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 |
|---|---|---|---|---|---|---|---|---|
2,983,218,493 | Introduce test skip markers for Sandcastle | Flamefire | open | [
"oncall: distributed",
"oncall: jit",
"triaged",
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Simplify the markers a bit to make them more expressive
It also makes it easier to skip those tests "manually" by changing the single definition of the skip marker.
This is important to reduce potential false positives (of failed tests) in some environments, such as HPC clusters
cc @H-Huang @awgu @wanchaol @fegin ... | true |
2,983,218,454 | DISABLED test_parity__foreach_acos_fastpath_inplace_cuda_complex128 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_acos_fastpath_inplace_cuda_complex128&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/4023781... | true |
2,983,218,447 | DISABLED test_foreach_reduce_large_input__foreach_max_w_empty_False_cuda_bfloat16 (__main__.TestForeachCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 2 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_foreach_reduce_large_input__foreach_max_w_empty_False_cuda_bfloat16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/... | true |
2,982,691,025 | Update triton wheel build, setuptools pin | atalman | closed | [
"Merged",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Observing failure in release workflow:
https://github.com/pytorch/pytorch/actions/runs/14346340202/job/40216804374
```
Traceback (most recent call last):
File "/opt/python/cp311-cp311/lib/python3.11/site-packages/wheel/bdist_wheel.py", line 11, in <module>
from setuptools.command.bdist_wheel import bdist_w... | true |
2,982,589,347 | [1/N] Use internal linkage in torch/csrc C++ files | cyyever | closed | [
"oncall: distributed",
"module: cpu",
"module: mkldnn",
"open source",
"Merged",
"NNC",
"ciflow/trunk",
"release notes: quantization",
"release notes: linalg_frontend",
"ciflow/periodic",
"module: dynamo",
"ciflow/inductor",
"ciflow/linux-aarch64"
] | 11 | COLLABORATOR | Turn more functions and variables into static if they are not used outside the cpp files. Unused functions are removed.
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @gujinghui @PenghuiCheng @jianyuh @min-jean-cho @yanbing-j @G... | true |
2,982,518,956 | Docs: Add missing whitespace in the cmake warning message | koyuki7w | closed | [
"open source",
"Merged",
"topic: not user facing"
] | 7 | CONTRIBUTOR | A trailing whitespace is needed to be concatenated to the following string correctly.
| true |
2,982,518,800 | ShardTensor gather will encounter an error when a local tensor on certain ranks has zero elements | tiankongdeguiji | open | [
"oncall: distributed",
"triaged"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
When a local tensor on certain ranks has zero elements, ShardTensor gather will raise an error. We can reproduce this using the following command: `torchrun --master_addr=localhost --master_port=49941 --nnodes=1 --nproc-per-node=8 test_shard_gather.py`
test_shard_gather.py
```python
import os
... | true |
2,982,328,511 | [CI] Enable XCCL in XPU CI build | chuanqi129 | open | [
"triaged",
"open source",
"topic: not user facing",
"keep-going",
"ciflow/xpu"
] | 10 | COLLABORATOR | As XCCL has been enabled for torch xpu, enable it in CI build. | true |
2,982,257,076 | Cannot export once a nn.Module is compiled | GdoongMathew | open | [
"oncall: pt2",
"oncall: export"
] | 6 | CONTRIBUTOR | ### 🐛 Describe the bug
Once a `nn.Module` is compiled through `module.compile()`, it fails during `torch.export.export`.
## Example
```python
class Custom(torch.nn.Module):
def __init__(self):
super().__init__()
self.module = torch.nn.Conv2d(3, 3, 3)
def forward(self, x: torch.Tensor) -> to... | true |
2,982,143,457 | Test new Windows Arm64 runner image | iremyux | closed | [
"open source",
"ciflow/binaries",
"topic: not user facing"
] | 2 | COLLABORATOR | Draft PR to see if the new Windows Arm64 runner image works as expected. | true |
2,982,101,598 | Fix StrictMinMaxConstraint issue | FlintWangacc | open | [
"open source",
"release notes: fx",
"fx"
] | 2 | NONE | Fixes #150922
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,982,100,650 | Add more check for torch.cuda.nccl | FFFrog | open | [
"oncall: distributed",
"open source",
"topic: not user facing"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151221
* __->__ #150923
Changes:
- add op check for nccl operations
- add related tests for op check | true |
2,982,099,310 | StrictMinMaxConstraint issue in pytorch 2.4.0 | FlintWangacc | open | [
"triaged",
"module: fx"
] | 0 | NONE | ### 🐛 Describe the bug
```python
class StrictMinMaxConstraint(Constraint):
"""
For clients: the size at this dimension must be within 'vr' (which
specifies a lower and upper bound, inclusive-inclusive) AND it
must be non-negative and should not be 0 or 1 (but see NB below).
For backends: there mu... | true |
2,982,054,195 | `M(*[torch.from_numpy(v).to('cpu') for v in inp])` hang when start with `multiprocessing.Process` | syheliel | open | [
"needs reproduction",
"module: multiprocessing",
"triaged"
] | 3 | NONE | ### 🐛 Describe the bug
when run under `mp.Process(target=run_model)`, the program will hang until timeout:
```
import numpy as np
import torch
import multiprocessing as mp
import hanging_threads # for debugging long time hang thread info
class M(torch.nn.Module):
def __init__(self):
super().__init__()
... | true |
2,982,050,287 | Assertion Failure: TestMathBitsCPU conj_view tests | rahultrada | closed | [
"module: tests",
"module: complex",
"module: correctness (silent)",
"module: arm"
] | 1 | NONE | ### 🐛 Describe the bug
Under test class `TestMathBitsCPU`, the following four tests
```
test_conj_view__refs_dot_cpu_complex64
test_conj_view__refs_vdot_cpu_complex64
test_neg_conj_view__refs_dot_cpu_complex128
test_neg_conj_view__refs_vdot_cpu_complex128
```
are failing with a similar error on `aarch64`
```
Asser... | true |
2,982,042,450 | Assertion Failure: TestCommonCPU complex64 tests | rahultrada | closed | [
"module: tests",
"module: arm"
] | 1 | NONE | ### 🐛 Describe the bug
Under test class `TestCommonCPU`, the following four tests
```
test_python_ref__refs_linalg_vecdot_cpu_complex64
test_python_ref_torch_fallback__refs_dot_cpu_complex64
test_python_ref_torch_fallback__refs_linalg_vecdot_cpu_complex64
test_python_ref_torch_fallback__refs_vdot_cpu_complex64
```
... | true |
2,982,031,937 | Assertion Failure: TestCommonCPU complex128 tests | rahultrada | open | [
"module: tests",
"triaged",
"module: complex",
"module: third_party",
"module: correctness (silent)",
"module: arm"
] | 4 | NONE | ### 🐛 Describe the bug
Under test class `TestCommonCPU`, the following four tests
```
test_python_ref__refs_linalg_vecdot_cpu_complex128
test_python_ref_torch_fallback__refs_dot_cpu_complex128
test_python_ref_torch_fallback__refs_linalg_vecdot_cpu_complex128
test_python_ref_torch_fallback__refs_vdot_cpu_complex128
`... | true |
2,982,014,122 | Document garbage_collection_threshold default | neoncube2 | open | [
"module: docs",
"module: cuda",
"triaged"
] | 1 | NONE | ### 📚 The doc issue
It'd be nice if https://pytorch.org/docs/stable/notes/cuda.html#memory-management documented the default for `garbage_collection_threshold`
### Suggest a potential alternative/fix
I _think_ the default is `1.0`
cc @svekars @sekyondaMeta @AlannaBurke @ptrblck @msaroufim @eqy | true |
2,981,985,194 | Elastic training crashes on killed agent | andreacarrara-polimi | open | [
"oncall: distributed",
"triaged"
] | 7 | NONE | ### 🐛 Describe the bug
I'm trying to use Elastic to handle nodes joining or leaving during training. My setup runs two EC2 instances (Ubuntu 24.04, g4dn.xlarge, NVIDIA Tesla T4, driver 550, PyTorch in a venv). My script is minimal, reproducible and attached [here](https://gist.github.com/andreacarrara-polimi/9ee27197... | true |
2,981,923,995 | `module.compile()` behaves differently from `torch.compile(module)` | GdoongMathew | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
`module.compile(backend=custom_backend)`'s forward method returns a different result from `torch.compile(module)`, especially when using `Conv2d`.
## Example
```python
def print_fx_graph(graph: torch.fx.GraphModule, example_inputs: list[torch.Tensor]):
print("Current graph:")
graph.g... | true |
2,981,910,226 | fix shard tensor gather when a local tensor on certain ranks has zero elements | tiankongdeguiji | closed | [
"oncall: distributed",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (sharded)"
] | 9 | CONTRIBUTOR | cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,981,906,172 | [Docs] Clarify behavior when integer dtype is used with requires_grad=True in `tensor.to()` | shink | closed | [
"open source",
"Merged",
"release notes: python_frontend",
"topic: docs"
] | 5 | CONTRIBUTOR | Fixes #150618
Related comment: https://github.com/pytorch/pytorch/issues/3226#issuecomment-489362234
| true |
2,981,904,285 | using torch.compile with torchao at the same time cause stack overflow error | zhangvia | open | [
"needs reproduction",
"triaged",
"oncall: pt2",
"module: dynamo"
] | 2 | NONE | ### 🐛 Describe the bug
when use torch.compile and torchao at the same time, there will be a stack overflow error. related issue [1775](https://github.com/pytorch/ao/issues/1775)
This issue appears to be related to a specific Python version and CUDA driver version.
error happens in:
python:3.10.0
torch:2.6.0+cu124
t... | true |
2,981,764,194 | [dynamo][invoke_subgraph] Use FxGraphModule comparison instead of hashing | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150717
* #151256
* __->__ #150911
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,981,745,425 | [DO NOT MERGE] Throwaway changes | mlazos | closed | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150910
* #152390
* #150909
* #150907
* #151406
* #150906
more throwaway | true |
2,981,745,262 | [Inductor] Fix cuda_template.py typing | mlazos | closed | [
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150910
* #152390
* __->__ #150909
* #150907
* #151406
* #150906
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauha... | true |
2,981,744,853 | [Inductor] Fix cuda_kernel typing | mlazos | closed | [
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150910
* #152390
* #150909
* __->__ #150908
* #150907
* #151406
* #150906
* #151713
* #151405
* #150905
* #152306
* #152305
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayi... | true |
2,981,744,709 | [Cutlass] Changes to gemm template for EVT | mlazos | open | [
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152815
* __->__ #150907
* #151406
* #150906
* #152733
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhun... | true |
2,981,744,562 | [Cutlass] Integrate EVT into CUDACPPScheduling | mlazos | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"ci-no-td"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152815
* #150907
* #151406
* __->__ #150906
* #152733
Previously merged:
* #151713
* #151405
* #150905
* #152306
* #152305
Allow epilogue nodes in cuda combined scheduling
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobin... | true |
2,981,744,441 | [Cutlass] Implement cutlass epilogue visitor python codegen | mlazos | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 9 | CONTRIBUTOR | This PR implements the second codegen task of CUTLASS EVT: translating inductor epilogue nodes into python code that will be traced by the EVT infra.
Details:
The implementation uses a simple ops wrapper which only supports add and mul pointwise ops today (to be extended in the future). This ops wrapper generates ... | true |
2,981,744,335 | [Cutlass] Implement EVT example tensor creation | mlazos | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"ci-no-td"
] | 9 | CONTRIBUTOR | This PR implements a translation layer from inductor IR to "example tensors" the expected arguments of the EVT tracer. These tensors basically store the name, shape, stride, and dtype of the tensor and allow an ast-based python parse to generate the EVT C++.
Stack from [ghstack](https://github.com/ezyang/ghstack) (o... | true |
2,981,744,221 | [Cutlass] Implement Epilogue Argument emitter | mlazos | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 20 | CONTRIBUTOR | This implements epilogue visitor tree argument generation (example type [here](https://github.com/NVIDIA/cutlass/blob/3fe62887d8dd75700fdaf57f9c181878701b0802/include/cutlass/epilogue/fusion/sm90_callbacks_tma_warpspecialized.hpp#L332)).
Details:
The codegen task here is to implement a function which can generate a... | true |
2,981,724,861 | DISABLED test_parity__foreach_acos_fastpath_inplace_cuda_bfloat16 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_acos_fastpath_inplace_cuda_bfloat16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40221902832).
Ov... | true |
2,981,649,287 | [llvm] strong_type.h: error: is_arithmetic cannot be specialized: Users are not allowed to specialize this standard library entity | atupone | open | [
"needs reproduction",
"module: build",
"triaged"
] | 1 | CONTRIBUTOR | I got a report (https://bugs.gentoo.org/953366) that clang++ is complaining about is_arithmetic usage here.
I'm not able to reproduce
cc @malfet @seemethere | true |
2,981,480,620 | Windows Preview (Nightly) does not support Nvidia 5090D | monkeycc | closed | [] | 4 | NONE | Windows 11
cuda 12.8
cudnn 9.8
`pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
`
```
torch 2.8.0.dev20250407+cu128
torchaudio 2.6.0.dev20250408+cu128
torchvision 0.22.0.dev20250408+cu128
```
```
Package Version
-------... | true |
2,981,467,342 | [torch.compile] handle a custom __delattr__ method correctly | SandishKumarHN | open | [
"module: dynamo",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Fixes #150765
- handle a custom __delattr__ method correctly
Test:
```
import torch
class MyObject:
def __init__(self, val):
self.val = val
# Flag to track deletion attempts instead of using print
self.deletion_attempted = False
def __delattr__(self, attr):
... | true |
2,981,418,143 | [device_mesh] replace dim_group_info with group_name | wanchaol | open | [
"oncall: distributed",
"open source",
"topic: not user facing"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150897
* __->__ #150898
* #150896
as titled, there's no need to maintain a dim_group_info anymore, we can
simply maintain a list of group_name instead. This will simplify the
logic
cc @H-Huang @awgu @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,981,418,058 | [device_mesh] improve device selection logic | wanchaol | open | [
"oncall: distributed",
"module: cpu",
"open source",
"ciflow/trunk",
"release notes: distributed (dtensor)"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150897
* #150898
* #150896
as titled, this PR improves the device selection logic when user did not
set the device before calling the DeviceMesh constructor, as a device
manager, DeviceMesh should try to set the device for use... | true |
2,981,417,968 | Fix DTensorTestBase to barrier with device ids | wanchaol | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150897
* #150898
* __->__ #150896
try to get rid of the below annoying warnings when running the unit tests
cc @H-Huang @awgu @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,981,296,976 | Revert "[ATen][CUDA] Implement 128 bit vectorization v2 (#145746)" | malfet | closed | [
"ciflow/periodic",
"ci-no-td"
] | 2 | CONTRIBUTOR | This reverts commit e84bf88dde509d44175a0a1c00cec13c9926843e.
Fixes #ISSUE_NUMBER
| true |
2,981,254,784 | [aotinductor] fix std::{min.max} compilation error for sympy expr with multiple args | ColinPeppler | closed | [
"module: cpu",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 20 | CONTRIBUTOR | ### Compilation error
The issue is that u0 (an unbacked symint) can come from a smaller int dtype e.g. int16, int32.
```
error: no matching function for call to ‘min(int64_t&, short int&)’
759 | call_add_kernel_with_scaling_0(... std::min(100L, s97, u0) ...);
```
### Diff
The fix is to explicitly specify... | true |
2,981,207,048 | Hipify global scrach defintion in AOTI codegen | zoranzhao | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | MEMBER | Summary: as title, a refactor is very needed I think .... or at least unify internal/external AOTI wrapper hipification method
Test Plan: P1780296121
Differential Revision: D72683568
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @che... | true |
2,981,191,407 | Fix inplacing with multiple, fused uses | pytorchbot | closed | [
"open source",
"module: inductor",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150845
We had `can_inplace` defined on a single use. When that buffer has multiple uses inside a fused node, we need to check if the other accesses have the same index. Otherwise we may read memory that has already been written to f... | true |
2,981,189,896 | [ONNX] How to export Llama4 | srijanie03 | open | [
"module: onnx",
"triaged"
] | 19 | NONE | ### 🐛 Describe the bug
I am trying to do an onnx export for the Llama 4 Scout model but it fails saying:
`RuntimeError: Only tuples, lists and Variables are supported as JIT inputs/outputs. Dictionaries and strings are also accepted, but their usage is not recommended. Here, received an input of unsupported type: Dyn... | true |
2,981,184,960 | [AO] fix per token block size calculation | mcr229 | closed | [
"Merged",
"ciflow/trunk",
"release notes: quantization",
"release notes: AO frontend"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150890
| true |
2,981,184,669 | 2.7 RC: fails to install the needed `optree` dependency | stas00 | closed | [
"high priority",
"triage review",
"module: regression",
"has workaround",
"oncall: pt2"
] | 13 | CONTRIBUTOR | The same issue occurs in nightly and 2.7-RC
```
pip3 install torch --index-url https://download.pytorch.org/whl/test/cu128 -U
```
then when trying to use torch:
```
File "/code/users/stas/github/DeepSpeed/deepspeed/runtime/compiler.py", line 25, in disable
return torch.compiler.disable(func)
File "/home/yak/... | true |
2,981,175,085 | [inductor] Change minimum number of SMs to 60 to let Ada use Triton GEMM backend | henrylhtsang | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 15 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148622
* __->__ #150888
context: https://github.com/pytorch/pytorch/issues/150390#issuecomment-2790272814
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy ... | true |
2,981,172,089 | add logs for debugging chunk metadata | wconstab | closed | [
"oncall: distributed",
"release notes: distributed (checkpoint)"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150887
* #150862
* #150650
* #150490
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @d4l3k | true |
2,981,166,871 | not-for-landing add logs for debugging chunk metadata | teja-rao | open | [
"oncall: distributed",
"release notes: distributed (checkpoint)"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,981,149,305 | Add basic functionality for installing params/bufs when specified | Lucaskabela | closed | [
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150978
* __->__ #150885
* #151022
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,981,143,911 | [Codemod][AddExplicitStrictExportForTrainingInferenceArg] caffe2/test/export | gmagogsfm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Differential Revision: D72667175
| true |
2,981,107,079 | `torch.autograd.backward` fails with single scalar `Tensor` as `inputs` | ValerianRey | closed | [
"high priority",
"module: autograd",
"triaged",
"actionable"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
When manually specifying the `inputs` parameter of `torch.autograd.backward` to be a single **scalar** tensor, a `TypeError` is wrongly raised.
The following code works without any problem:
```python
import torch
x = torch.tensor([5.0, 6.0], requires_grad=True)
y = (x * 2).sum()
torch.autogra... | true |
2,981,104,947 | [c10d][fr] Enable FR analysis script for all coalesce op | fduwjj | closed | [
"oncall: distributed",
"ciflow/trunk",
"release notes: distributed (c10d)",
"topic: not user facing",
"suppress-api-compatibility-check",
"suppress-bc-linter"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150882
This PR is to enable FR for all coalesce ops. (batch p2p is enabled in the current script, so we will mainly focus on non-P2P ops)
For non-P2P coalesced ops, there are are several ways to call it (due to legendary reasons)... | true |
2,981,104,794 | [c10d][fr] Refactor analysis script for modularization and reusing for coalesce collectives | fduwjj | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150882
* __->__ #150881
Trying to make the code of FR analysis more reusable and modularized. So we split core error analysis logic into separate functions.
This PR mostly is shuffle around the code a bit.
Differential Revision: [D7269... | true |
2,981,067,897 | Document non-pytorch CUDA memory allocation and how to query it | wconstab | closed | [
"Merged",
"ciflow/trunk",
"release notes: cuda"
] | 6 | CONTRIBUTOR | This PR documents the fact that PyTorch does not have visibility into how every CUDA memory allocation happend - it only knows about allocations that went through the pytorch CUDA allocator.
It also adds a code snippet showing how to use pynvml to query current GPU memory usage.
## Preview
Added a note at the ... | true |
2,981,031,828 | strict multidimensional slicing | avikchaudhuri | closed | [
"fb-exported",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150879
WIP
Differential Revision: [D72673207](https://our.internmc.facebook.com/intern/diff/D72673207/)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyan... | true |
2,981,014,386 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_uint8 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 7 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_abs_fastpath_outplace_cuda_uint8&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40194907361).
Over ... | true |
2,981,013,877 | DISABLED test_multiple_module (__main__.TestInvokeSubgraphExportStrict) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher"
] | 4 | NONE | Platforms: dynamo
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_multiple_module&suite=TestInvokeSubgraphExportStrict&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40188284672).
Over the past 3 hours,... | true |
2,980,984,221 | [export] Refine draft-export CVE with Dim.AUTO | angelayi | closed | [
"Merged",
"ciflow/trunk",
"release notes: export"
] | 3 | CONTRIBUTOR | Instead of using refine_dynamic_shapes_from_suggested_fixes to fix ConstraintViolationErrors in draft-export, we can just convert the dims to Dim.AUTO, which is less error prone | true |
2,980,917,451 | Do not cover up `__dunder`__ method type-hints from `.pyi` file | alanhdu | open | [
"oncall: distributed",
"module: typing",
"triaged",
"open source",
"topic: not user facing",
"release notes: torch.func",
"ciflow/inductor"
] | 11 | CONTRIBUTOR | In the build system, we generate a `torch/_C/__init__.pyi` that contains typehints of the base `TensorBase` that `torch.Tensor` inherits from. That contains a bunch of type-annotations for annotating these dunder methods.
Unfortunately, by defining them here, these are being automatically overwritten and "hidden", ... | true |
2,980,917,250 | Fix aten.div type promotion for FakeTensor | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: export"
] | 7 | CONTRIBUTOR | Summary:
When we divide a FakeTensor by an integer using the fast op implementation, the type promotion should be `ELEMENTWISE_TYPE_PROMOTION_KIND.INT_TO_FLOAT` so we get a float when dividing an int FakeTensor by an integer.
```
FAST = get_fast_op_impls()
fast_div = FAST[torch.ops.aten.div.Tensor]
fast_div(fake_tenso... | true |
2,980,871,008 | Add Created On | Last Updated On to the docs | svekars | open | [
"module: build",
"module: docs",
"triaged"
] | 2 | CONTRIBUTOR | ### 📚 The doc issue
The "Created On | Last Updated" dates provide immediate context about documentation age and maintenance status, helping users assess content reliability.
Benefits
--------
* **Content freshness indicator**: Users can quickly determine if documentation is current or outdated
* **Maintenance t... | true |
2,980,815,251 | [Inductor][NCU] Add kernel name filtering, and allow custom metrics | yf225 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150872
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,980,741,548 | register_replacement should also respect arg_kwarg_vals | zou3519 | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 0 | CONTRIBUTOR | Followup to the stack over at https://github.com/pytorch/pytorch/pull/150511. Assigning myself so I don't forget. It will happen soon
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @aakhund... | true |
2,980,730,515 | Fix torchscript issues with reference quantized modules | Ivan-Dimitrov | closed | [
"oncall: jit",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: AO frontend"
] | 15 | CONTRIBUTOR | Summary:
The reference quantized modules for linear / conv / etc fail to torchscript due to two issues
(1) The type of torch.qscheme doesn't script
(2) The "_DTYPE_TO_QVALUE_BOUNDS" values were resolving to union[float, int] instead of just int. We fix that with a hard cast.
See: <internal post> + comments for... | true |
2,980,672,676 | Move prologue_supported_inputs computations to def_kernal | laithsakka | open | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150869
* #151778
* #151773
* #151764
This avoid replaying load_input on a cache hit on the generate_code_cache.
Effect on the current benchmark on a local run on dev server.
18549985383 -> 15072230073
25697270062 -> 207386... | true |
2,980,672,162 | DISABLED test_cache_load_function_device_cuda_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True (__main__.TestFxGraphCache) | pytorch-bot[bot] | open | [
"module: rocm",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | Platforms: rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_cache_load_function_device_cuda_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True&suite=TestFxGraphCache&limit=100) and the most recent trunk [workflow ... | true |
2,980,658,621 | Expand allowed_getattr_types_for_subgm to torch.Tensor | SherlockNoMad | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 5 | CONTRIBUTOR | Summary:
att
regular weight has the type of torch.nn.parameter.Parameter
buffer and tensor constant has the type of torch.Tensor
both types are valid.
Test Plan: CI
Differential Revision: D72657275
| true |
2,980,654,925 | add test for import cutlass | henrylhtsang | closed | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150866
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,980,650,824 | Add dynamic version for mm_loop benchmark | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150869
* #149267
* __->__ #150865
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,980,650,463 | [dynamo] `torch.compile` graph breaks on `setattr` of type objects | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Observed in https://github.com/pytorch/pytorch/issues/150848#issuecomment-2787279312
Minimal repro:
```python
import torch
class Foo():
pass
@torch.compile(backend="eager", fullgraph=True)
def f(x):
Foo.bar = 42
return x + 1
f(torch.ones(2))
```
### Error logs
```verbatim
Trac... | true |
2,980,636,743 | [ez][c10d] Disable start event recording for coalesced col and improve profile title | fduwjj | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150863
While looking at enabling FR analysis for coalesced collectives, I found that for the slow-path coalescing (cols which are not all-gather, all-reduce or reduce-scatter), we still record start event for them. This is wrong a... | true |
2,980,620,931 | [DTensor] Fix empty shard global-offset calculation | wconstab | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150862
`compute_local_shape_and_global_offset` util computes the local shape of
a particular shard of a DTensor, and the global offset (which describes
how the shard fits into the global tensor).
When the tensor dim does not evenly ... | true |
2,980,613,704 | Allow non-Tensor subclass in `torch.Tensor._make_wrapper_subclass` | ZhiyuanChen | open | [
"triaged",
"tensor subclass"
] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
I have a NestedTensor class like this:
```python
from collections.abc import Mapping, Sequence
from typing import Any, Iterable, SupportsFloat, Tuple
import torch
from torch import Tensor
from ..utils import method_cache
from .functions import NestedTensorFuncRegistry, Nest... | true |
2,980,588,621 | Fill config2launcher with correct launchers during cache hit coordinate descent | jamesjwu | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150860
This bug was crazy hard to reproduce, so I can't seem to get a unit test written that isn't the internal one I used for debugging.
Here's a short TLDR of the bug:
- Due to D71983456(OSS: https://github.com/pytorch/pyt... | true |
2,980,573,902 | RMS norm causes NaNs when used with torch.compile + float8 with rowwise scales | danielvegamyhre | open | [
"high priority",
"triaged",
"has workaround",
"module: correctness (silent)",
"months",
"module: norms and normalization",
"bug",
"oncall: pt2",
"module: inductor",
"module: float8"
] | 33 | CONTRIBUTOR | ### 🐛 Describe the bug
This PR (https://github.com/pytorch/pytorch/pull/147203) causes NaNs in torchtitan training when RMS norm is used with torch.compile and float8 training with rowwise scalese.
- Sometime between 2.6.0 and present, a change in pytorch core was introduced that caused loss to not go down and then ... | true |
2,980,471,381 | Add basic unit test and noop config | Lucaskabela | closed | [
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150978
* #150885
* __->__ #150858
### Tests
```
python test/dynamo/test_install_params_as_graph_attr.py
```
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @che... | true |
2,980,440,089 | No way to save/load model weights between PyTorch and LibTorch (C++) in a compatible way | FuryBaM | open | [
"module: cpp",
"module: serialization",
"triaged",
"enhancement"
] | 2 | NONE | ### 🚀 The feature, motivation and pitch
LibTorch (C++) does not provide a way to save or load model weights in a way compatible with Python’s torch.save() / torch.load() or state_dict() / load_state_dict(). This makes it hard to share models between Python and C++ environments.
### Alternatives
I've managed to impl... | true |
2,980,431,315 | [logging] Separate cuda synchronize overhead in autotuning | masnesral | closed | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Summary: In order to more accurately debug the overhead of autotuning (and pad_mm), explicity do a cuda.synchronize before benchmarking and time that.
Test Plan: See internal run here: https://fburl.com/f365xfcj
Zooming on on relevant examples from the perfetto:
<img width="1076" alt="Screenshot 2025-04-08 at 9 ... | true |
2,980,414,143 | Revert "[CUDA] Only use vec128 if CUDA version is newer than 12.8" | atalman | closed | [
"ci-no-td"
] | 1 | CONTRIBUTOR | Reverts pytorch/pytorch#150818
Reverting since reverted on trunk | true |
2,980,383,313 | [pytorch] add header docs for TORCH_LIBRARY_THREAD_UNSAFE_LAZY_INIT | rmaz | closed | [
"oncall: jit",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: mobile"
] | 7 | CONTRIBUTOR | Summary: Add header docs for the experimental TORCH_LIBRARY_THREAD_UNSAFE_LAZY_INIT feature, and guard behind C10_MOBILE.
Reviewed By: albanD
Differential Revision: D72572345
cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel | true |
2,980,223,011 | Inconsistent value from `torch.sum` | LogicFan | closed | [
"module: rocm",
"triaged"
] | 10 | NONE | ### 🐛 Describe the bug
Applying `torch.sum` to the same vector results a different value.
```
j = torch.load('./j0.pt')
for _ in range(1000):
print(torch.sum(j))
```
in rare chance, it will produce very wrong value.
[j0.zip... | true |
2,980,215,463 | NCCL init hits CUDA failure 'invalid argument' on 12.2 driver | kwen2501 | open | [
"oncall: distributed",
"triaged",
"module: nccl",
"has workaround"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
Error seen with nightly build, e.g. torch==2.8.0.dev20250327+cu126
```
[2025-04-08 08:39:46] devgpu263:589012:591652 [0] transport/nvls.cc:254 NCCL WARN Cuda failure 1 'invalid argument'
devgpu263:589012:591652 [0] NCCL INFO transport/nvls.cc:409 -> 1
devgpu263:589012:591652 [0] NCCL INFO init.... | true |
2,980,210,594 | Cannot export torch.sym_max(x.shape[0], y.shape[0]) | xadupre | closed | [
"oncall: pt2",
"module: dynamic shapes",
"oncall: export"
] | 8 | COLLABORATOR | ### 🐛 Describe the bug
Nothing I tried for this example works.
```python
import torch
class Model(torch.nn.Module):
def forward(self, x, y):
s1 = max(x.shape[0], y.shape[0])
s2 = max(x.shape[1], y.shape[1])
z = torch.zeros((s1, s2), dtype=x.dtype)
z[:x.shape[0], :x.shape[1]] = x... | true |
2,980,115,696 | [BE] Add FrozenOrderedSet | eellison | closed | [
"good first issue",
"triaged",
"better-engineering",
"oncall: pt2"
] | 6 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Subclass torch/utils/_ordered_set.py and error on update. We might use this in some places in the compiler/pytorch.
cc @chauhang @penguinwu @Skylion007 who made some changes here
### Alternatives
_No response_
### Additional context
_No response_ | true |
2,980,069,764 | logging start of torch elastic workers. | aschhabra | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (torchelastic)"
] | 11 | CONTRIBUTOR | Summary:
We would like to log start of the workers. It will help with complete logging.
Test Plan:
unit tests
https://www.internalfb.com/intern/testinfra/testrun/6473924724652056
e2e tests
https://www.internalfb.com/mlhub/pipelines/runs/mast/f712311762-27449483648-TrainingApplication_V403K?job_attempt=0... | true |
2,980,016,941 | torch.compile cannot handle plain nn.Parameter subclasses | zou3519 | closed | [
"triaged",
"module: regression",
"tensor subclass",
"oncall: pt2",
"module: dynamo",
"vllm-compile",
"dynamo-triage-jan2025"
] | 12 | CONTRIBUTOR | Context: vLLM has a lot of plain nn.Paramater subclasses (e.g. no torch_function, no torch_dispatch). Dynamo doesn't have a good time with them:
Repro:
```
import torch
from torch.nn import Parameter
from typing import Callable
class BasevLLMParameter(Parameter):
"""
Base parameter for vLLM linear layers. Ext... | true |
2,979,952,101 | [Build] Fix fbgemm build with gcc-12+ | malfet | closed | [
"Merged",
"release notes: build",
"topic: bug fixes"
] | 3 | CONTRIBUTOR | By suppressing more warnings
TODO: fbgemm pin really needs to get updated
| true |
2,979,844,106 | PyTorch can not be build by gcc-12 | malfet | closed | [
"module: build",
"triaged",
"module: third_party"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
CI
### Versions
Attempt to run `python setup.py develop` results in
```
In file included from /usr/lib/gcc/x86_64-linux-gnu/12/include/immintrin.h:43:
/usr/lib/gcc/x86_64-linux-gnu/12/include/avxintrin.h: In function ‘void fbgemm::FloatToBfloat16_avx512(const float*, bfloat16*, size_t)’:
/usr... | true |
2,979,725,031 | Fix inplacing with multiple, fused uses | eellison | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150845
We had `can_inplace` defined on a single use. When that buffer has multiple uses inside a fused node, we need to check if the other accesses have the same index. Otherwise we may read memory that has already been written to f... | true |
2,979,528,308 | [NVIDIA] Thor | johnnynunez | closed | [
"triaged",
"open source"
] | 8 | CONTRIBUTOR | Thor are based on SBSA
@malfet @atalman | true |
2,979,438,761 | [AOTInductor] Can't compile with a relative cache path for bert | ChuanqiXu9 | open | [
"oncall: pt2",
"oncall: export",
"module: aotinductor"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Reproducer:
```
import os
import torch
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
self.fc1 = torch.nn.Linear(10, 16)
self.relu = torch.nn.ReLU()
self.fc2 = torch.nn.Linear(16, 1)
self.sigmoid = torch.nn.Sigmoid()
def f... | true |
2,979,424,599 | Exporting BertModel failed with marking batch as dynamic | ChuanqiXu9 | closed | [
"oncall: pt2",
"module: dynamic shapes",
"oncall: export"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Reproducer:
```
import torch
import json
from transformers import BertModel, BertConfig
import os
CONFIG = """
{
"architectures": [
"BertForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"h... | true |
2,979,388,641 | Fix the Problems About Defining Static Variable in Inline Function | pytorchbot | open | [
"oncall: distributed",
"oncall: jit",
"open source",
"release notes: cpp"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147095
Refer to https://github.com/pytorch/pytorch/issues/125465 for more informations
- Remove unused header files
- Move the inline function that defines the static variable to .cc
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz33... | true |
2,979,278,506 | gui-uv doesn't work with rocm | Krytern | closed | [
"module: rocm"
] | 0 | NONE | EDIT: WRONG PROJECT! | true |
2,979,228,514 | Code Clean: Using the new builtin function provides by python 3.8 later | FFFrog | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)",
"fx"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150839
Changes:
- reversed
- math.perm
- inspect.getfile
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,979,228,204 | Code Clean: Remove specific bytecode support in dynamo for python3.8 | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 11 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150839
* __->__ #150838
* #150834
Related Bytecode:
- CALL_FINALLy
- END_FINALLy
- POP_FINALLy
The bytecodes above were removed before python3.9, refer to [this](https://github.com/python/cpython/blob/53908bd7905b849e110d2c6f4bce739bff0371... | true |
2,979,216,663 | DISABLED test_parity__foreach_abs_fastpath_outplace_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_parity__foreach_abs_fastpath_outplace_cuda_int8&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40151959719).
... | true |
2,979,097,872 | `Aborted (core dumped)` in `torch.cuda.nccl.reduce` | vwrewsge | open | [
"oncall: distributed",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
When using `torch.cuda.nccl.reduce` with invalid operation codes, the program crashes with `Aborted (core dumped)` instead of raising a `RuntimeError` or validating the input.
# To Reproduce
```
import torch
import torch.cuda as cuda
from torch.cuda.nccl import reduce
def test_bug():
# Che... | true |
2,979,082,232 | `Floating point exception` in `torch.nn.functional.ctc_loss` | vwrewsge | closed | [
"module: nn",
"module: cuda",
"triaged",
"module: edge cases"
] | 1 | NONE | ### 🐛 Describe the bug
When calling `ctc_loss` with empty tensors on CUDA (device="cuda"), a `Floating point exception` occurs. This does not happen on CPU, where a proper error is raised.
# To reproduce
```
import torch
import torch.nn.functional as F
device = "cuda" # "cpu" is fine
num_classes = 4
log_probs = to... | true |
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