423
* #144422
* #144421
* #141055
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amja... | true |
2,776,181,757 | Implement `generator.close()` | guilhermeleobas | closed | [
"open source",
"Merged",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #142513
* #145223
* #144420
* #144424
* __->__ #144423
* #144422
* #144421
* #141055
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amja... | true |
2,776,181,493 | Implement `generator.send(..)` | guilhermeleobas | closed | [
"open source",
"Merged",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #142513
* #145223
* #144420
* #144424
* #144423
* __->__ #144422
* #144421
* #141055
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amja... | true |
2,776,181,363 | Implement `generator.__iter__()` | guilhermeleobas | closed | [
"open source",
"Merged",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #142513
* #145223
* #144420
* #144424
* #144423
* #144422
* __->__ #144421
* #141055
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amja... | true |
2,776,181,212 | Add `CLEANUP_THROW` bytecode | guilhermeleobas | closed | [
"open source",
"Merged",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #142513
* #145223
* __->__ #144420
* #144424
* #144423
* #144422
* #144421
* #141055
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amja... | true |
2,776,172,823 | [dynamo] Avoid graph break on updates to `obj.__dict__` | StrongerXi | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144419
`obj.__dict__` is handled specially in Dynamo, and prior to this patch
we only support read and membership check on that dictionary object.
This patch adds support for writes and some documentation.
Fixes #143756.
cc @vozne... | true |
2,776,109,172 | [ONNX] Avoid overwriting overlapped decomposed functions | pytorchbot | closed | [
"open source",
"release notes: onnx"
] | 1 | COLLABORATOR | Fixes #141770
The decomposed function in `torch.export.default_decompositions().items()` is overwritten by `torch._decomp.decomposition_table`. As from `torch.onnx.export()` perspective, we should rather respect the table of decompositions in `torch.export.default_decompositions().items()` and avoid overwriting it ... | true |
2,776,100,913 | [ONNX] Handle list values as 0d inputs | pytorchbot | closed | [
"open source",
"release notes: onnx"
] | 1 | COLLABORATOR | Handle list values as 0d inputs instead of 1d, as the `SymInt`s are expected to be 0d tensors in ONNX.
This PR reshapes int64 values into 1D tensors in a list, assuming they are 0D tensors initially. | true |
2,776,099,826 | Allows pep658 metadata uploader script to backfill for prefix | clee2000 | closed | [
"topic: not user facing"
] | 1 | CONTRIBUTOR |
Test
`uv run scripts/release/upload_metadata_file.py --use-s3-prefix --bucket pytorch --key-prefix whl/nightly/cpu-cxx11-abi --dry-run
`
I also did the upload of one file without dry run and checked that metadata uploaded looked sane.
I wonder if this would be better put in test-infra's s3 index manager scrip... | true |
2,776,015,857 | [BE] fix ruff rule E226: add missing whitespace around operator in f-strings | XuehaiPan | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"release notes: releng",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144415
The fixes are generated by:
```bash
ruff check --fix --preview --unsafe-fixes --select=E226 .
lintrunner -a --take "RUFF,PYFMT" --all-files
```
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d... | true |
2,776,012,778 | [do not land] Test warm start compile latency with fx graph caching | masnesral | closed | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144414
* #144413
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aak... | true |
2,776,009,884 | [do not land] Test warm start compile latency with triton caching | masnesral | closed | [
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144414
* __->__ #144413
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aak... | true |
2,776,000,671 | [do not land] Test warm start compile latency with fx graph caching | masnesral | closed | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144412
* #144411
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aak... | true |
2,776,000,451 | [do not land] Test warm start compile latency with triton caching | masnesral | closed | [
"module: inductor",
"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 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,775,999,184 | [do not land] Test warm start compile latency with triton caching | masnesral | closed | [
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144410
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,775,965,131 | Set maximum supported version of Python as 3.13 | pytorchbot | closed | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Same as https://github.com/pytorch/pytorch/pull/119743 Required for Release 2.6.0 | true |
2,775,927,307 | torchgen: sharded_keys should be immutable | swolchok | closed | [
"fb-exported",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144408
* #144364
* #144363
Per @Skylion007.
Differential Revision: [D67943449](https://our.internmc.facebook.com/intern/diff/D67943449/) | true |
2,775,900,157 | Remove extra copy torch/_prims | LlamaFarm | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | updated _reshape_aten
| true |
2,775,886,087 | [inductor][cpu] Fix accuracy error in BMM benchmarking for input weight with offset | frost-intel | closed | [
"open source",
"Stale",
"topic: not user facing",
"module: inductor"
] | 3 | COLLABORATOR | Fixes #143770
When an input weight tensor has an offset (i.e. is a slice of another larger tensor at non-zero dim) the test/benchmarking process was changing the benchmarking argument to be only the one slice instead of the entire tensor. This resulted in an accuracy error and potentially a crash if in `VERIFY` mod... | true |
2,775,829,268 | [BE][pytree][Easy] change imports `torch.utils._pytree` -> `torch.utils.pytree.python` | XuehaiPan | open | [
"oncall: distributed",
"open source",
"Stale",
"release notes: quantization",
"release notes: distributed (fsdp)",
"topic: not user facing",
"module: pytree",
"fx",
"ciflow/mps",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd",
"oncall: distributed chec... | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144332
* #130141
* __->__ #144405
* #137400
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @zou3519 @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @Xiaob... | true |
2,775,800,091 | [DTensor] Add `aten.view.dtype` op support | awgu | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: distributed (dtensor)"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144404
Fixes https://github.com/pytorch/pytorch/issues/144286
Viewing a tensor to a different dtype does not require any redistribution and can use the default strategy.
cc @H-Huang @kwen2501 @wanchaol @fegin @fduwjj @wz337 ... | true |
2,775,791,527 | Extended functionality for torch.quantization.fuse_modules | Kautenja | open | [
"oncall: quantization",
"triaged"
] | 4 | NONE | ### 🚀 The feature, motivation and pitch
The method `torch.quantization.fuse_modules` supports many of the common fusion strategies, i.e., conv+bn, conv+bn+relu, etc. However, there are additional fusion operations that are useful in practice that could be interesting. Specifically, cascades of bn+linear layers can ac... | true |
2,775,791,001 | `Dirichlet.mode`: use `dim=` instead of `axis=` | randolf-scholz | closed | [
"module: distributions",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | `axis=` is undocumented and will raise typing errors when #144197 is merged.
See: https://github.com/pytorch/pytorch/pull/144197#pullrequestreview-2537398866
cc @fritzo @neerajprad @alicanb @nikitaved | true |
2,775,770,361 | ReshapeTransform: added missing argument in docstring | randolf-scholz | closed | [
"module: distributions",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: python_frontend"
] | 7 | CONTRIBUTOR | See https://github.com/pytorch/pytorch/pull/144197#discussion_r1907336339
cc @fritzo @neerajprad @alicanb @nikitaved | true |
2,775,760,331 | Fix `AffineTransform.sign` | randolf-scholz | closed | [
"module: distributions",
"open source",
"release notes: python_frontend"
] | 4 | CONTRIBUTOR | Fixes a bug where `AffineTransform.sign` could return a `Tensor` instead of `int`.
`AffineTransform` is applied element-wise, so the jacobian is diagonal and the sign of the determinant is the product of the signs of the diagonal entries.
See: https://github.com/pytorch/pytorch/pull/144197#discussion_r1907328379... | true |
2,775,751,767 | Update the Triton DeviceInterface in test/inductor/extension_backends/triton/device_interface.py | GeorgeWigley | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor"
] | 14 | CONTRIBUTOR | Following the changes to how `DeviceInterface` is used in this [PR](https://github.com/pytorch/pytorch/pull/142033), the `DeviceInterface` in `extension_backend/triton/device_interface.py` should by updated to return the `DeviceProperties` instead of raising a NotImplementedError.
This PR mirrors the [changes](https... | true |
2,775,687,940 | ROCm SDPA: Ensure attn_mask has the same dtype with q | pytorchbot | closed | [
"module: rocm",
"open source",
"ciflow/rocm"
] | 1 | COLLABORATOR | This is required by current AOTriton's backend.
Fixes NaN when calling SDPA ME backend with `q.dtype() != attn_mask.dtype()` when training llama2 using transformers+deepspeed+pytorch
Corresponding CUDA check seems to be here:
https://github.com/pytorch/pytorch/blob/708ce3c0082d670d9eaff84bc3c43cad4554a75d/aten/... | true |
2,775,679,163 | Optimizer state cannot get offloaded to CPU | fingertap | closed | [
"triaged",
"module: fsdp"
] | 7 | NONE | ### 🐛 Describe the bug
When I try to offload the FSDP optimizer state to CPU, most states get left on GPU. This only happens with FSPD, and it is fine when I use a normal nn.Module.
nn.Module (using `main`):
FSDP (using `... | true |
2,775,657,894 | Set maximum supported version of Python as 3.13 | atalman | closed | [
"Merged",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Same as https://github.com/pytorch/pytorch/pull/119743 Required for Release 2.6.0 | true |
2,775,634,966 | Fix fractional_max_pool lowering in inductor | isuruf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 9 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144395
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov
... | true |
2,775,602,574 | fix a bug for constant_pad_nd | ywq880611 | open | [
"triaged",
"open source",
"Stale"
] | 13 | CONTRIBUTOR | Fixes #144187
This PR sync the implement of `constant_pad_nd` in cpp with its implement in python, please see details in the issue.
| true |
2,775,356,940 | [3.13t] use sysconfig to check for Python nogil builds | pytorchbot | closed | [
"open source",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144361
`sys._is_gil_enabled()` wasn't working in certain cases, according to @atalman
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @c... | true |
2,775,298,714 | EP_FAIL : Non-zero status code returned while running Conv node. Name:'/features/features.0/Conv' Status Message: Failed to initialize CUDNN Frontend | m0hammadjaan | closed | [
"module: cudnn",
"module: convolution",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
I have an EC2 instance of type g5g.xlarge. I have installed the following:
```
CUDA-Toolit: Cuda compilation tools, release 12.4, V12.4.131
CUDNN Version: 9.6.0
Python: 3.12
Pytorch: Compiled from source as for aarch64 v2.5 is not available.
Onnxruntime: Compiled from source as the distru... | true |
2,775,261,339 | Fix a bug for conj_physical | ywq880611 | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Fixes #141426
fix a bug in previous [PR](https://github.com/pytorch/pytorch/pull/141427), which shouldn't convert the data type for conj. | true |
2,775,172,890 | `torch.linalg.solve`: doc update on dealing with rank-deficient systems which admit a solution | nikitaved | closed | [
"triaged",
"open source",
"module: linear algebra",
"Stale",
"release notes: linalg_frontend",
"topic: docs"
] | 6 | COLLABORATOR | As per title.
cc @jianyuh @pearu @mruberry @walterddr @xwang233 @Lezcano | true |
2,775,122,642 | Fix lowering to inductor IR for triton CPU | kundaMwiza | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 15 | CONTRIBUTOR | Example failing test:
`pytest -s test_torchinductor_opinfo.py -k test_comprehensive_special_polygamma_special_polygamma_n_0_cpu_float32` when using triton CPU.
Failure:
```shell
triton.compiler.errors.CompilationError: at 10:11:
def triton_poi_fused_polygamma_0(in_ptr0, out_ptr0, xnumel, XBLOCK : tl.constexpr... | true |
2,775,080,085 | Add test cases of fp8 datatypes in pt2e | yintong-lu | closed | [
"triaged",
"open source",
"Stale",
"release notes: quantization"
] | 2 | CONTRIBUTOR | As fp8 datatypes have been added to torch export serialization, this PR aims to add test cases of fp8 datatypes in pt2e quantization.
| true |
2,775,037,908 | Adapt Dynamo tests to HPUs using instantiate_device_type_tests | amathewc | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 26 | CONTRIBUTOR | **MOTIVATION**
We recently integrated support for Intel Gaudi devices (identified as 'hpu') into the common_device_type framework via the pull request at https://github.com/pytorch/pytorch/pull/126970. This integration allows tests to be automatically instantiated for Gaudi devices upon loading the relevant library.... | true |
2,775,015,191 | cudagraph trees support handling live tensors from a previous run? | wbigat | closed | [
"triaged",
"module: cuda graphs",
"oncall: pt2"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Hello，when I try cudagraph trees，I find the following case in ```https://pytorch.org/docs/2.4/torch.compiler_cudagraph_trees.html#cudagraph-trees```
```
import torch
@torch.compile(mode="reduce-overhead")
def my_model(x):
y = torch.matmul(x, x)
return y
x = torch.randn(10,... | true |
2,774,927,870 | [Intel GPU] fix memory leak in deconv backward | jianyizh | closed | [
"module: cpu",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"ciflow/xpu",
"release notes: xpu",
"module: xpu"
] | 13 | CONTRIBUTOR | Fixes #143807
We need manage onednn scratchpad in pytorch, otherwise onednn will always allocate scratchpad memory during primitive execution and causes memory leak.
cc @gujinghui @EikanWang @fengyuan14 @guangyey @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,774,913,306 | ``torch.linalg.eigh`` produces significant errors compared to ``numpy.linalg.eigh`` | vuonghy2442 | closed | [
"triaged",
"module: linear algebra"
] | 8 | NONE | ### ``torch.linalg.eigh`` producing inaccurate eigenvalues/eigenvectors compared to NumPy
### Steps to Reproduce
1. Use the matrix A provided in the code below.
2. Compute the eigenvalues and eigenvectors using both torch.linalg.eigh and np.linalg.eigh.
3. Compare the results.
```python
import torch
import... | true |
2,774,838,127 | Totensor seems to have a memory leak | angel-yi | closed | [] | 0 | NONE | ### 🐛 Describe the bug
```python
tensor = transforms.ToTensor()(image)
tensor = transforms.Normalize(mean=self.cfg['MEAN'], std=self.cfg['STD'], inplace=True)(tensor)
tensor = tensor.unsqueeze_(0)
tensor = tensor.to(self.device)
```
use memory_profiler
Continuously accumulating memory
```
Line # Mem usage... | true |
2,774,788,159 | [ONNX] MelSpectrogram results in "Pads has incorrect number of values" | WangHHY19931001 | closed | [
"module: onnx",
"triaged"
] | 10 | NONE | ### 🐛 Describe the bug
``` python
class DataCov(nn.Module):
def __init__(self):
super(DataCov, self).__init__()
self.transform = nn.Sequential(
torchaudio.transforms.MelSpectrogram(sample_rate=48000, n_fft=1536, hop_length=768, f_min=20, f_max=20000)
)
def forwar... | true |
2,774,786,956 | onnx export error | WangHHY19931001 | closed | [] | 1 | NONE | ### 🐛 Describe the bug
``` python
class DataCov(nn.Module):
def __init__(self):
super(DataCov, self).__init__()
self.transform = nn.Sequential(
torchaudio.transforms.MelSpectrogram(sample_rate=48000, n_fft=1536, hop_length=768, f_min=20, f_max=20000)
)
def forwar... | true |
2,774,751,007 | Update readme | Lonely523 | closed | [
"topic: not user facing"
] | 2 | NONE | add dependency
| true |
2,774,680,653 | Refine torch.xpu.get_device_properties API error message | guangyey | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu",
"release notes: xpu"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144379
# Motivation
Remove the redundant error message.
Without this PR:
```python
>>> import torch
>>> torch.xpu.get_device_name(1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/gu... | true |
2,774,670,017 | Filter out iGPU if dGPU is found on XPU | guangyey | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu",
"release notes: xpu"
] | 9 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144378
# Motivation
for https://github.com/pytorch/pytorch/issues/143914
On Windows, there are two separate SYCL platforms for iGPU and dGPU. To simplify the logic, we will exclude iGPUs when a dGPU is present. This ensures that a... | true |
2,774,425,008 | error in RMSNorm documentation | yuanyao-nv | closed | [] | 1 | NONE | ### 📚 The doc issue
The formula for RMS [documentation ](https://pytorch.org/docs/stable/generated/torch.nn.modules.normalization.RMSNorm.html) should have MS instead of RMS on the denominator. Writing RMS inside sqrt implies there are two sqrt operations.
![image](https://github.com/user-attachments/assets/631e1675... | true |
2,774,404,478 | torch.compile post_accumulate_grad_hook ordering is wrong for tiebreakers | xmfan | open | [
"triaged",
"oncall: pt2",
"module: aotdispatch",
"module: pt2-dispatcher"
] | 0 | MEMBER | ### 🐛 Describe the bug
```python
import torch
import torch.nn as nn
import functools
model = nn.Sequential(
nn.Linear(10, 10, bias=False), # i=0
nn.Linear(10, 10, bias=False), # i=1
nn.Linear(10, 10, bias=False), # i=2
)
hook_ordering = []
def hook(param, i):
global hook_ordering... | true |
2,774,361,882 | Unable to compile models using tensorrt backend: CUDNN_STATUS_BAD_PARAM_STREAM_MISMATCH | deo-abhijit | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | ### 🐛 Describe the bug
When i use torch compile with tensorrt backend, im getting following error.
apparently tracing for conv2d operation is getting too many values (my guess)?
```bash
convolution = torch.ops.aten.convolution.default(slice_1, arg3_1, None, [2, 2], [3, 3], [1, 1], False, [0, 0], 1); sli... | true |
2,774,339,345 | [mps/inductor] Add support for rsqrt(). | 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 @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,774,324,177 | [Windows] Experimental `torch.compile` support for Windows on XPU | Stonepia | closed | [
"module: windows",
"oncall: pt2",
"module: inductor",
"module: xpu"
] | 6 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
BKC for Experimental Support on `torch.compile` for Windows on XPU
This document provides early experimental support for `torch.compile` on Windows with XPU. It tracks the status and known issues.
- [1. Overall Branch](#1-overall-branch)
- [2. Build Steps](#2-build-ste... | true |
2,774,313,667 | [dynamo] log compiler collective duration to tlparse chromium trace | xmfan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144372
To show wall time in tlparse for the synchronous compiler collective. Can eliminate the leading hypothesis from https://fb.workplace.com/groups/1075192433118967/permalink/1578670289437843.
<img width="1296" alt="image" src... | true |
2,774,248,961 | [codemod] Remove unused-variable in caffe2/aten/src/ATen/native/quantized/cpu/fbgemm_utils.cpp +2 | r-barnes | closed | [
"oncall: distributed",
"module: cpu",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: quantization",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Summary:
LLVM-15 has a warning `-Wunused-variable` which we treat as an error because it's so often diagnostic of a code issue. Unused variables can compromise readability or, worse, performance.
This diff either (a) removes an unused variable and, possibly, it's associated code or (b) qualifies the variable with `... | true |
2,774,199,471 | [RELAND] Generalize at::manual_seed for all accelerators | guangyey | closed | [
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: improvements",
"topic: not user facing",
"ciflow/mps",
"ciflow/rocm",
"ciflow/xpu",
"ci-no-td",
"module: accelerator"
] | 7 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144370
# Additional Context
This is a reland PR originated from eeb57394f93d720bca498c3fa9d167fc7b9cca46
cc @albanD @EikanWang | true |
2,774,164,162 | Migrate from Tuple -> tuple in torch/utils/data | bobrenjc93 | closed | [
"release notes: dataloader"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144369
Pull Request resolved: #144255 | true |
2,774,161,250 | [Don't Merge] Fix poision child process issue when call getAccelerator() | guangyey | closed | [
"oncall: jit",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: improvements",
"topic: not user facing",
"ciflow/xpu",
"ci-no-td",
"module: accelerator"
] | 13 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144664
* __->__ #144368
# Motivation
fix https://github.com/pytorch/pytorch/issues/144152
# Solution
- Align `at::globalContext()::hasXXX` to determine if accelerator XXX is built with PyTorch or an extension already registered to P... | true |
2,774,087,022 | [XPU] quantile related tests failed with Assertion failed: helper.isSupportedLayout() && "Unexpected srcLayout in ReduceOpConversion" | Stonepia | closed | [
"triaged",
"module: xpu"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
When running the UT on Windows/Linux:
```Python
pytest -k test_comprehensive_nanquantile_xpu_float32 -v test_torchinductor_opinfo.py
pytest -k test_comprehensive_quantile_xpu_float32 -v test_torchinductor_opinfo.py
```
The test failed with the following:
```Python
Assertion f... | true |
2,774,077,428 | disable experimental benchmarker | nmacchioni | open | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144366
* #144507
* #144505
* #144501
* #144353
* #133287
* #144365
* #133121
* #133058
* #144315
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 ... | true |
2,774,077,329 | implement LazyInductorBenchmarker | nmacchioni | closed | [
"module: rocm",
"Stale",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144507
* #144505
* #144501
* #144353
* #133287
* __->__ #144365
* #133121
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd @voznesenskym @penguinwu @EikanWang @jgong5 @Gu... | true |
2,774,035,904 | Shard RegisterDispatchKey | swolchok | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: build"
] | 13 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144364
* #144363
Should fix https://github.com/pytorch/pytorch/issues/143952 .
Testing: built PyTorch on Raspberry Pi 5; this seemed to alleviate high peak memory requirement. (I did increase shard counts for other generated file... | true |
2,774,035,714 | torchgen: move dispatch_helpers out of RegisterDispatchDefinitions.ini | swolchok | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: build"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144364
* __->__ #144363
The dispatch_helpers should be generated once, not once per kernel namespace.
Differential Revision: [D67925497](https://our.internmc.facebook.com/intern/diff/D67925497/) | true |
2,774,032,221 | Some operators miss dtype check when using `torch.compile` | maybeLee | open | [
"module: error checking",
"triaged",
"module: structured kernels",
"oncall: pt2",
"module: inductor"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
As reported here (https://github.com/pytorch/pytorch/issues/144314#issuecomment-2574508557), I notice some operators missing dtype check when executed in the context of `torch.compile`. The specific symptom is as follows:
- Eager Mode: Raises `not implemented for [specific dtype]` error
- torch... | true |
2,774,027,067 | [3.13t] use sysconfig to check for Python nogil builds | williamwen42 | closed | [
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144361
`sys._is_gil_enabled()` wasn't working in certain cases, according to @atalman
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @c... | true |
2,774,010,872 | Skip empty frames recursively when top-level is empty | ydwu4 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
def k(x):
return x
def g(x):
return k(x)
def f(x):
return g(x)
a = torch.ones(2, 2)
c = torch.compile(f, fullgraph=True)(a)
```
The above compile 3 times, f, g, and k with following log:
```
I0107 16:55:09.455000 1702873 torch/_dynamo/ut... | true |
2,773,999,079 | Incorrect Results with Tensor Parallelism | amogkam | open | [
"oncall: distributed"
] | 3 | NONE | ### 🐛 Describe the bug
I am trying a basic Tensor Parallel implementation on a 2 layer MLP using `ColwiseParallel` followed by a `RowwiseParallel`. I would expect the final output of the MLP to be the same in the Tensor Parallel version compared to the non-parallelized version. However, the output tensors are differe... | true |
2,773,991,895 | [ONNX] Update images and APIs to onnx_dynamo.rst | titaiwangms | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: docs",
"suppress-bc-linter"
] | 15 | COLLABORATOR | Update the result image of exporting, and delete the functions/class that belongs to `torch.onnx.dynamo_export` | true |
2,773,985,315 | python-3.13t binaries are only available for Linux x86 | malfet | closed | [
"module: binaries",
"oncall: releng",
"triaged"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
Looking at https://download.pytorch.org/whl/test/torch/ I've noticed that 3.13t binaries are only available for Linux-x86, neither linux-aarch64, not Windows nor Mac support those
### Versions
2.6/CI
cc @seemethere @osalpekar @atalman | true |
2,773,943,148 | [ONNX] Use torch.export.Dim.AUTO in dynamo_export | titaiwangms | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: improvements"
] | 3 | COLLABORATOR | Align to the changes in https://github.com/pytorch/pytorch/pull/143158 | true |
2,773,939,907 | Add `is_dtype_supported` predicate to DeviceInterface | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Which will return true, unless dtype is bf16 by default
For MPS device it will return false if dtype is double
Check that it works by refactoring `test_inf` that should expect TypeError raised if invoked with unsupported dtype
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaoz... | true |
2,773,885,857 | Improve torchrun documentation | fepegar | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 13 | CONTRIBUTOR | Fixes #142042:
- #142042
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,773,874,438 | implement pruning for GroupedInductorBenchmarker | nmacchioni | closed | [
"Stale",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144507
* #144505
* #144501
* __->__ #144353
* #133287
* #144365
* #133121
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8... | true |
2,773,865,542 | [Pipelining] Fix PP grad scaling | wconstab | closed | [
"oncall: distributed",
"Merged",
"release notes: distributed (pipeline)"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144734
* #144596
* __->__ #144352
Adds a grad-scaling method `perform_pp_grad_scaling()` which divides grads by num_microbatches.
Enables grad scaling by default, unless disabled due to using a loss function that sums instead of averagi... | true |
2,773,814,912 | Add fp8 content for hipify | PoodleWang | closed | [
"fb-exported",
"topic: not user facing"
] | 12 | NONE | Summary:
Add fp8 hipify content.
Test plan:
Internal test for NV and AMD GPUs.
Internal usage for meta. [D67305195]
| true |
2,773,745,007 | Remove tests for linux-focal-py3_9-clang10-build | zxiiro | closed | [
"triaged",
"open source",
"topic: not user facing"
] | 4 | COLLABORATOR | The 2 test suites seem to run the same tests.
* linux-focal-py3_9-clang10-build
* linux-focal-py3_13-clang10-build
Perhaps we can reduce redundancy and only run the test suites with one of the builds?
```
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "${{ needs.get-lab... | true |
2,773,693,492 | codecache.py: Utilize precompiled headers for CPP python bindings | benjaminglass1 | closed | [
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144349
* #144293
* #146928
Significantly increase default inductor OpInfo testing speed by precompiling a complex header included in CPU tests.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @... | true |
2,773,671,121 | Add SM89 support for f8f8bf16_rowwise() | alexsamardzic | closed | [
"module: cuda",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"no-runner-experiments"
] | 12 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144348
cc @ptrblck @msaroufim @eqy @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire... | true |
2,773,596,696 | [CD] Aarch64 builds should not override `OVERRIDE_PACKAGE_VERSION` envvar | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | Currently our nightly aarch64 binaries have correct suffixes +cpu or +cu126. But release binaries are missing these suffixes. Hence to correct this, make sure are nightly and release binaries are consistent, I propose this change.
I see that override is already set correctly in release workflow:
https://github.com/... | true |
2,773,558,920 | Eliminate c10::optional usage in PyTorch | houseroad | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | MEMBER | Differential Revision: D67907427
| true |
2,773,554,047 | [Pipelining] Refactor pp composability test to use faster MPCT | wconstab | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144426
* #144352
* __->__ #144345
* Using MultiProcessContinuousTest base class is faster (60s vs 279s for
the full run of `test_manual_with_data_parallel` and all its
parametrizations
* Have to move to a new file to use MPTC since it r... | true |
2,773,541,254 | custom_op's backward changes can't invalidate `torch.compile` cache for backward | YouJiacheng | open | [
"triaged",
"module: custom-operators",
"oncall: pt2",
"module: pt2-dispatcher"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
(clean cache: `rm -r /tmp/torchinductor_root/*`)
First, run the following code
```python
import torch
from torch import Tensor
@torch.library.custom_op("mylib::foo", mutates_args=())
def foo(x: Tensor) -> Tensor:
return x.clone()
@foo.register_fake
def _(x):
return tor... | true |
2,773,487,918 | [ONNX] Handle list values as 0d inputs | justinchuby | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: bug fixes"
] | 11 | COLLABORATOR | Handle list values as 0d inputs instead of 1d, as the `SymInt`s are expected to be 0d tensors in ONNX.
This PR reshapes int64 values into 1D tensors in a list, assuming they are 0D tensors initially. | true |
2,773,485,767 | [dynamo][dicts] Consolidate dict(..) construction | anijain2305 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 11 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144342
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,773,432,144 | torchgen: support exception boundary for ExecuTorch functions | swolchok | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144341
Needed for ExecuTorch diff D67904052.
Differential Revision: [D67906411](https://our.internmc.facebook.com/intern/diff/D67906411/) | true |
2,773,424,409 | c10::optional -> std::optional in a few places | r-barnes | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"topic: improvements"
] | 26 | CONTRIBUTOR | Test Plan: Sandcastle
| true |
2,773,415,953 | `logsumexp` parameter `dim` is optional according to the doc, but the code errors out if it's not provided | kit1980 | closed | [
"module: docs",
"triaged",
"actionable",
"module: python frontend"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
a = torch.randn(3, 3)
torch.logsumexp(a)
```
Should be "all dimensions are reduced" (https://pytorch.org/docs/stable/generated/torch.logsumexp.html), instead there is an error:
```
TypeError: logsumexp() received an invalid combination of arguments - got (Tenso... | true |
2,773,382,684 | [TorchInductor] Add ALiBi (Attention with Linear Biases) Fused Attention Pattern | vyom1611 | open | [
"triaged",
"open source",
"Stale",
"topic: not user facing",
"module: inductor"
] | 4 | NONE | ## Summary
This PR adds support for ALiBi (Attention with Linear Biases) in TorchInductor’s fused-attention. ALiBi applies a position-based bias to attention scores, improving extrapolation for language modeling tasks. With this addition, ALiBi-based attention can leverage PyTorch’s optimized `_scaled_dot_product_atte... | true |
2,773,376,588 | Testing new triton llvm commit | jataylo | closed | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"ciflow/rocm",
"ciflow/inductor-micro-benchmark",
"ciflow/inductor-rocm",
"ciflow/inductor-periodic"
] | 3 | COLLABORATOR | Previous triton llvm commit (https://github.com/pytorch/pytorch/pull/140698) broke A100 in resnet models, retesting CI to see if this is resolved. | true |
2,773,374,580 | Fix int8 mm V.ops.mul dispatching | pytorchbot | closed | [
"open source",
"module: inductor",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #142350
* __->__ #143127
This is sort of subtle - because we were doing `V.ops.mul` at binding time, we dont redispatch later when we invoke the epilogue. and then later running into assertion checking in pr above.
cc @voznesenskym @peng... | true |
2,773,371,675 | Fix PythonMod printing | isuruf | closed | [
"module: cpu",
"open source",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 3 | COLLABORATOR | Cherry pick #144078 and its dependency #143197
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,773,355,897 | Implement `Size.__radd__` (currently `tuple + Size` upcasts to `tuple`) | randolf-scholz | open | [
"triaged",
"actionable",
"module: python frontend"
] | 4 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
`torch.Size`, just like `tuple` which it subclasses from, does not implement an `__radd__` function. This has the consequence that `Size + tuple` returns a `Size`, whereas `tuple + Size` returns a `tuple`, since it falls back to `tuple.__add__(left, right)`:
```py
>>> imp... | true |
2,773,272,071 | [pytree][2/N] change pytree usages to implementation agnostic | XuehaiPan | open | [
"oncall: distributed",
"oncall: jit",
"open source",
"Stale",
"topic: not user facing",
"fx",
"module: dynamo",
"ciflow/inductor",
"release notes: AO frontend"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #138056
* __->__ #144333
* #144332
* #130141
* #137884
* #144405
* #137400
* #130140
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @ezyang @SherlockNoMad ... | true |
2,773,271,744 | [pytree][1/N] change pytree usages to implementation agnostic: `torch.distributed` | XuehaiPan | open | [
"oncall: distributed",
"open source",
"Stale",
"release notes: distributed (sharded)",
"module: dynamo",
"ciflow/inductor",
"release notes: distributed (checkpoint)"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144332
* #130141
* #144405
* #137400
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @ji... | true |
2,773,188,988 | [Export] UserWarning: Attempted to insert a get_attr Node with no underlying reference in the owning GraphModule | bhack | open | [
"oncall: pt2",
"oncall: export"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
Using `torch.export` on https://github.com/MCG-NJU/VFIMamba
I got
```python
/opt/conda/lib/python3.11/site-packages/torch/export/_unlift.py:75: UserWarning: Attempted to insert a get_attr Node with no underlying reference in the owning GraphModule! Call GraphModule.add_submodule to add t... | true |
2,773,174,371 | Fix batch-specific attention mod for NJT + Flex | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143866
Fixes #143788 | true |
2,773,108,317 | [BE]: Remove unnecessary copy of gradients in util | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | COLLABORATOR | No need to copy gradients to CPU too
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,773,070,647 | Debug build fails to compile on x86 with WERROR=1 | robert-hardwick | open | [
"module: build",
"triaged"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
Attempted to build a debug whl on x86 machine in ubuntu docker image 'pytorch-linux-jammy-py3.9-gcc11'
Build passes when DEBUG=0 OR with DEBUG=1 and WERROR=0
`In file included from /var/lib/jenkins/workspace/torch/csrc/jit/tensorexpr/llvm_codegen.cpp:24:
/opt/llvm/include/llvm/IR/IRBui... | true |
2,772,977,781 | [Fix]: Enable support for Arm Neon & SVE support for FP32 Gemm Wrapper | nikhil-arm | closed | [
"open source",
"module: arm",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"ciflow/linux-aarch64"
] | 12 | COLLABORATOR | **Performance Improvements**:
Linear Layer [ 1x512 * 512x512 ] -> 2x - 4x
Linear Layer [ 3x512 * 512x512 ] -> 2x - 4x
cc @malfet @snadampal @milpuz01 @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 ... | true |
2,772,858,969 | Add batch_add function and test case for simplifying tensor operations | namezz | closed | [
"open source",
"release notes: nn"
] | 3 | NONE | Fixes #ISSUE_NUMBER
| true |
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