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 |
|---|---|---|---|---|---|---|---|---|
2,974,435,833 | Training/Fine-tuning fails with PyTorch 2.8 + 4x 5090 GPUs using DDP/FSDP/DeepSpeed | felixliufei | open | [
"oncall: distributed",
"triaged",
"module: ddp",
"module: fsdp"
] | 6 | NONE | ### 🐛 Describe the bug
Hi everyone,
I seem to have hit a roadblock and could use some help or clarification.
Environment:
* PyTorch Version: 2.8 (Is this correct? Please confirm the exact version)
* GPUs: 4 x NVIDIA 5090
* Parallelism Strategy Tried: DistributedDataParallel (DDP), FullyShardedDataParallel (FSDP), Dee... | true |
2,974,211,661 | GeForce RTX 5090 D with CUDA capability sm_120 is not compatible with the current PyTorch installation. | monkeycc | closed | [
"module: binaries",
"module: cuda",
"triaged"
] | 3 | NONE | ### 🐛 Describe the bug
```
import torch
# Check if CUDA is recognized by PyTorch
print("Is CUDA available:", torch.cuda.is_available())
# Output the number of GPU devices and their names (if available)
if torch.cuda.is_available():
print("Number of GPU devices:", torch.cuda.device_count())
print("Current GP... | true |
2,974,003,987 | [BE][CI][Easy] Run `lintrunner` on generated `.pyi` stub files | XuehaiPan | open | [
"module: typing",
"module: ci",
"module: lint",
"open source",
"better-engineering",
"ciflow/trunk",
"topic: not user facing"
] | 10 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150732
* #150731
* #150730
* #150626
* #150729
* #150728
* #150727
* #150726
cc @ezyang @malfet @xuzhao9 @gramster @seemethere @pytorch/pytorch-dev-infra | true |
2,974,003,923 | [BE] Resolve lint errors in `.pyi` stub files | XuehaiPan | open | [
"module: typing",
"module: lint",
"open source",
"better-engineering",
"topic: not user facing"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150732
* __->__ #150731
* #150730
* #150626
* #150729
* #150728
* #150727
* #150726
cc @ezyang @malfet @xuzhao9 @gramster | true |
2,974,003,881 | [BE] Ensure generated stub files by `gen_pyi` are properly formatted | XuehaiPan | open | [
"open source",
"better-engineering",
"topic: not user facing"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150732
* #150731
* __->__ #150730
* #150626
* #150729
* #150728
* #150727
* #150726
| true |
2,974,003,819 | [BE] Add `__all__` to `torch/nn/functional.pyi` and `torch/return_types.pyi` | XuehaiPan | open | [
"module: nn",
"open source",
"better-engineering",
"module: codegen",
"topic: not user facing"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150732
* #150731
* #150730
* #150626
* __->__ #150729
* #150728
* #150727
* #150726
cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki @ezyang @bhosmer @bdhirsh @kadeng | true |
2,974,003,788 | [BE] Update `.pyi` stub template to use Generic TypeAlias (PEP 585) and Union Type (PEP 604) | XuehaiPan | open | [
"module: typing",
"open source",
"better-engineering",
"module: codegen",
"topic: not user facing"
] | 4 | COLLABORATOR | https://github.com/pytorch/pytorch/pull/129001#discussion_r1645126801 is the motivation for the whole stack of PRs. In `torch/__init__.py`, `torch._C.Type` shadows `from typing import Type`, and there is no type stub for `torch._C.Type` in `torch/_C/__init__.pyi`. So we need to use `from typing import Type as _Type`. A... | true |
2,974,003,729 | [torchgen] Refactor and simplify `gen_pyi.py` to use Generic TypeAlias (PEP 585) and Union Type (PEP 604) | XuehaiPan | open | [
"module: typing",
"open source",
"better-engineering",
"module: codegen",
"topic: not user facing",
"ciflow/inductor"
] | 5 | COLLABORATOR | https://github.com/pytorch/pytorch/pull/129001#discussion_r1645126801 is the motivation for the whole stack of PRs. In `torch/__init__.py`, `torch._C.Type` shadows `from typing import Type`, and there is no type stub for `torch._C.Type` in `torch/_C/__init__.pyi`. So we need to use `from typing import Type as _Type`. A... | true |
2,974,003,676 | [torchgen] Refactor `torchgen.utils.FileManager` to accept `pathlib.Path` | XuehaiPan | open | [
"open source",
"better-engineering",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"suppress-bc-linter",
"ci-no-td"
] | 13 | COLLABORATOR | This PR allows `FileManager` to accept `pathlib.Path` as arguments while keeping the original `str` path support.
This allows us to simplify the code such as:
1. `os.path.join(..., ...)` with `Path.__floordiv__(..., ...)`.
https://github.com/pytorch/pytorch/blob/95a5958db490608cacca75b89d9a1d2e955b60e8/torchge... | true |
2,973,962,635 | Continuous calls to nn.Linear in fp32 on the 5090D cause severe performance degradation | mobulan | open | [
"module: performance",
"module: nn",
"module: cuda",
"triaged",
"Blackwell"
] | 34 | NONE | ### 🐛 Describe the bug
Continuously calling nn.Linear in fp32 on 5090D causes severe performance degradation. I don't know if it will occur on other 50 series cards.
```python
import torch
from torch import nn
import time
import torch.nn.functional as F
linear = nn.Linear(768,768).cuda()
x = torch.randn(256, 196,... | true |
2,973,828,817 | PyTorch fails to import due to incompatible glibc version (requires GLIBC_2.27) | wangleiofficial | closed | [
"needs reproduction",
"module: binaries"
] | 1 | NONE | 🐛 Bug Report
When importing torch, an ImportError is raised due to an unmet GLIBC version requirement. The current system has glibc version 2.17, but libcurand.so.10 (used by PyTorch) requires GLIBC_2.27.
📄 Error Message
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/wangl... | true |
2,973,639,324 | Add check in `test_cow_input` to ensure COW data is never changed | kurtamohler | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150723
| true |
2,973,606,938 | [executorch hash update] update the pinned executorch hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 27 | COLLABORATOR | This PR is auto-generated nightly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/nightly.yml).
Update the pinned executorch hash. | true |
2,973,538,906 | Avoid overwriting COW data in MPS code | kurtamohler | open | [
"open source",
"release notes: mps",
"ciflow/mps",
"keep-going"
] | 2 | COLLABORATOR | Fixes MPS ops that were breaking COW behavior by overwriting data without first materializing. Along with necessary materializations, this also introduces many unnecessary materializations, but the MPS-CPU lazy cloning feature should now be safe to use.
Also introduces APIs in the MPS code which will be used in prev... | true |
2,973,530,060 | [wip] support tracing async collectives | xmfan | open | [
"oncall: distributed",
"release notes: distributed (c10d)",
"module: dynamo",
"ciflow/inductor"
] | 1 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150720
* #150258
* #150074
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @... | true |
2,973,526,678 | [export] add runtime assert messages to python torch checks | pianpwk | open | [
"fb-exported",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor",
"merging"
] | 16 | CONTRIBUTOR | ~fixes #150063 (for python at least)
Before:
```
Runtime assertion failed for expression Eq(Mod(s16*s35, s35 - 1), 0) on node 'eq'
```
Now:
```
RuntimeError: Runtime assertion failed for expression Eq(Mod(s16*s35, s35 - 1), 0) on node 'eq'
The original traceback points to the following location and error ... | true |
2,973,522,646 | Codegen or Lint for python-api.md | svekars | open | [
"module: build",
"module: docs",
"triaged"
] | 0 | CONTRIBUTOR | ### 📚 The doc issue
In https://github.com/pytorch/pytorch/pull/149331, we are migrating to pytorch_sphinx_theme2 and the main file that will contain toctree for the python APIs will be `python-api.md`. `index.md` will contain torctrees whose captions will be displayed on the horizontal bar.
We need to add a codegen... | true |
2,973,522,624 | [utils] Print compilation time breakdown across main components | anijain2305 | open | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151410
* #151409
* #150704
* __->__ #150717
* #151357
* #151256
* #151330
Prints something like this
<img width="384" alt="image" src="https://github.com/user-attachments/assets/eaeae3ec-bab1-42e2-acbf-9e74904c6ac2" />
which is very h... | true |
2,973,459,642 | [export] raise when Dim.DYNAMIC 0/1 specializes | pianpwk | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 5 | CONTRIBUTOR | Previously we didn't catch this, mark_dynamic() just doesn't allocate a symbol for it
Differential Revision: D72486930
| true |
2,973,437,169 | Add type hints to `_tensor_docs.add_docstr_all` | pganssle-google | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 8 | CONTRIBUTOR | There is some sort of bug in `pytype` where if this function doesn't have type hints, `pytype` will spend 10 minutes inferring the types. Not that this matters much for a project not using `pytype`, but it led me to realize that this function could easily be type hinted and is not, so here is a PR adding some type hint... | true |
2,973,433,050 | sglang x torch.compile silent incorrectness in PyTorch 2.6 for deepseek-v3 | zou3519 | closed | [
"high priority",
"triaged",
"module: correctness (silent)",
"oncall: pt2"
] | 7 | CONTRIBUTOR | We should check if it's in PyTorch 2.7 as well. If it is then we should fix it
cc @ezyang @gchanan @kadeng @msaroufim @chauhang @penguinwu | true |
2,973,428,721 | cd: Introduce new binary build workflows (cpu) | seemethere | open | [
"release notes: releng"
] | 1 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150713
* #149830
Introduces new binary build workflows and some supplementary changes to
downstream scripts in order to accommodate the new workflows.
Goal here is to get off the ground with the new syntax and ideally make
it easier... | true |
2,973,416,424 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_float16 (__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_abs_fastpath_outplace_cuda_float16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/4000254491... | true |
2,973,400,957 | [ued] HF diffusers pipeline `enable_cpu_offload` errors or graph breaks with a `torch.compile`-ed transformer | StrongerXi | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
_No response_
### Error logs
## Non-inplace `torch.compile` repro
```python
import torch
from diffusers import (
AuraFlowPipeline,
GGUFQuantizationConfig,
AuraFlowTransformer2DModel,
)
transformer = AuraFlowTransformer2DModel.from_single_file(
"https://huggingface.co/city96/... | true |
2,973,376,433 | torch.compile LLMs on MPS progress tracker | manuelcandales | closed | [
"triaged",
"module: mps",
"oncall: pt2",
"module: inductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
This issue is used to keep track of progress using torch.compile on MPS to compile LLMs
##### gpt-fast (mps-compile-experiments branch):
- [ ] Make mps compile work on main.
- [x] stories15M
- [x] stories110M
- [x] llama2-7B
- [ ] llama2-7B 8bit quantized
- [IndexError: Out of range: piece i... | true |
2,973,373,840 | torch.profile aten metadata plumbing | exclamaforte | open | [
"oncall: profiler"
] | 3 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Inductor would like to pass some metadata for `aten` ops down to the dispatcher so that it can add it to the args field of the kineto trace.
### Alternatives
We are manually post processing the profile.json, which is a bit fragile.
### Additional context
_No response_
cc ... | true |
2,973,367,928 | [ued] VRAM keeps growing upon new resolution for diffuser pipeline with `torch.compile`-ed transformer | StrongerXi | closed | [
"needs reproduction",
"oncall: pt2"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
From a user: https://github.com/huggingface/diffusers/issues/10795#issuecomment-2745417752
> 2.2 The VRAM usage keeps growing significantly on each new resolution used in inference (I've run my tests after compiling the pipeline independently) which makes me believe that a new graph may be loa... | true |
2,973,365,734 | Reland of "[ROCm] change preferred blas lib defaults (#150249)"" | atalman | closed | [
"module: rocm",
"ciflow/rocm",
"ci-no-td"
] | 1 | CONTRIBUTOR | Relands pytorch/pytorch#150658 since fixed.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,973,364,200 | [ued] Slow start up time for `torch.compile` on GGUF Auraflow | StrongerXi | open | [
"triaged",
"oncall: pt2",
"compile-cache",
"dynamo-triage-jan2025"
] | 6 | CONTRIBUTOR | ### 🐛 Describe the bug
From a user: https://github.com/huggingface/diffusers/issues/10795#issuecomment-2745417752
> 2.1 Pre-compiling for each resolution is manageable (and somewhat expected), but loading the pipeline and warming it up for each resolution seems to be a big bottleneck as each new resolution takes abo... | true |
2,973,340,290 | [CUDA] Only use vec128 if CUDA version is newer than 12.8 | malfet | open | [
"Merged",
"Reverted",
"ciflow/binaries",
"ciflow/trunk",
"release notes: cuda",
"ciflow/periodic",
"ci-no-td",
"no-runner-experiments"
] | 16 | CONTRIBUTOR | By addressing a feedback requested at https://github.com/pytorch/pytorch/pull/145746 | true |
2,973,328,361 | [invoke_subgraph][fake_tensor] Run the subgraph with fake tensor mode to validate cache | anijain2305 | open | [
"topic: not user facing",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151620
* __->__ #150704
* #151410
* #151409
* #151756
* #151633
* #151477
* #151357
* #151256
* #151330
| true |
2,973,319,279 | Support XPU in memory tracker | frost-intel | open | [
"oncall: distributed",
"open source",
"release notes: python_frontend"
] | 4 | COLLABORATOR | This PR adds support for XPU devices to the distributed MemoryTracker tool, including unit test for XPU.
In detail, I add a few pure-python functions to `torch.accelerator`:
- `torch.accelerator.empty_cache`
- `torch.accelerator.memory_allocated`
- `torch.accelerator.memory_reserved`
- `torch.accelerator.memory_... | true |
2,973,309,427 | [ued] Investigate diffuser pipeline transformer recompilations due to different width/height | StrongerXi | closed | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 17 | CONTRIBUTOR | ### 🐛 Describe the bug
From a user: https://github.com/huggingface/diffusers/issues/10795#issuecomment-2745417752
> 2. Changing the pipeline resolution triggers a recompilation, this happens with both dynamic=None and dynamic=True and resolution affecting the compilation is the most annoying issue right now.
We sho... | true |
2,973,245,857 | Support having no metadata file for HuggingFaceStorageReader | ankitageorge | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (checkpoint)"
] | 6 | CONTRIBUTOR | Summary: If there is only one safetensors file, we don't need users to have a metadata file and we can just construct it from the keys of that file. This is a use-case for some HuggingFace models, so adding support for it
Test Plan:
ensure existing tests pass
tested e2e in a notebook
Differential Revision: D72472490
... | true |
2,973,235,669 | CuDNN + H100 Gives Weird Gradients | alanhdu | open | [
"module: cudnn",
"module: cuda",
"triaged"
] | 9 | CONTRIBUTOR | ### 🐛 Describe the bug
If I run this reproduction script at https://gist.github.com/alanhdu/68aeca1b1cfbe63fe3464541a201fb79 (using this [arr.txt](https://github.com/user-attachments/files/19609554/arr.txt) file in `/tmp/arr.pt`), then I see something quite strange.
On an A100 GPU , I get results like:
```
cpu bf1... | true |
2,973,234,563 | Revert "Dont exclude constant_pad_nd in prologue fusion" | atalman | closed | [
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 1 | CONTRIBUTOR | Reverts pytorch/pytorch#150145
| true |
2,973,204,049 | [Feature Request] Memory optimization for backward propagation in GPU | jobs-git | open | [
"module: autograd",
"module: memory usage",
"triaged"
] | 3 | NONE | ### 🚀 The feature, motivation and pitch
Backprop uses a lot of VRAM and can reach multiple factors the size of the model parameters and input data resulting to a lower GPU utilization. Computing resource and power savings maybe realized if instead we can optimize backprop VRAM usage.
### Alternatives
Possible solut... | true |
2,973,188,735 | Fix conv2d strided prologue | eellison | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/rocm",
"ci-no-td"
] | 11 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150697
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,973,178,868 | Remove Clear Cache Time from do_bench_using_profiling | oniononion36 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Summary: In most instances, this action would take ~33% of the total run time, which means that our benchmark would previously differ from the end results by a lot.
Test Plan:
We can compare the benchmark results for
```
CUDA_VISIBLE_DEVICES=4,5 buck run mode/opt -c python.package_style=inplace -c fbcode.enable_gpu_s... | true |
2,973,149,041 | [AOTI][dashboard] Fix mis-calculated memory compression ratio | desertfire | closed | [
"Merged",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150695
Summary: https://github.com/pytorch/pytorch/pull/149817 introduced an extra warmup run to compute AOTI memory compression ratio, but since weights are only loaded once in the AOTI run, the peak memory seen in the extra warmup ... | true |
2,973,142,897 | [draft][distributed] add into 3d composability test at AMD CI test | mori360 | open | [
"oncall: distributed",
"topic: not user facing"
] | 1 | CONTRIBUTOR | cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,973,129,850 | Remove a workaround added in #149381 | tengyifei | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: releng"
] | 5 | CONTRIBUTOR | Remove a workaround added in https://github.com/pytorch/pytorch/pull/149381.
Fixes https://github.com/pytorch/xla/issues/8934
| true |
2,973,127,295 | [MTIA] Map names to operand indices when folding submodules | klintqinami | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx"
] | 15 | CONTRIBUTOR | When replacing placeholders with getattrs during constant folding, we can have an argument and parameter name mismatch. In fact, there is no guarantee that the parameter name is equivalent to the argument name used in the module call.
Differential Revision: D72415970
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @... | true |
2,973,054,461 | Raise `BufferError` for DLPack buffer-related errors. | ysiraichi | open | [
"open source",
"module: dlpack",
"release notes: python_frontend"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150691
* #150218
* #150217
* #150216
* #145000
This PR addresses the Array API documentation for [`__dlpack__`][1] and
[`from_dlpack`][2] by making some buffer-related errors `BufferError`
instead of `RuntimeError`, e.g. incompatible... | true |
2,972,966,098 | Fixing NCCL abort hang issue when a ProcessGroupNCCL manages multiple ncclComms | hexinw-nvidia | closed | [
"oncall: distributed",
"triaged",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: distributed (c10d)",
"ci-no-td"
] | 35 | CONTRIBUTOR | Detail of the issue:
If PyTorch issues send/recv to each 2 rank comm, and these comms are managed by a single ProcessGroupNCCL instance, then comms need to abort either in sequence or in group.
I.e. the following sequential abort will cause hang in NCCL. recv(..., comm0, stream);
send(..., comm1, stream);
abort... | true |
2,972,920,291 | [rfc] Guard filter hook | anijain2305 | open | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150689
* #150429
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,972,880,083 | [test] cusparse installation in binary build docker img | clee2000 | open | [
"ciflow/binaries",
"topic: not user facing"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
2,972,843,702 | [CI][Inductor] Add missing unittest import | nWEIdia | closed | [
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | COLLABORATOR | Fixes unit test failures:
test/inductor/test_fused_attention.py", line 567, in TestSDPAPatternRewriterTemplate
@unittest.skip("disabled in upstream") ^^^^^^^^ ... | true |
2,972,837,626 | [Inductor] Fix consolidating _scaled_mm into mm template TMA error | PaulZhang12 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Summary: The previous diff broke a few tests that didn't run on internal or GH CI: T220169086, this fixes that issue. The {% if } block is only supposed to support autotuned parameters (constexpr), and should not be used for locals based on other examples.
Test Plan: buck test 'fbcode//mode/opt' fbcode//caffe2/test/in... | true |
2,972,821,266 | WIP : test3 | laithsakka | open | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150685
| true |
2,972,794,969 | Register also future allocations in mempool with NCCL | lw | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150564
* __->__ #150684
* #150683
This is the final PR, where everything comes together.
The problem I'm trying to solve is the following: when we register a MemPool with the NCCL ProcessGroup, it calls `ncclCommRegister` on all the all... | true |
2,972,794,696 | Add mempool to allocator's trace events | lw | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150564
* #150684
* __->__ #150683
In the NCCL ProcessGroup we want to support being able to "register" with NCCL all the allocations that belong to a certain private MemPool. In order to do so on-the-fly for every new allocation, we regist... | true |
2,972,794,398 | Clarify behavior of TORCH_NCCL_USE_TENSOR_REGISTER_ALLOCATOR_HOOK | lw | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150564
* #150684
* #150683
* __->__ #150682
* #150681
I still don't really understand the original purpose of that env var, but it appears that its usage is completely disconnected from MemPools and from `ncclMemAlloc`/`Free`. In fact, whe... | true |
2,972,794,159 | Safer bookkeeping of NCCL communicators | lw | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150564
* #150684
* #150683
* #150682
* __->__ #150681
This consists mainly in two changes:
- ensure we can reliably obtain the device from a `NCCLComm` object (there was one constructor which didn't set the device)
- use a RAII pattern f... | true |
2,972,772,914 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_bool (__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_bool&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/39977154907).
... | true |
2,972,740,951 | Revert "[ATen][CUDA] Implement 128 bit vectorization v2 (#145746)" | atalman | open | [
"topic: not user facing",
"ci-no-td"
] | 2 | CONTRIBUTOR | This reverts commit e84bf88dde509d44175a0a1c00cec13c9926843e.
This PR caused binary size increase 10% and compile time increase:
https://github.com/pytorch/pytorch/issues/150647
https://github.com/pytorch/pytorch/issues/147376
Proposing to revert this PR and reland together: Optimize 128 bit vectorization https... | true |
2,972,463,420 | Split up cub-RadixSortPairs-scalars.cu to parallelize compilation | TovlyFB | open | [
"fb-exported",
"ciflow/trunk",
"release notes: cuda"
] | 4 | CONTRIBUTOR | Summary: `cub-RadixSortPairs-scalars.cu` has slow compilation times, especially on Windows. These changes split up the file into smaller components to allow each component to compile in parallel. On Windows, I observed a compile time drop from about 6 minutes to 4 minutes. This is a similar follow up to [PR 148936](htt... | true |
2,972,454,113 | Compilation Errors with Float Values in flex_attention and create_block_mask | Rilwan-Adewoyin | open | [
"triaged",
"oncall: pt2",
"module: higher order operators",
"module: flex attention"
] | 3 | NONE | ### 🐛 Describe the bug
Bug description:
I've encountered two reproducible bugs when using PyTorch's compiled flex_attention or create_block_mask and referencing either a float value < 1.0 or a scalar float tensor as described in the reproduction steps section. In the script I test four cases: scalar tensor < 1.0, sc... | true |
2,972,357,665 | [CUDA][avgpool2d] Fix backward launch bounds again for `sm100`, `sm120` | pytorchbot | closed | [
"open source",
"release notes: cuda"
] | 1 | COLLABORATOR | `__CUDA_ARCH__` is not visible in host code, which causes incorrect launch bounds and `too many resources requested for launch` on blackwell
CC @atalman @malfet as we would want this in 2.7 @nWEIdia
cc @ptrblck @msaroufim | true |
2,972,156,930 | Add notes of non-integer `dtype` in documentation of `torch.triu_indices()` and `torch.tril_indices()` | ILCSFNO | closed | [
"module: docs",
"triaged",
"module: linear algebra"
] | 5 | CONTRIBUTOR | ### 📚 The doc issue
The docs of [torch.triu_indices()](https://pytorch.org/docs/stable/generated/torch.triu_indices.html#torch-triu-indices) and [torch.tril_indices()](https://pytorch.org/docs/stable/generated/torch.tril_indices.html#torch-tril-indices) show their shared parameter as below:
https://github.com/pytorc... | true |
2,972,117,715 | Size of `tau` can mismatch with the context in `torch.ormqr()` | ILCSFNO | closed | [
"module: docs",
"module: error checking",
"triaged",
"module: linear algebra"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
The docs of [torch.ormqr()](https://pytorch.org/docs/stable/generated/torch.ormqr.html#torch-ormqr) show its documentation as below:
https://github.com/pytorch/pytorch/blob/73358d37dab22a9d080de3e29a576dbab775d15f/torch/_torch_docs.py#L8316-L8358
Let's see a repro below, it can run well:
### ... | true |
2,971,629,485 | AOTI: add all fallback ops that are missing from C-shim | benjaminglass1 | open | [
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu",
"release notes: inductor (aoti)"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150673
Adds all fallback ops that are logged as missing when running the Inductor OpInfo tests with cpp_wrapper mode, with the exception of one or two ops that cannot be currently represented in the C-shim interface.
cc @voznesensky... | true |
2,971,629,367 | AOTI fallback ops: sort alphabetically | benjaminglass1 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150673
* #147225
* __->__ #150672
* #150671
This is just a housekeeping task that makes the listed fallback op order match what's in the generated C shim files. | true |
2,971,629,250 | cpp_wrapper: Re-enable code disabled for forward compatibility | benjaminglass1 | closed | [
"open source",
"Merged",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150673
* #147225
* #150672
* __->__ #150671
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,971,558,604 | Add inductor standalone_compile API | oulgen | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"ci-no-td"
] | 14 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150670
This PR adds standalone_compile API that does precompilation via caching to support vLLM use case in the short term while we work on the longer term precompilation solution.
```
standalone_compile(gm, example_inputs, opti... | true |
2,971,439,069 | [Inductor] Fix CUDA memory usage for CPU only compile | leslie-fang-intel | open | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150669
* #151528
**Summary**
Fix https://github.com/pytorch/pytorch/issues/150622. The root-cause is CUDA device used by default when CUDA is available to generate pattern for a CPU specific compilation. The original PR comes from ... | true |
2,971,427,610 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_bfloat16 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 6 | 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_bfloat16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/39961656616... | true |
2,971,343,322 | [ROCm][CI] Enable distributed CI on MI300 | jithunnair-amd | closed | [
"oncall: distributed",
"module: rocm",
"open source",
"Merged",
"topic: not user facing",
"keep-going",
"ciflow/rocm",
"ciflow/periodic-rocm-mi300"
] | 6 | COLLABORATOR | * Enable distributed CI on MI300 runners, same schedule-based and release-branch triggers as `periodic.yml`; also uses label `ciflow/periodic-rocm-mi300` for triggering on PRs.
* Disabled failing distributed tests on MI300 via Github issues: [151077](https://github.com/pytorch/pytorch/issues/151077), [151078](https://... | true |
2,971,303,426 | [invoke_subgraph] Lazy backward | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150717
* #150782
* __->__ #150666
| true |
2,971,168,530 | The WanVideo ImageClip Encode node Or the Wan Image to Video or WanVideo VACE Encode node in ComfyUI runs very slowly | githust66 | closed | [] | 6 | NONE | ### 🐛 Describe the bug
The WanVideo ImageToVideo Encode node Or the Wan Image to Video node or WanVideo VACE Encode node in ComfyUI runs very slowly. It takes about 500 seconds to execute this node. he GPU utilization is consistently at 5%-8%. Previously, the decoding node also had this problem. Now the decoding work... | true |
2,971,122,431 | [MPS/inductor] Add support for hermite_polynomial_h. | dcci | closed | [
"Merged",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | MEMBER |
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,971,078,614 | Proposing torch.empty_cache (device_type) as generalization of torch.cuda.empty_cache() . | githubsgi | open | [
"triaged",
"module: accelerator"
] | 5 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Device dependent call torch.cuda.empty_cache () make PyTorch model code brittle and un-portable. Proposing a general api torch.empty_cache (device_type) .
### Alternatives
_No response_
### Additional context
_No response_
cc @albanD @guangyey @EikanWang | true |
2,971,016,811 | DISABLED test_parity__foreach_abs_fastpath_inplace_cuda_uint8 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 6 | 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_inplace_cuda_uint8&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/39951410523).
Over t... | true |
2,971,015,429 | [MPS] Make fused rms_norm traceable | malfet | closed | [
"Merged",
"Reverted",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 12 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150661
Which is a regression, introduced by https://github.com/pytorch/pytorch/issues/150629#issue-2970312779 which I should have reviewed more thoroughly.
- Defined `_fused_rms_norm`, added MPS-only implementation for it and dis... | true |
2,970,970,216 | torchrun global rank assignement issues | nsrilalith | closed | [
"oncall: distributed"
] | 5 | NONE | ### 🐛 Describe the bug
```
import torch
import torch.distributed as dist
import os
def main():
# Initialize the distributed process group using NCCL
rank = int(os.environ["RANK"])
world_size = int(os.environ["WORLD_SIZE"])
local_rank = int(os.environ["LOCAL_RANK"])
torch.cuda.set_device(local_ra... | true |
2,970,949,478 | [Inductor] Fallback embedding when sparse is True | leslie-fang-intel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150659
**Summary**
Fix issue: https://github.com/pytorch/pytorch/issues/150656, fallback `embedding` when sparse is True.
**Test Plan**
```
python -u -m pytest -s -v test/inductor/test_torchinductor.py -k test_embedding_sparse... | true |
2,970,944,719 | Revert "[ROCm] change preferred blas lib defaults (#150249)" | atalman | closed | [
"module: rocm",
"ciflow/rocm",
"ci-no-td"
] | 1 | CONTRIBUTOR | This reverts commit 8b6bc59e9552689e115445649b76917b9487a181.
The associated Test was reverted on Trunk: https://github.com/pytorch/pytorch/pull/150581
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,970,935,948 | [AOTI] Remove typedef for half and bfloat16 | desertfire | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor",
"ciflow/rocm",
"ci-no-td",
"ciflow/inductor-periodic"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150657
Summary: typedef is prone to name collision. Explicitly spell out the actual aten types, needed for the libtorch-free codegen.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @w... | true |
2,970,927,881 | `torch.compile` fails with sparse embedding (`F.embedding(sparse=True)`) | merajhashemi | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
When using `torch.compile` on a function that calls `torch.nn.functional.embedding` with `sparse=True`, an assertion error occurs during graph lowering. It appears that this behavior may be intentional due to the lack of support for sparse embeddings, but I couldn't find a tracking issue for it... | true |
2,970,920,645 | Create better alerting for binary size validations and time it takes to build the binary | atalman | open | [
"module: binaries",
"triaged"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
We have following workflow that validates binary size:
https://github.com/pytorch/test-infra/blob/main/.github/workflows/validate-pypi-wheel-binary-size.yml
However it has low visibility.
We need to:
1. Add this to https://github.com/pytorch/test-infra/blob/main/.github/workflows/validate-bi... | true |
2,970,919,590 | [Inductor] Add decomposeK as an autotuning choice for mm | PaulZhang12 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td",
"skip-url-lint"
] | 26 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150654
As a result of adding subgraph as a choice to inductor https://github.com/pytorch/pytorch/pull/149761 and enabling FP32 output from PyTorch GEMMs from FP16/BF16 inputs: https://github.com/pytorch/pytorch/pull/150812, this PR ... | true |
2,970,919,534 | [Inductor] Add Subgraph as a Autotuning Choice | PaulZhang12 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150653
Add the option for providing a Subgraph as an autotuning choice in Inductor. This is crucial for implementing the split-k optimization for GEMMs by decomposing a mm -> bmm. https://github.com/pytorch/pytorch/pull/150654 uses ... | true |
2,970,895,725 | [c10d][fr] Improve FR dump robustness with all watchdog broadcast wait and more frequent store check | fduwjj | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150652
When debugging FR missing dump and missing dump logs, I have couple initial findings:
1. On the same rank, if a second watchdog timeout triggers on a different PG(or subPG), that watchdog thread will immediately throw except... | true |
2,970,895,636 | [aoti] Use generate_fake_kernels_from_real_mismatches config for draft exported programs | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Summary:
Sometimes we get `MetadataMismatchError` in aoti compilation because draft export uses the flag below to infer the fake kernel when there’s a mismatch, but aoti doesn’t have this flag turned on.
https://fburl.com/code/9qzytl6q
torch._functorch.config.generate_fake_kernels_from_real_mismatches
If we set thi... | true |
2,970,895,388 | [DTensor] clean up _local_shard_size_and_offset | 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):
* #150887
* #150862
* __->__ #150650
* #150490
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @d4l3k | true |
2,970,870,410 | ENH: Publish full-fledged tarballs also for release candidates | h-vetinari | closed | [
"oncall: releng",
"triaged",
"enhancement",
"actionable"
] | 1 | CONTRIBUTOR | In #149044, there was the following discussion
> @h-vetinari:
> > **Phase 2 (after 3/31/25):**
> > Note that changes here require us to rebuild a Release Candidate
>
> What's the intention w.r.t. release candidates like [`v2.7.0-rc2`](https://github.com/pytorch/pytorch/releases/tag/v2.7.0-rc2)? Since we're still in P... | true |
2,970,867,381 | [c10d] Surface error type when we unlink and create named pipe for DumpPipe | fduwjj | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150648
cc @H-Huang @awgu @wanchaol @fegin @wz337 @wconstab @d4l3k | true |
2,970,866,954 | PyTorch wheel binary size increase ~80mb | atalman | open | [
"module: binaries",
"oncall: releng",
"triaged",
"topic: binaries"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Found that we had binary size increase ~80mb for cuda 12.4 happen on Jan 31 2025:
<img width="1015" alt="Image" src="https://github.com/user-attachments/assets/ad25ed02-31e2-46a3-8a36-6e3f94c26de5" />
Commit where the increase happened: https://github.com/pytorch/pytorch/commit/edf08cb080c202... | true |
2,970,841,965 | WIP: Remove Conda Instructions | AlannaBurke | closed | [
"module: docs",
"release notes: releng",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Fixes #149551
Removing Conda installation instructions.
Anywhere there were multiple instructions, I removed the Conda ones and left the pip ones. If I wasn't sure what to replace the instructions with, I just left a comment so we'd see all the places it's mentioned when reviewing this PR. I also cleaned up a cou... | true |
2,970,841,904 | [dynamo] reconstruct functions decorated in the compiled region properly | williamwen42 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"keep-going"
] | 6 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150586
* __->__ #150645
We were previously unable to reconstruct functions that were decorated in the compiled region.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayis... | true |
2,970,838,269 | [AO] Refactor convert and add QuantAffinePlaceholderObserver | mcr229 | closed | [
"Merged",
"ciflow/trunk",
"release notes: quantization"
] | 19 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150644
* #150643
* #150642
| true |
2,970,838,146 | [AO] Add Moving Average Affine Observer | mcr229 | closed | [
"Merged",
"ciflow/trunk",
"release notes: quantization"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150644
* __->__ #150643
* #150642
| true |
2,970,838,005 | [AO] update port_metadata_pass to support quant_affine ops | mcr229 | closed | [
"Merged",
"release notes: quantization",
"release notes: AO frontend"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150644
* #150643
* __->__ #150642
| true |
2,970,811,764 | tutorial example for cp | XilunWu | open | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150641
| true |
2,970,766,348 | [CUDA][avgpool2d] Fix backward launch bounds again for `sm100`, `sm120` | eqy | closed | [
"module: cuda",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing"
] | 8 | COLLABORATOR | `__CUDA_ARCH__` is not visible in host code, which causes incorrect launch bounds and `too many resources requested for launch` on blackwell
CC @atalman @malfet as we would want this in 2.7 @nWEIdia
cc @ptrblck @msaroufim | true |
2,970,713,917 | [cutlass backend] Add more logs for cutlass backend benchmark | henrylhtsang | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150639
Goal is to have a way to compare if a change make it better or worse.
```
Average edge over aten (max(-edge, 0), higher is better):
triton: 8.596507086950552 (from 6 valid values)
triton_persistent_tma: 9.517193693923... | true |
2,970,658,678 | Difference in outputs with dtype `bf16` with `torch.compile` | shivam15s | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 4 | NONE | ### 🐛 Describe the bug
- Difference in outputs with torch compile vs eager pytorch with input dtype bf16
- Also note, setting bias to zeros makes the torch.allclose pass.
Reproducer:
```python
import torch
import torch.nn.functional as F
# seed
torch.manual_seed(0)
def get_per_token_logps(input, weight, bias, sel... | true |
2,970,584,290 | Segmentation fault with float16 + CPU mode + large tensor matmuls | srampal | closed | [
"high priority",
"module: crash",
"module: cpu",
"triaged",
"module: 64-bit",
"module: regression",
"module: half",
"module: intel"
] | 11 | NONE | ### 🐛 Describe the bug
Performing torch.matmul() with large tensors and dtype = float16 and cpu mode triggers a segmentation fault.
Example:
```python
import torch
def matrix_vector_operations(N_values):
for N in N_values:
A = torch.rand(N, N, dtype=torch.float16, device="cpu")
X = torch.... | true |
2,970,563,557 | [precompile] Serialization for GlobalStateGuard | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Summary: To preserve global state guards we need to make the C++ type serialzable. Using json because it's easier to do and we don't have a lot of data in global state.
Test Plan: test_dynamo -k test_global_state_guard_serialization
Differential Revision: D72410611
cc @voznesenskym @penguinwu @EikanWang @jgong5 @... | true |
2,970,527,939 | [validations] Run nccl version check on Linux only | atalman | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Followup https://github.com/pytorch/pytorch/pull/150194 to disable nccl version print on OS's other then Linux | true |
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