id int64 2.74B 3.05B | title stringlengths 1 255 | user stringlengths 2 26 | state stringclasses 2
values | labels listlengths 0 24 | comments int64 0 206 | author_association stringclasses 4
values | body stringlengths 7 62.5k ⌀ | is_title bool 1
class |
|---|---|---|---|---|---|---|---|---|
3,040,294,136 | [precompile] [easy] Refactor FxGraphCache to add cache_hit_post_compile function | jamesjwu | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152840
* __->__ #152839
* #152836
This PR refactors CompiledFxGraph by adding a new post_compile step that only runs on cache hit. This refactors a bunch of code in _lookup_graph to its own function so that we can use it in BundledAOTA... | true |
3,040,292,658 | [ROCm] Fix SymmetricMemory build error on NAVI arch | pragupta | closed | [
"oncall: distributed",
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)",
"ciflow/periodic",
"ciflow/rocm",
"ciflow/periodic-rocm-mi300"
] | 6 | CONTRIBUTOR | NAVI arch doesn't support `__builtin_amdgcn_s_memtime()`, using `clock64()` instead which works for both NAVI and MI archs.
Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @nar... | true |
3,040,279,361 | [nativert] Move MPMCQueue to torch/nativert. | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 21 | CONTRIBUTOR | Summary:
Torch Native Runtime RFC: https://github.com/zhxchen17/rfcs/blob/master/RFC-0043-torch-native-runtime.md
To land the runtime into PyTorch core, we will gradually land logical parts of the code into the Github issue and get each piece properly reviewed.
This diff adds a small library implementing a multi... | true |
3,040,243,576 | [precompile] Refactor AOTAutogradCacheEntry to be generic | jamesjwu | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152840
* #152839
* __->__ #152836
The purpose of this stack is to create a new BundledAOTAutogradCacheEntry, which is an AOTAutogradCacheEntry that is self contained, i.e. it contains all of the CompiledFxGraph directly in the entry, i... | true |
3,040,225,776 | [DRAFT] Test nccl | atalman | open | [
"ciflow/binaries"
] | 2 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
3,040,174,808 | [c10d] Fix extra CUDA context created by barrier | kwen2501 | open | [
"oncall: distributed",
"release notes: distributed (c10d)"
] | 1 | CONTRIBUTOR | Fixes #149119.
In ProcessGroup.hpp, we create a dummy tensor for dispatching. This requires a correct device index. This PR uses `device_id` given by user when calling `init_process_group`.
This PR also uses `torch._C._get_accelerator()` to determine the device type.
ghstack-source-id: 96c32b9565794d995c26bd17... | true |
3,040,167,991 | Document that dampening is skipped in SGD momentum first step | janeyx99 | closed | [
"Merged",
"ciflow/trunk",
"topic: docs",
"release notes: optim"
] | 3 | CONTRIBUTOR | Pointed out by https://x.com/hi_tysam/status/1917318692276174977/photo/2.
It would be BC breaking to change this behavior 7 years after it has been decided, so we are documenting it first at the very least.
<img width="642" alt="image" src="https://github.com/user-attachments/assets/3febcb07-e0ed-44a1-bd3b-a8e685... | true |
3,040,134,501 | Allow to set custom PYTHONPATH for torch.inductor | gdippolito | open | [
"triaged",
"open source",
"oncall: pt2",
"module: inductor",
"release notes: inductor"
] | 4 | NONE | When using Bazel, it’s common to encounter issues like [this](https://github.com/bazelbuild/bazel/issues/14640) and [this](https://github.com/bazel-contrib/rules_python/issues/792) where the `PYTHONPATH` environment variable becomes too long and results in an error such as: `OSError: [Errno 7] Argument list too long` .... | true |
3,040,131,353 | [pytorch][PR][inductor] Fix one instance of launch_enter_hook | devashishshankar | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Summary: One usage seems missed in https://github.com/pytorch/pytorch/pull/152457
Test Plan: EMS local benchmark
Differential Revision: D74159749
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @... | true |
3,040,101,312 | [BE]: Improve aten formatter with fmtlib | Skylion007 | open | [
"open source"
] | 2 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
3,040,027,504 | Don't hardcoded support for DTensor to_local/from_local/redistribute into dynamo | bdhirsh | open | [
"oncall: distributed",
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | There has been a long-standing hack in dynamo around support for DTensor - there are a few primitive functions (listed above) that accept opaque python types (`DTensorSpec/Placement/DeviceMesh`) and therefore cannot go in the dynamo graph, that have hardcoded support in dynamo.
This is bad for several reasons:
(1) it... | true |
3,040,016,632 | [MSVC] Enable updated lambda processor by setting compiler flag /Zc:lambda globally | taras-janea | open | [
"module: build",
"module: windows",
"module: cpu",
"open source",
"topic: not user facing",
"skip-url-lint"
] | 1 | COLLABORATOR | Fixes:
- https://github.com/pytorch/pytorch/issues/92600
[Enable updated lambda processor](https://learn.microsoft.com/en-us/cpp/build/reference/zc-lambda?view=msvc-170) by setting compiler flag `/Zc:lambda` globally.
cc @malfet @seemethere @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremyux @Blackhex @jgong5 @min... | true |
3,039,923,454 | Pipeline Parallelism Fails when stage input does not produce gradients in all stages. | man2machine | open | [
"oncall: distributed"
] | 0 | NONE | ### 🐛 Describe the bug
TLDR: Pipeline parallelism fails if stage input does not have gradients produced
Consider the case where a outputs from each pipeline stage is passed to the next stage, but whether or not the output is used or not for a particular batch is conditional (based on the code of the model). Hence, i... | true |
3,039,919,509 | Only do shallow clone when checkout nccl | YouJiacheng | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Note: `--depth` implies `--single-branch` since git 2.7.6
```sh
git clone https://github.com/NVIDIA/nccl.git
Cloning into 'nccl'...
remote: Enumerating objects: 4205, done.
remote: Counting objects: 100% (238/238), done.
remote: Compressing objects: 100% (122/122), done.
remote: Total 4205 (delta 144), reused ... | true |
3,039,882,069 | Use gcc13 in Manylinux 2.28 images | atalman | open | [
"ciflow/binaries",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Related to: https://github.com/pytorch/pytorch/issues/152426 | true |
3,039,706,050 | `mypy` stage of `lintrunner -a` has intermittent but continuing crashes | rec | open | [
"module: crash",
"module: lint",
"triaged",
"module: flaky-tests",
"bug"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
Sometimes (5-10% of the time?) when I run `lintrunner init && lintrunner -a` I get a Python traceback in the second step (listed below). Almost always this does not happen again when I rerun the command.
I've been sort of ignoring it for a long time but figured I should finally report it!
The... | true |
3,039,582,622 | Performance Regression nightly 03/11→03/12, on nanogpt speedrun | YouJiacheng | open | [
"high priority",
"triaged",
"oncall: pt2",
"upstream triton",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 9 | CONTRIBUTOR | ### 🐛 Describe the bug
code: https://gist.github.com/YouJiacheng/687efdab59a3c3b4ad89864804bd918a
I manually applied changes from #152641
03/10: 1469.0-1470.4s (3 runs)
03/11: 1469.4-1470.5s
03/12: 1486.0-1487.4s (a few runs)
03/15: ≈1487.5s (a single run)
FWD diffs (03/10 vs. 03/15): https://www.diffchecker.com/bL... | true |
3,039,556,091 | TorchRun: Option to specify which GPUs to run on | bjourne | open | [
"oncall: distributed"
] | 2 | NONE | ### 🚀 The feature, motivation and pitch
TorchRun has an `--nproc-per-node` option to specify how many processes/gpus to use. But it has no option for specifying *which* gpus to use. So if you run torchrun multiple times the same gpus will be used. You can get around that as follows:
CUDA_VISIBLE_DEVICES="2,4,7" ... | true |
3,039,454,175 | [Easy][Inductor] Adds safety checks in get_estimated_runtime | Aidyn-A | open | [
"triaged",
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 11 | COLLABORATOR | This PR adds checks on `gpu_memory_bandwidth` and `gpu_flops` in `get_estimated_runtime`. This will prevent division by zero and other potential incorrect values:
https://github.com/pytorch/pytorch/blob/9210a98b9203c5ff42f39241304a8e38435110b8/torch/_inductor/scheduler.py#L864-L865
https://github.com/pytorch/pytorc... | true |
3,039,435,245 | [DO NOT MERGE] update build tools version | alinpahontu2912 | open | [
"triaged",
"open source",
"ciflow/binaries_wheel"
] | 2 | COLLABORATOR | Use latest msvc to build pytorch and check if avs512 instructions are correctly set
| true |
3,039,424,780 | [TEST][Quantization] Skip test_learnable due to hypothesis | Aidyn-A | open | [
"triaged",
"open source",
"release notes: quantization",
"topic: not user facing"
] | 2 | COLLABORATOR | As per comment in https://github.com/pytorch/pytorch/issues/111471#issuecomment-1866933243 the tests are failing due to hypothesis. This PR adds a skip to those tests. | true |
3,039,320,406 | fix: correct typo in randomness/reproducibility documentation | nachodieez | closed | [
"open source",
"topic: not user facing"
] | 4 | NONE | Fixes #152817 by using the correct word in the documentation file.
| true |
3,039,309,286 | Mention of nondeterministic index_add when deterministic implementation is being used | nachodieez | closed | [] | 1 | NONE | ### 📚 The doc issue
In [this documentation page](https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms) it is mentioned that the nodeterministic CUDA implementation of `index_add` is being used when in fact the one that is being used and is giving error is the deterministic versio... | true |
3,039,170,171 | Depthwise Separable Convolutions with Large Tensors (> 2**31) Elements) Fail Despite cuDNN 64-bit Indexing Support | lely475 | open | [
"module: cudnn",
"module: cuda",
"module: convolution",
"triaged",
"module: 64-bit"
] | 3 | NONE | ### 🐛 Describe the bug
The forward pass on a 2D convolutional layer using grouped convolutions (e.g., depthwise separable convolutions) fails when operating on tensors with more than 2\**31 elements. This limitation persists even when cuDNN v9.7.1 is used, which should theoretically support 64-bit indexing for large t... | true |
3,039,108,164 | [Cutlass] E2E Tests for EVT | mlazos | open | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | 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 |
3,039,106,703 | [TEST][ATen][CUDA] Skip row-wise scaled matrix mmultiplication tests on sm_120+ | Aidyn-A | open | [
"module: cuda",
"triaged",
"open source",
"topic: not user facing"
] | 10 | COLLABORATOR | The float8 row-wise scaled matmuls are not supported on Blackwell yet. This PR adds skips to those tests to decrease the noise on `sm_120+` machines.
cc @ptrblck @msaroufim @eqy @jerryzh168 | true |
3,039,101,868 | Mismatch in dynamic quantization performance for torchao and torch.quantization | PioneerAlexander | open | [
"oncall: quantization"
] | 0 | NONE | Hi everyone!
Can someone explain, why I get different performance, when I apply torch.quantization.quantize_dynamic and torchao.quantize_?
More specifically, I have an LSTM model with two fully connected layers (in the front and in the back). In order to quantize it with torchao, I reimplemented a lstm layer (checked... | true |
3,038,948,509 | Fix typo on `test_multi_device_context_manager` for XPU | guangyey | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu"
] | 11 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152812
# Motivation
Align https://github.com/pytorch/pytorch/pull/152474, fix the typo on UT for XPU introduced by https://github.com/pytorch/pytorch/issues/148864 | true |
3,038,926,403 | [Quant][X86] add an op to compute uint8 batch norm 2d | Xia-Weiwen | open | [
"module: cpu",
"open source",
"release notes: quantization",
"intel"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152811
* #152411
**Summary**
This PR adds a new op, `onednn.qbatch_norm2d`, which accepts uint8 inputs on CPU device (instead of QuantizedCPU).
The new ops are implemented with AVX512 instructions and it provides similar performan... | true |
3,038,863,226 | Upgrade to NCCL 2.26.5 for CUDA 12 | tinglvv | open | [
"open source",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 19 | COLLABORATOR | Upgrade NCCL to latest 2.26.5
cc @atalman @ptrblck @malfet @eqy @nWEIdia
| true |
3,038,859,346 | [xla hash update] update the pinned xla hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | COLLABORATOR | This PR is auto-generated nightly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/nightly.yml).
Update the pinned xla hash. | true |
3,038,821,202 | another try | hl475 | open | [
"module: cpu",
"fb-exported",
"release notes: quantization"
] | 2 | CONTRIBUTOR | Differential Revision: D74161994
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 | true |
3,038,800,154 | wip | hl475 | open | [
"module: cpu",
"fb-exported",
"release notes: quantization"
] | 2 | CONTRIBUTOR | Differential Revision: D74161784
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 | true |
3,038,780,293 | [invoke_subgraph] Force the output stride to be same as eager | anijain2305 | open | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152806
* #152675
* #152770
* #152772
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,038,763,925 | False INTERNAL ASSERT FAILED | noaft | closed | [
"needs reproduction",
"oncall: jit"
] | 3 | NONE | ### 🐛 Describe the bug
This my code:
import torch
# Đây là model sau khi convert rồi
quantized_model.eval()
# Convert sang TorchScript
scripted_model = torch.jit.script(quantized_model)
# Lưu lại bằng TorchScript
scripted_model.save("resnet50_int8_scripted.pt")
I want to save my model quantitied with jit and have... | true |
3,038,592,496 | Segmentation fault (core dumped) in torch.nn.functional.max_unpool2d | cx104906 | closed | [
"triage review",
"module: crash",
"topic: fuzzer"
] | 3 | NONE | ### 🐛 Describe the bug
reproduce
```
curl -L -o 004-args "https://github.com/cx104906/poc/raw/main/pytorch/id%3A000004-args"
curl -L -o 004-kwargs "https://github.com/cx104906/poc/raw/main/pytorch/id%3A000004-kwargs"
python cxtest1.py
```
cxtest1.py
```
import torch
import pickle
print(torch.__version__)
mylist = to... | true |
3,038,557,505 | same test for guard_or_false 2 | laithsakka | open | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152803
* #152802
* #152784
* #152722
* #148872
| true |
3,038,556,240 | same test for guard_or_false 1 | laithsakka | open | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152803
* __->__ #152802
* #152784
* #152722
* #148872
| true |
3,038,539,405 | Thread through options so GraphPickler can allow all ops | aorenste | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"topic: not user facing",
"fx"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152801
Fixes #151904
In #151904 we discussed the feasibility of including all ops in the GraphPickler. This PR changes it so we can filter which ops are allowed and which are blocked.
cc @ezyang @SherlockNoMad @EikanWang @jgo... | true |
3,038,484,054 | Add "#pragma once" to CachingHostAllocator.h | jhapradip | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | null | true |
3,038,430,994 | [float16]: Fast path for torch.dot with float16/bfloat16 | f2013519 | closed | [
"module: cpu",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: linalg_frontend",
"topic: performance",
"ci-no-td"
] | 21 | CONTRIBUTOR | Fixes #152798
Add the fast path for dot with contiguous tensors for float16/bfloat16 types.
Performance with patch (see issue for benchmark and current performance):
**We see up to 10x+ improvement i... | true |
3,038,418,140 | Poor performance of torch.dot with float16 & bfloat16 | f2013519 | closed | [
"triaged",
"module: bfloat16",
"module: half",
"module: linear algebra",
"topic: performance"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
torch.dot is an order of magnitude slower(or more) with float16/bfloat16 versus float32:
```python
import torch
import timeit
import sys
import platform
import matplotlib.pyplot as plt
import numpy as np
import warnings
import math
# --- Configuration ---
# Vector sizes (N) - Powers of 10 fro... | true |
3,038,373,933 | DISABLED test_comprehensive_fliplr_cuda_float16 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_fliplr_cuda_float16&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41618142892).
Over the p... | true |
3,038,373,932 | DISABLED test_comprehensive_rot90_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 5 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_rot90_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41618142889).
Over the pa... | true |
3,038,373,442 | DISABLED test_comprehensive_unbind_copy_cuda_int32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 14 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_unbind_copy_cuda_int32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41618142889).
Over th... | true |
3,038,373,416 | DISABLED test_comprehensive_slice_scatter_cuda_bool (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 12 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_slice_scatter_cuda_bool&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41618142892).
Over t... | true |
3,038,373,413 | DISABLED test_comprehensive_linalg_pinv_singular_cuda_float64 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_linalg_pinv_singular_cuda_float64&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41618142... | true |
3,038,371,840 | Pass UNINSTALL_DILL to docker build | cyyever | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | `UNINSTALL_DILL` was not really passed to docker before. | true |
3,038,326,479 | Inconsistent export behavior for nonzero+grid_sample between CUDA and CPU/MPS backends | sachin-skyline | open | [
"oncall: pt2",
"oncall: export"
] | 1 | NONE | ### 🐛 Describe the bug
I am trying to `export` a model that contains a `nonzero` call followed by a `grid_sample` (for use in `aoti_compile_and_package`). When exporting for cpu or mps, no error is thrown, but when using cuda, "torch._dynamo.exc.UserError: Could not guard on data-dependent expression Eq(2*u0, 0) (unh... | true |
3,038,266,053 | [CXX11ABI] torch 2.6.0-cu126 and cu124 have different exported symbols | vadimkantorov | open | [
"module: binaries",
"module: cuda",
"triaged"
] | 15 | CONTRIBUTOR | ### 🐛 Describe the bug
The symbol `_ZN3c105ErrorC2ENS_14SourceLocationESs` is exported in cu124's version, but missing in cu126: some `nm` outputs in https://github.com/Dao-AILab/flash-attention/issues/1644
I understand that because of missing symbols, flash_attention has stopped working with torch 2.7. But it was a... | true |
3,038,259,121 | Fixed rerr computation in lobpcg | ignasa007 | open | [
"open source",
"release notes: linalg_frontend"
] | 15 | NONE | Fixes #101075
This PR fixes an issue with the computation of residuals in the LOBPCG algorithm.
**Bug**: [Line 788](https://github.com/pytorch/pytorch/blob/8f54e56e62692bcebf218f2e4c1855a3be97baf2/torch/_lobpcg.py#L788) is supposed to compute the denominator in Equation 9 of [Duersch et al., 2018](https://arxiv.... | true |
3,038,243,246 | [MPSInductor] Fix `truncdiv` implementation | malfet | closed | [
"Merged",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152788
For integral dtypes it should be just an alias for division
Fixes `GPUTests.test_div7_mps`
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @cheny... | true |
3,038,209,346 | Implement DeviceType.h as header-only | desertfire | open | [
"oncall: jit",
"module: cpu",
"module: mkldnn",
"ciflow/trunk",
"release notes: quantization",
"ciflow/inductor",
"ciflow/linux-aarch64"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152787
Summary: Move c10/core/DeviceType.h to a separate torch/csrc/header_only directory. Still keep a copy of c10/core/DeviceType.h for backwrad compatibility. More header files will be moved as follow-up. CI to guard "header-only-... | true |
3,038,188,163 | Update CMakeLists.txt | gisp-cubicon | open | [
"triaged",
"open source",
"topic: not user facing"
] | 2 | NONE | Fixes #ISSUE_NUMBER
| true |
3,038,177,115 | Fix negative dim issue in for parallel loss context manager | abhilash1910 | open | [
"oncall: distributed",
"triaged",
"open source",
"topic: not user facing"
] | 6 | NONE | Facing similar issue as on #152016 , and added as per @tianyu-l 's solution.
Fixes #152016
Tagging @tianyu-l @atalman for review.
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,038,168,322 | test that guard_or_true change can only make valid results null but does not change result or make invalid valid | laithsakka | open | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152803
* #152802
* __->__ #152784
* #152722
* #148872
| true |
3,038,134,742 | undefined symbol: __nvJitLinkCreate_12_8, version libnvJitLink.so.12 | FurkanGozukara | open | [
"triage review",
"module: binaries"
] | 3 | NONE | I am trying to use Torch 2.7 with CUDA 12.8 on Linux with Kohya trainer and I am getting this error
Exactly same installation and setup works on Windows
I tried Torch 2.7 official and latest Torch 2.8 nightly all CUDA 12.8 and same error
```
╭───────────────────── Traceback (most recent call last) ────────────────... | true |
3,038,076,765 | [BE]: Update cudnn to 9.9 for cu128 | Skylion007 | open | [
"open source",
"topic: not user facing",
"ciflow/inductor",
"ciflow/inductor-cu126"
] | 1 | COLLABORATOR | Update cudnn to 9.9 for better blackwell support for cu128 | true |
3,038,073,282 | [MPS] SDPA specialized kernels | Isalia20 | closed | [
"triaged",
"open source",
"Merged",
"module: mps",
"release notes: mps",
"ciflow/mps",
"module: sdpa"
] | 8 | COLLABORATOR | Paritally fixes #139668 and #152550
Still work in progress. Following needs to be addressed:
- [x] Some tests are failing and need to check why and bugfix
- [x] Benchmark the new kernels and add to this PR for varying sequence lengths head dimensions(the ones that get dispatched to kernels)
- [x] Add tests to co... | true |
3,038,054,985 | Error with nccl + multiple RTX5090 in ddp training. CUDA error: an illegal memory access was encountered | KohakuBlueleaf | closed | [
"oncall: distributed",
"triaged"
] | 3 | NONE | ### 🐛 Describe the bug
Related issues: https://github.com/Lightning-AI/pytorch-lightning/issues/20757
When I tried to run DDP training with multiple RTX5090 I encountered the error in nccl.
I have seen this in different task/project and different trainer implementation, and eventually reproduced this error with nati... | true |
3,038,050,985 | [BE]: Update cutlass submodule to 3.9.2 | Skylion007 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda",
"module: dynamo",
"ciflow/inductor"
] | 4 | COLLABORATOR | A lot of last minute bugfixes for CUTLASS blackwell that we should upstream. It's a header only library and a minor release so this should strictly improve compiler support and fix some bugs. Needed to update some instruction numbers in torch compile baselines for the new kernels
cc @voznesenskym @penguinwu @Eikan... | true |
3,038,048,736 | [BE]: Update torch core lazy helpers with micropts | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | COLLABORATOR | Some minor nits I noticed. Use reserve when possible | true |
3,037,894,802 | Segmentation fault (core dumped) in torch.nn.functional.alpha_dropout | cx104906 | open | [
"module: crash",
"oncall: quantization",
"module: error checking",
"triaged",
"module: empty tensor",
"topic: fuzzer"
] | 1 | NONE | ### 🐛 Describe the bug
reproduce
```
curl -L -o 003-args "https://github.com/cx104906/poc/raw/main/pytorch/id%3A000003-args"
curl -L -o 003-kwargs "https://github.com/cx104906/poc/raw/main/pytorch/id%3A000003-kwargs"
python cxtest1.py
```
cxtest1.py
```import torch
import pickle
print(torch.__version__)
mylist = tor... | true |
3,037,832,335 | [WIP] Pattern matcher support for mutable ops with view inputs | yf225 | open | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152776
* #152775
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,037,808,077 | [Inductor] Pattern matcher support for mutable ops with non-view inputs | yf225 | open | [
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 2 | CONTRIBUTOR | Fixes the non-view input use case in https://github.com/pytorch/pytorch/issues/152441.
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152776
* __->__ #152775
Pull-Request-resolved: https://github.com/pytorch/pytorch/pull/152767
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guob... | true |
3,037,780,186 | [dynamo][super variable] Fix bug to use correct source | anijain2305 | closed | [
"module: rocm",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,037,779,755 | RuntimeError: creation_meta == CreationMeta::DEFAULT INTERNAL ASSERT FAILED at "/build/pytorch/torch/csrc/autograd/variable.cpp":224, please report a bug to PyTorch. | ad8e | open | [
"high priority",
"triage review",
"module: autograd",
"triaged"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
Reproducer:
1. `git clone https://github.com/crowsonkb/k-diffusion.git`
2. `cd k-diffusion`
3. Use find in files: `q, k = scale_for_cosine_sim(q, k, self.scale[:, None], 1e-6)` (it'll be in image_transformer_v2.py). Comment it out.
4. Run `python train.py --config configs/config_oxford_flowers.... | true |
3,037,774,797 | [fx] Recursive DCE on subgraphs | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"topic: not user facing",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"ci-no-td",
"ciflow/pull"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152806
* #152675
* #152770
* __->__ #152772
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @cha... | true |
3,037,772,983 | [aoti] Add grid_sampler_3d to cshim | MaanasArora | open | [
"triaged",
"open source",
"module: inductor",
"release notes: inductor (aoti)"
] | 4 | NONE | Fixes #147625.
Do we need any tests?
This is my first contribution. Thanks!
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @angelayi @desertfire
| true |
3,037,768,075 | [inductor][refactor] Refactor the fetching of subgraph names | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"ciflow/pull"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152806
* #152675
* __->__ #152770
* #152772
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,037,708,655 | Set CMake 3.5 as minimum version in pytorch_android | cyyever | closed | [
"open source",
"Merged",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing",
"ciflow/android"
] | 9 | COLLABORATOR | I saw pytorch_android failure in docker image builds. This fix attempts to bypass CMake 4 limitations. | true |
3,037,694,873 | [cudagraphs] Fix issue in collecting static_input_idxs | pytorchbot | closed | [
"open source",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: AO frontend"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152287
related to https://github.com/pytorch/pytorch/issues/152275
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amj... | true |
3,037,692,794 | [WIP] Pattern matcher support for custom op | yf225 | closed | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152767
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,037,690,318 | [caffe2] Support building for armv8.1 | andrewjcg | closed | [
"module: cpu",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary:
- Remove explicit `-march=` compiler flags, as they're already implied by
the toolchain:
https://www.internalfb.com/code/fbsource/[7f85b0565073]/fbcode/tools/build/buck/wrappers/defs.bzl?lines=819
- Gate non-8.1 compliant opcodes with `__ARM_FEATURE_*`.
Test Plan: CI
Reviewed By: rahulg
Differential Revi... | true |
3,037,687,461 | [c10d] Fix unused `group` input argument in `new_subgroups()` | tsunghsienlee | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 10 | CONTRIBUTOR | Summary: This diff fixes an unused input argument [`group`](https://github.com/pytorch/pytorch/blob/8faa22569519b8916dfa0334287cbb849704965f/torch/distributed/distributed_c10d.py#L5341) in the `new_subgroups()` function.
Test Plan: contbuild & OSS CI, see
Differential Revision: D74132537
cc @H-Huang @awgu @wancha... | true |
3,037,685,086 | [WIP] fix issue 151198 | yf225 | closed | [
"module: cpu",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152764
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @... | true |
3,037,676,169 | can't build torch on WSL | thot-experiment | closed | [
"module: build"
] | 5 | NONE | ### 🐛 Describe the bug
I'm on hour 5 of trying to get a version of torch built that support sm_70 AND sm_120, for some reason the latest linux version does not, everything is working fine for me under windows so I know it must be possible to do both somehow but I'm sort of at wits end. I've followed the instructions ... | true |
3,037,564,690 | added short integer for repeat_interleave_cpu, Fixes #151311 | arjuanwall | open | [
"triaged",
"open source",
"topic: not user facing"
] | 5 | NONE | - Fixes #151311 (repeat_interleave_cpu not implemented for "Char")
- Allows torch.repeat_interleave on CPU to accept int8, uint8, and int16 repeat‑count tensors
- In aten/src/ATen/native/Repeat.cpp, tiny integer dtypes (kChar, kByte, kShort) are up‑cast to kInt before the AT_DISPATCH_INDEX_TYPES macro, so they reach ... | true |
3,037,563,460 | Performance Regression nightly 02/14→02/15, on nanogpt speedrun | YouJiacheng | closed | [] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
I manually applied changes from #152641
02/09: 1469.8-1470.4s.
03/01: 1471.3-1472.5s.
#### Inductor output code
1. (02/09 + patch vs. 03/01 + patch)
Bwd diff:
https://www.diffchecker.com/p6TsbcIF/
Fwd diff (~no diff):
https://www.diffchecker.com/BaZVI86E/
#### Bisection
02/20 Bwd is identic... | true |
3,037,539,544 | [Easy][BE] update recommanded VS Code settings | XuehaiPan | open | [
"open source",
"better-engineering",
"topic: not user facing"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152760
Remove old invalid settings and replace with new settings. | true |
3,037,484,623 | Allow ATen ops overloading | goldcoderZ | open | [
"fb-exported"
] | 4 | CONTRIBUTOR | Summary: Allow ATen ops being overloaded.
Test Plan: contbuild & OSS CI [pending]
Differential Revision: D74117257
| true |
3,037,303,120 | [MPS] Migrate div roudning modes | malfet | closed | [
"Merged",
"topic: improvements",
"release notes: mps",
"ciflow/mps",
"keep-going"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152788
* __->__ #152758
By implementing `div_floor` and `div_trunc` . Do not mark `div_trunc` as OPMATH, to align following output with CPU(if division is performed in fp32, than result will be truncated to 25
```
import torch
print(t... | true |
3,037,220,364 | wip | bobrenjc93 | closed | [
"release notes: fx",
"fx",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152757
* #152601
* #152597
* #152596
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
3,037,212,290 | Cuda-12.9 removed libnvToolsExt.so.* and is now purely header nvtx3 | whitesscott | open | [
"module: cuda",
"triaged",
"actionable"
] | 3 | NONE | ### 🐛 Describe the bug
Nvidia released Cuda-12.9 on 05/01/25
Python 3.12.10 venv
Nvidia Jetson AGX Orin dev kit
Cuda-12.9 removed libnvToolsExt.so.* and is now purely header /usr/local/cuda/include/nvtx3/*
torch/__init__.py attempts to load the now nonexistent library:
"nvtx": "libnvToolsExt.so.*[0-9]",
I... | true |
3,037,186,867 | Inconsistent behavior between CPU and GPU implementations of `torch.Tensor.put_` method | SilentTester73 | closed | [] | 1 | NONE | ### 🐛 Describe the bug
## Description
I've discovered a discrepancy in the behavior of the `put_` method between CPU and GPU tensors. When executing identical operations, CPU tensors maintain their original values while GPU tensors are incorrectly modified to zero.
## Reproduction Code
colab link: [https://colab.re... | true |
3,037,173,341 | [nativert] move intrusive list to c10/util | dolpm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 13 | CONTRIBUTOR | Summary:
nativert RFC: https://github.com/zhxchen17/rfcs/blob/master/RFC-0043-torch-native-runtime.md
To land the runtime into PyTorch core, we will gradually land logical parts of the code into the Github issue and get each piece properly reviewed.
This diff moves intrusive list to c10/util
Test Plan: CI
Different... | true |
3,037,152,263 | Handle less functions than number of segments | JacobHelwig | open | [
"triaged",
"open source",
"release notes: autograd"
] | 9 | NONE | Fixes #152752
| true |
3,037,151,754 | Checkpoint sequential doesn't raise clear error when segments is greater than number of functions | JacobHelwig | open | [
"module: activation checkpointing",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
When incorrectly specifying segments to be greater than number of functions, the error message is not clear:
```
import torch
print(torch.__version__)
from torch.utils.checkpoint import checkpoint_sequential
lin = torch.nn.Linear(10, 10)
torch.nn.init.zeros_(lin.weight)
torch.nn.init.zeros_(l... | true |
3,037,106,704 | Implement util function compute_global_tensor_shape for 1D device mesh | dharakk | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152166
* __->__ #152751
### Summary
Recreating #151990 to mitigate easyCLA failure
compute_global_tensor_shape util function takes in local tensor shape, device mesh
and placements. We all gather the shapes from the shards and ... | true |
3,037,070,633 | Error on padding 0-sized tensors | roman-openai | open | [
"triaged",
"actionable",
"module: python frontend",
"module: edge cases"
] | 1 | NONE | ### 🐛 Describe the bug
```python
from torch.nn import functional
x = torch.ones((0, 1))
y = functional.pad(x, [1, 1, 0, 0])
```
raises
```python
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In[517], line 3
... | true |
3,037,034,349 | wip | bobrenjc93 | closed | [
"release notes: fx",
"fx",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152749
* #152670
* #152601
* #152597
* #152596
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,037,027,389 | Conditionally support experimental filesystem include in jit_opt_limit | aa6moham | open | [
"oncall: jit",
"fb-exported",
"ciflow/trunk",
"release notes: jit"
] | 11 | NONE | Summary: some build modes rely on GCC toolchains older than 8.1 (version where the official std::filesystem library was integrated into the STL library) so to support these older build modes (i.e. arvr/mode/embedded/linux/clang-aarch64-release) lets have a conditional on when to include the experimental filesystem libr... | true |
3,037,006,558 | torch.compile causes stride mismatch in SDPA with non-contiguous query in torch 2.7 | felix-lyx | open | [
"high priority",
"triaged",
"module: regression",
"oncall: pt2"
] | 0 | NONE | ### 🐛 Describe the bug
In PyTorch 2.7, when running compiled attention block with non-contiguous query input to `F.scaled_dot_product_attention` on CUDA, I got a stride mismatch error. The default mode for `torch.compile` is used. Non-contiguous query comes from transpose sequence and head dimensions, which should be... | true |
3,037,003,894 | [FSDP2] fully_shard(mesh=(shard, shard)) for intra and inter node all-gathers | weifengpy | open | [
"oncall: distributed",
"triaged"
] | 3 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
current stauts: `fully_shard(mesh=(shard))` do intra/inter node all-gather together by calling `torch.distributed.all_gather_into_tensor` once
what if we all-gather into 2 stages: do inter-node AG first, then intra-node AG
for recommendation workload, we can have following AG... | true |
3,037,002,135 | [CUDA][cuDNN] Fix handling of `CPU` side input and target length tensors in `CTCLoss` | eqy | closed | [
"module: cudnn",
"module: cuda",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing"
] | 3 | COLLABORATOR | https://github.com/pytorch/pytorch/pull/128271 migrated to cuDNN V8 CTCLoss which expects input and target length tensors to be on `CUDA` rather than `CPU` without adding the logic to account for the edge case of them being on `CPU`
see also #152421
cc @csarofeen @ptrblck @xwang233 @msaroufim @jerryzh168 | true |
3,037,001,982 | Ensure mxfp8 scaled_mm works w/ max-autotune | drisspg | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152665
* __->__ #152744
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,036,995,932 | [MPS] Migrate `div` to Metal | malfet | closed | [
"Merged",
"topic: not user facing",
"release notes: mps",
"ciflow/mps",
"keep-going"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152758
* __->__ #152743
TODOs:
- Verify accuracy of `metal::dot` vs `x.x*x.x + y.y*y.y` | true |
3,036,993,246 | [export][cond] support merging constant ints as unbacked symint | ydwu4 | open | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"release notes: export"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152742
@pianpwk points out that this will be helpful to address several data dependent issues in huggingface [models](https://github.com/huggingface/diffusers/blob/e23705e5577387872dd55ebf6db81bd59df928f1/src/diffusers/schedulers/... | true |
3,036,992,230 | [dynamo] Support `delattr` on result of `torch.compile(module)` | StrongerXi | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152741
* #152740
This is essentially a follow-up on #122098, where we added support of
`getattr` and `setattr` on result of `torch.compile(module)`, but didn't
add support for `delattr`.
Fixes #150711.
cc @voznesenskym @penguinwu @... | true |
3,036,992,201 | [dynamo] Avoid running `torch.nn.Module.__call__` twice under `torch.compile(mod)` | StrongerXi | closed | [
"Merged",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152741
* __->__ #152740
When we do `torch.compile(mod)`, we eventually end up returning a new
module instance, whose `forward` method is the result of
`torch.compile(mod.__call__)`, meaning it already captures all the extra
logic (e.g., hoo... | true |
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