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 |
|---|---|---|---|---|---|---|---|---|
2,913,029,543 | pin_memory() function doesn't work when it is called before lazy device initalization | BartlomiejStemborowski | closed | [] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
When a **pin_memory()** is called on a tensor, before the device is initialized, then the **is_pinned()** always return false. I believe this was broken by a #145752 PR and to be more precise by not calling lazyInitDevice in **_pin_memory** function.
Reproduction:
```
import torch
ifm = torch.t... | true |
2,912,993,241 | Add AOTI shim for _weight_int4pack_mm_cpu_tensor | Xia-Weiwen | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"intel",
"module: inductor",
"ciflow/inductor"
] | 11 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149031
**Summary**
Previous implementation of shim did not align with the design and it was removed by https://github.com/pytorch/pytorch/pull/148907
This PR adds it back in the files of MKLDNN backend and re-enable the CPP wrappe... | true |
2,912,720,548 | [ca] fix lazily compiled aot bwd | xmfan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 6 | MEMBER | FIXES https://github.com/pytorch/pytorch/issues/137372
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149014
* #149064
* #148801
* __->__ #149030
* #148799
sometimes, the aot bwd is lowered lazily. so the bw_module we saved in CompiledFunction._lazy_backward_info hasn't gone through... | true |
2,912,698,379 | reshard_after_forward does not work as expected in FSDP2 | caiqi | closed | [
"oncall: distributed",
"module: fsdp"
] | 3 | NONE | ### 🐛 Describe the bug
@awgu When enabling the reshard_after_forward flag, parameters appear to remain unsharded even after the forward pass completes. While this works as expected for simple networks, the text encoder module from HuggingFace Transformers exhibits a memory increase after forward propagation even wit... | true |
2,912,631,085 | [Intel gpu] always set deterministic for xpu accuracy test | jianyizh | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"ciflow/xpu",
"release notes: xpu"
] | 19 | CONTRIBUTOR | On Intel Max 1550, models like Super_SloMo can actually pass accuracy test after set deterministic, because we do not use atomic in upsampling bilinear backward in some cases when running on XPU. Furthermore, I guess the only reason not to set deterministic on these models is just avoiding errors. We should use warn_on... | true |
2,912,619,830 | [Inductor][Optimus] split cat aten pass | mengluy0125 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 9 | CONTRIBUTOR | Summary:
We add the aten pattern to optimize big cat node with arbitrary order of inputs to support APS jobs
context: https://docs.google.com/document/d/1G2qFcQu1K7VXbz2uPe0CS2aBirnwtwI_B8lxmlBlAPQ/edit?tab=t.0
Test Plan:
### how to enable
Add the following patterns to the post grad
```
post_grad_fusion_optio... | true |
2,912,610,253 | Add `__all__` for `torch.utils.dlpack` | ringohoffman | closed | [
"triaged",
"open source",
"Merged",
"module: dlpack",
"ciflow/trunk",
"release notes: python_frontend",
"topic: not user facing"
] | 14 | CONTRIBUTOR | Fixes the issue:
```python
torch.utils.dlpack.to_dlpack(tensor) # "to_dlpack" is not exported from module "torch.utils.dlpack" Pylance[reportPrivateImportUsage](https://github.com/microsoft/pyright/blob/main/docs/configuration.md#reportPrivateImportUsage)
```
the docs for `torch.utils.dlpack`: https://pytorch.... | true |
2,912,601,118 | [inductor] Fix profiler tests with latest Triton | jansel | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/rocm",
"ciflow/inductor-rocm"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149025
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,912,538,471 | DISABLED test_wrap_kwarg_only_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 5 | NONE | Platforms: linux, mac, macos
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_wrap_kwarg_only_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38598241... | true |
2,912,492,523 | [Inductor UT] Enable PYTORCH_TESTING_DEVICE_ONLY_FOR test case filter for test_torchinductor.py | etaf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149023
The environ var PYTORCH_TESTING_DEVICE_ONLY_FOR controls the devices
in get_desired_device_type_test_bases, so we add RUN_CPU and RUN_GPU to
make sure cases are only enabled for devices specified for PYTORCH_TESTING_DEVICE_ONL... | true |
2,912,474,255 | Support broadcast for nested tensors | shadow150519 | closed | [
"triaged",
"module: nestedtensor"
] | 2 | NONE | ### 🚀 The feature, motivation and pitch
When working with variable-length sequence batches using NestedTensor, there is a common need to perform element-wise operations (e.g., scaling, weighting) where each sequence in the batch requires a unique tensor operation specific to that sequence. However, the current implem... | true |
2,912,401,282 | [MPSInductor] Fix `argmin`/`argmax` long reductions | malfet | closed | [
"Merged",
"topic: bug fixes",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149021
* #149020
* #149004
By adding an additional indexes array for aggregates and populating it when performing partial reductions.
And with that I can finally `torch.compile` TinyStories and get 600+ tokens/sec vs <200 on ... | true |
2,912,401,222 | [MPSInductor][EZ] Fix argmin/max signatures | malfet | closed | [
"topic: bug fixes",
"release notes: mps"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149021
* __->__ #149020
* #149004
threadgroup_argmin used to return input type, which is wrong, it should have returned `int` or `long`
Change signatures of both thredgroup_argmin and threadgroup_argmax to return int, as group size is smal... | true |
2,912,387,552 | Avoid oneDNN primitives when GradMode is enabled on avx2_vnni_2 | CaoE | closed | [
"module: cpu",
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Fixes #148861.
oneDNN only supports bf16/f16 forward on the platform with avx2_vnni_2 by now. Add an additional check to avoid oneDNN primitive when GradMode is enabled on avx2_vnni_2.
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,912,349,091 | Add `nn.Bilinear` param validation | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: nn"
] | 10 | CONTRIBUTOR | Fixes #103425
## Changes
- Add doc description size value `must be > 0`
- Add validation for `in1_features` param
Currently, only `in1_features` will cause runtime error, if add checks for `in2_features` and `out_features` as well, might be kind of BC breaking.
```python
import torch
from torch import nn... | true |
2,912,310,209 | [MPS] Enable angle and atan2 for `torch.long` | malfet | closed | [
"Merged",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | This check was added by https://github.com/pytorch/pytorch/pull/85817, that introduced no unit-tests and its content seems to be totally unrelated to title/subject of that PR. Anyway, right now it seems to be working fine on MacOS-13+
| true |
2,912,263,450 | DISABLED test_var_mean_tile_reduction_True_dynamic_shapes_cuda (__main__.DynamicShapesGPUTests) | pytorch-bot[bot] | open | [
"module: rocm",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | Platforms: rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_var_mean_tile_reduction_True_dynamic_shapes_cuda&suite=DynamicShapesGPUTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38592796229).
... | true |
2,912,182,725 | [cutlass backend] try make cutlass backend benchmark more robust | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149015
Differential Revision: [D71006269](https://our.internmc.facebook.com/intern/diff/D71006269/)
I want to make sure the benchmark even if failed on some experiment can still print most of the results.
```
Experiment grou... | true |
2,912,180,129 | [ca] don't inline accumulate grad op | xmfan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 3 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149229
* __->__ #149014
* #149064
we use dummy tensors in our initial trace, so we should never inline. the subclass dispatch might not support the dummy tensor, e.g. DTensor accumulate grad will check that both param and grad are DTenso... | true |
2,912,170,299 | Unexpected out-of-boundary behavior in `grid_sample` | turtleizzy | open | [
"module: nn",
"triaged",
"module: numpy",
"module: edge cases"
] | 3 | NONE | ### 🐛 Describe the bug
`grid_sample` should return padding value (0) when grid coordinates are outside `[-1, 1]`, but it does not.
I spotted this problem when I couldn't replicate the result of `grid_sample` with other libraries like `scipy.ndimage.map_coordinates` and `itk.DisplacementFieldTransform`. I experimente... | true |
2,912,143,601 | [ez] Flush trymerge print statements | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Logs of trymerge don't match up with timestamps, ex
https://github.com/pytorch/pytorch/actions/runs/13766246347/job/38493307591
Ex:
```
2025-03-10T14:20:41.4899509Z Attempting merge of https://github.com/pytorch/pytorch/pull/148648 (0.003460856278737386 minutes elapsed)
...
2025-03-10T14:20:41.4907867Z Merge of h... | true |
2,912,109,914 | Fix issue #149006: Added docstring for backward() | Jason1ien | open | [
"triaged",
"open source",
"topic: not user facing"
] | 3 | NONE | Added a clear docstring for the backward() function to enhance readability of the code.
Fixes #149006 | true |
2,912,108,093 | [XFORMERS] torch._dynamo.exc.Unsupported | bhack | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
exporting/compiling Meta research xformers `memory_effiecient_attention` has an issue with dispatch
https://github.com/facebookresearch/xformers/blob/52f96c05723e9b79c88f25a4c406816ef2348a10/xformers/ops/fmha/dispatch.py#L70
### Error logs
```python
torch._dynamo.exc.Unsupported: SKIPPED INL... | true |
2,912,105,542 | [cutlass backend] switch layout for cutlass backend benchmark | henrylhtsang | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149009
```
python benchmarks/inductor_backends/cutlass.py
```
logs:
```
Experiment group: mm (1024x1024, 1024x1024) torch.float16
+-----------------------+--------------------+----------------------+---------------------+
... | true |
2,912,087,583 | [AOTI][Debug logger] Min value: Error: "min_all_cuda" not implemented for 'Float8_e4m3fn' | henrylhtsang | open | [
"triaged",
"module: float8",
"module: aotinductor"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Problem is with AOTI intermediate debug logger with FP8.
repro:
```
import torch
import torch._inductor.config as config
config.aot_inductor.debug_intermediate_value_printer = "2"
config.aot_inductor.filtered_kernel_names = "triton_poi_fused__to_copy_add_0"
class Model(torch.nn.Module):
... | true |
2,912,076,400 | [AOTI][debug logger] small fix for intermediate value debugger for jit when arg is not tensor | henrylhtsang | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149007
repro:
```
import torch
import torch._inductor.config as config
config.aot_inductor.debug_intermediate_value_printer = "2"
config.aot_inductor.filtered_kernel_names = "triton_poi_fused__to_copy_add_0"
class Mode... | true |
2,912,059,086 | Missing Additional documentation in autograd.py | Jason1ien | closed | [
"module: docs",
"triaged",
"module: library",
"oncall: pt2",
"module: pt2-dispatcher"
] | 3 | NONE | Some of the functions within autograd.py are missing some docstrings.
Specifically, the backward() function is missing a docstring.
Below is the link to the file:
https://github.com/pytorch/pytorch/blob/main/torch/_library/autograd.py
My systems specs:
Windows 11 Home
Intel 11th Gen Core i7-11800H @ 2.30GHz
Nvidia ... | true |
2,912,053,466 | flex_attention without CUDA | jjh42 | closed | [] | 1 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Flex attention is great. But if a model is implement with flex attention it can only run on a CUDA device.
This (baby step) proposal is to implement a pure python function
flex_attention.create_full_mask()
which will accept the same parameters as create_block_mask but return a... | true |
2,912,043,919 | [MPSInductor] Fix `min`/`max` reductions over large dims | malfet | closed | [
"Merged",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149021
* #149020
* __->__ #149004
Simple followup after sum/prod
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauha... | true |
2,912,017,990 | [test] bigger runnner | clee2000 | open | [
"ciflow/trunk",
"topic: not user facing"
] | 1 | CONTRIBUTOR | Now that I actually use the new version of the calculate docker image action, I feel like I should have done it differently... | true |
2,912,014,737 | [inductor] nan_asserts doesn't work for FP8, "RuntimeError: "isinf" not implemented for 'Float8_e4m3fn'" | henrylhtsang | open | [
"triaged",
"module: inductor",
"module: float8"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
repro:
```
import torch
import torch._inductor.config as config
config.nan_asserts = True
class Model(torch.nn.Module):
def forward(self, x):
return x.half() + 1
model = Model().cuda()
x = torch.randn(10).cuda().to(torch.float8_e4m3fn)
_ = torch.compile(model, fullgraph=True)(x)... | true |
2,912,012,314 | Explicitly set use-ephemeral runners for windows nightly cpu test jobs | atalman | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | This PR migrated windows builds to use ephemeral runners: https://github.com/pytorch/pytorch/pull/134463 however missed test jobs.
Explicitly set use-ephemeral runners for windows nightly cpu tests.
Please note we should be using already ephemeral runners for these after: https://github.com/pytorch/test-infra/pull/... | true |
2,911,947,066 | DISABLED test_wrap_kwarg_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 5 | NONE | Platforms: linux, mac, macos
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_wrap_kwarg_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38582441675).... | true |
2,911,921,877 | test diff | c00w | closed | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148999
Summary:
Test Plan:
Reviewers:
Subscribers:
Tasks:
Tags: | true |
2,911,916,127 | Denote a table of type conversions through StableIValue | janeyx99 | closed | [
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148998
| true |
2,911,911,110 | [dynamo][invoke_subgraph] Faster aliasing checks | anijain2305 | closed | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148997
* #148953
* #149072
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,911,909,996 | [codemod][lowrisk] Fix deprecated use of 0/NULL in caffe2/aten/src/ATen/native/quantized/cpu/qnnpack/src/fc-unpack.cc + 1 | r-barnes | closed | [
"module: cpu",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: quantization",
"release notes: cpp",
"topic: improvements",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Summary:
`nullptr` is typesafe. `0` and `NULL` are not. In the future, only `nullptr` will be allowed.
This diff helps us embrace the future _now_ in service of enabling `-Wzero-as-null-pointer-constant`.
Test Plan: Sandcastle
Reviewed By: dtolnay
Differential Revision: D70939306
cc @jgong5 @mingfeima @Xiaobing... | true |
2,911,887,859 | [test] for https://github.com/pytorch/pytorch/pull/147994/files | clee2000 | closed | [
"topic: not user facing",
"ciflow/xpu"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
2,911,885,905 | [PGNCCL] Stash tensors for reduce_scatter_v and all_gather_v | kwen2501 | closed | [
"oncall: distributed",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148994
https://github.com/pytorch/pytorch/pull/148590 removed `record_stream`. Since previous `AVOID_RECORD` flag does not cover `reduce_scatter_v` and `all_gather_v` which are in coalescing form, these two ops were missed. Causin... | true |
2,911,871,875 | skip torchbind in cosntant folding | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"module: aotinductor"
] | 5 | CONTRIBUTOR | Summary:
Do not fold torchbind objects in constant folding
Any operation on these torchbind objects can have arbitrary side effects, so we can't effectively constant fold anything torchbind-obj-related anyway.
Test Plan:
```
buck run fbcode//mode/dev-nosan //caffe2/test/inductor:torchbind -- -r aot_compile_constant_f... | true |
2,911,832,517 | [TD] test_cpp_extensions_aot_ninja corresponds to things in test/cpp_extensions | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Manually map test_cpp_extensions_aot_ninja to files in test/cpp_extensions since test_cpp_extensions_aot_ninja isn't an actual file you can edit, but a wrapper for files in test/cpp_extensions.
Idk if this is a good idea, feels very manual. Maybe it would be better to classify this the same as any other TD failure ... | true |
2,911,827,358 | Fix score_mod.py dynamic max autotune | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148991
python benchmarks/transformer/score_mod.py --dynamic --max-autotune
previously would crash with
```
"/home/bobren/local/a/pytorch/torch/_inductor/select_algorithm.py", line 2306, in key_of
node.get_device().type,
```
b... | true |
2,911,825,074 | Update VS references in README.md | botmethere | closed | [
"topic: not user facing"
] | 4 | NONE | Fixes #ISSUE_NUMBER
| true |
2,911,803,153 | [CI] Update crossvit_9_240 as pass | desertfire | 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):
* __->__ #148989
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,911,799,892 | second derivative of scaled_dot_product_attention does not work for nested tensors | mahyarkoy | closed | [
"module: autograd",
"triaged",
"module: nestedtensor",
"actionable"
] | 2 | NONE | ### 🐛 Describe the bug
Trying to compute the gradient of scaled_do_product_attention of nested tensor using create_graph=True fails, the code below recreates the issue:
```python
import torch
import torch.nn.functional as F
t1 = torch.arange(20).float().reshape(5,4)
n1 = torch.nested.as_nested_tensor([t1[:2], t1[2:... | true |
2,911,645,939 | test/dynamo/test_utils: Fix one broken test on different python versions | c00w | 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):
* __->__ #148987
We correctly handed different python version in the explicit ir_nodes test, but
didn't handle it in the dynamo_timed test. Just explicitly deleting the fields
there so the dynamo_timed test passes on all python versions.
(I n... | true |
2,911,629,444 | [AMD] Various fixes for mem efficient attention on CK backend | xw285cornell | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Summary: Decouple aotriton vs. ck for mem efficient attention. Also fixed HW check.
Reviewed By: henryhu6
Differential Revision: D70872677
| true |
2,911,603,753 | security test for reopened PR | hashupdatebot | closed | [
"open source",
"topic: not user facing"
] | 4 | NONE | Fixes #ISSUE_NUMBER
| true |
2,911,590,841 | [Sync file] the new file is not sync properly between pytorch/pytorch and pytorch/benchmark | yangw-dev | open | [
"oncall: releng",
"triaged"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
the timm_model.yml file created in pytorch/pytorch PR does not sync in pytorch/benchmark
## Issue Details
- pr submitted in pytorch:https://github.com/pytorch/pytorch/commit/e02c038a237483e70fa3541b0ade5d0d1c13165c
- the sync pr (by robot) in pytorch/benchmark (missing the new yaml file)
https... | true |
2,911,536,414 | inference_mode Tensors do not always need to be guarded on | zou3519 | open | [
"triaged",
"vllm-compile",
"dynamo-triage-jan2025"
] | 0 | CONTRIBUTOR | the following triggers a recompile
```
with torch.inference_mode():
x = torch.randn(3)
y = torch.randn(3)
@torch.compile(backend="eager", fullgraph=True)
def f(x):
return x.sin()
f(x)
f(y)
```
We saw this in vLLM | true |
2,911,516,646 | [ROCm][TunableOp] Unit test for TunableOp BLAS logging. | naromero77amd | closed | [
"module: rocm",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 4 | COLLABORATOR | Add unit test for new TunableOp BLAS logging feature.
Requires this PR to be merged in first: https://github.com/pytorch/pytorch/pull/148979
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang | true |
2,911,499,374 | [Inductor] Record Triton’s Base32 Cache Key in .best_config for Debugging | fulvius31 | open | [
"triaged",
"open source",
"Merged",
"Reverted",
"topic: not user facing",
"module: inductor",
"ci-no-td"
] | 42 | CONTRIBUTOR | This is a follow-up PR of the reverted one https://github.com/pytorch/pytorch/pull/147019 :
Modified TorchInductor’s autotuning flow so that each best_config JSON file also includes the Triton “base32” (or base64) cache key.
Motivation
Debugging & Analysis: With this change, we can quickly identify which compi... | true |
2,911,467,641 | torch.export.export used to work with scan in 1/2025 | xadupre | closed | [
"oncall: pt2",
"oncall: export"
] | 5 | COLLABORATOR | ### 🐛 Describe the bug
The following example used to work in January 2025. Now, it says ``torch._dynamo.exc.InternalTorchDynamoError: AttributeError: 'UserFunctionVariable' object has no attribute 'keywords'``.
```python
import scipy.spatial.distance as spd
import torch
class ModuleWithControlFlowLoop(torch.nn.Mod... | true |
2,911,464,558 | [ROCm][TunableOp] Fix TunableOp BLAS logging for online tuning case. | naromero77amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 3 | COLLABORATOR | In a previous PR https://github.com/pytorch/pytorch/pull/147034, there was a bad merge at the last minute.
BLAS logging works for offline tuning, but does not currently work for online tuning.
This PR fixes BLAS logging for online tuning.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dlleh... | true |
2,911,456,802 | [ez] include config as part of __all__ in torch.compiler | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148991
* __->__ #148978
Right now we are susceptive to a race condition where if the torch.compiler.config is not implicitly import via dynamo/builder.py, we will throw an error when trying to set compiler configs. This fixes it by includi... | true |
2,911,373,550 | module.cuda() doesn't work under FakeTensorMode | bdhirsh | open | [
"module: nn",
"triaged",
"oncall: pt2",
"module: fakeTensor",
"module: pt2-dispatcher"
] | 5 | CONTRIBUTOR | repro:
```
import torch
from torch._subclasses import FakeTensorMode
mode = FakeTensorMode()
with mode:
m = torch.nn.Linear(16, 16).cuda()
print(m.weight.device)
```
cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki @chauhang @penguinwu @eellison @zou3519 | true |
2,911,373,064 | `dist.barrier()` fails with TORCH_DISTRIBUTED_DEBUG=DETAIL and after dist.send/dist.recv calls | slitvinov | open | [
"oncall: distributed",
"triaged"
] | 3 | NONE | This program
```sh
$ cat bug.py
import torch
import torch.distributed as dist
import torch.distributed.elastic.multiprocessing.errors
@dist.elastic.multiprocessing.errors.record
def main():
dist.init_process_group()
rank = dist.get_rank()
size = dist.get_world_size()
x = torch.tensor(0)
if rank =... | true |
2,911,346,773 | [MPSInductor] Fix large prod and sum reductions | malfet | closed | [
"Merged",
"topic: improvements",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149004
* __->__ #148975
After this change, if reduction dimension is larger than `max_threadgroup_size`, emit a `for` loop from `codegen_iteration_ranges_entry` and wrap it up in `codegen_body()`
I.e. after this changes following command... | true |
2,911,285,563 | Fix DCP link | H-Huang | closed | [
"Merged",
"ciflow/trunk",
"topic: docs",
"topic: not user facing"
] | 3 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148974
| true |
2,911,209,094 | ConvTranspose1d on MKLDNN with BF32 yields wrong results on Intel Sapphire Rapids CPUs | Flamefire | closed | [
"module: mkldnn",
"module: intel"
] | 6 | COLLABORATOR | ### 🐛 Describe the bug
I see test failures in `test_conv_deconv_*d_lower_precision_cpu_bfloat16` on systems with Intel Sapphire Rapids. They are consistent with the same diff so fully reproducible.
I reduced the test to a minimal example:
```
import copy
import torch
from torch.utils import mkldnn as mkldnn_utils
im... | true |
2,911,144,418 | [MPS] Make `torch.mps.compile_shader` public | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: improvements",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | It was a private method in 2.6, but nothing changes in its APIs for 2.7
and it will likely remain the same in 2.8, so time to remove underscore from its name
This allows one to author/invoke shaders directly from PyTorch, for example code below implements an increment by thread index:
```python
```python
... | true |
2,911,130,785 | [release] Move triton pin to latest triton release/3.3.x | atalman | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"ciflow/rocm",
"ciflow/inductor-rocm"
] | 3 | CONTRIBUTOR | This branch contains latest AMD cherry-picks:
https://github.com/triton-lang/triton/pull/6171
https://github.com/triton-lang/triton/pull/6165
cc @jeffdaily @jataylo @jithunnair-amd | true |
2,911,112,520 | ONNX export drops namespace qualifier for custom operation | borisfom | closed | [
"module: onnx",
"triaged",
"onnx-triaged",
"onnx-needs-info"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
Here, a repro modified from the example used on Pytorch doc page for custom ONNX ops.
I expect saved ONNX file to have com.microsoft::Gelu node - OnnxProgram seem to have the qualifier, but it's lost when file is saved:
```
import torch
import onnxscript
import onnx
class GeluModel(torch.nn.... | true |
2,911,100,657 | [MPSInductor] Prep for mutlistage reductions | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148975
* __->__ #148969
----
- Move reduction variable initialization from `loads` to `indexing_code`
- Move barriers from `codegen_kernel` to `reduction` and only use them for `any` reductions (as other reduction ops do barriers ... | true |
2,911,091,183 | Slow evaluation on Mac with custom-built library | matteosal | closed | [
"module: performance",
"triaged",
"module: macos",
"module: arm"
] | 4 | NONE | I have built libtorch on Mac (Apple Silicon) with these settings
```
`# GENERAL` \
-DCMAKE_INSTALL_PREFIX=$output_dir \
-DCMAKE_BUILD_TYPE=Release \
`# PYTORCH SPECIFIC` \
-DBUILD_PYTHON=OFF \
-DUSE_NUMPY=OFF \
-DUSE_DISTRIBUTED=OFF `# distributed computing tools` \
-DUSE_FBGEMM=OFF `# quantized operators` \
-DATEN_NO_... | true |
2,911,063,053 | [ROCm] Fix TORCH_CHECK for hdim 512 support added in AOTriton 0.9b | xinyazhang | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 5 | COLLABORATOR | Fixes #148850
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,911,032,106 | DISABLED test_parity__foreach_abs_fastpath_inplace_cuda_bfloat16 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 10 | 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_inplace_cuda_bfloat16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38551199174)... | true |
2,911,031,933 | DISABLED test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_bfloat16 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 7 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_bfloat16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytor... | true |
2,910,886,541 | Consistently use `testing.assert_close` in tests | Flamefire | closed | [
"oncall: distributed",
"oncall: jit",
"open source",
"release notes: quantization",
"topic: not user facing",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: distributed (checkpoint)"
] | 2 | COLLABORATOR | The error message for failing tests are much better.
The replacement was done using Search&Replace with a Regexp so should all be fine.
Edit: Looking around I'd say even `self.assertEqual` would work. Not sure when to use which
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p... | true |
2,910,830,810 | [BE]: Update CU128 cudnn to 9.8.0.87 | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing"
] | 9 | COLLABORATOR | Also cu12.6 is an on old CUDNN version, we may want to upgrade it for all the performance reasons as I don't see a manywheel linux reason to stay back on the old 9.5 release. I might split that into it's own PR. This one just updates CU126 to the latest and greatest. | true |
2,910,810,940 | [AOTI][experiment] Turn on freezing as default | desertfire | open | [
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148962
Summary:
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,910,437,241 | DISABLED test_wrap_kwarg_default_if_branch_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 4 | NONE | Platforms: linux, rocm, mac, macos
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_wrap_kwarg_default_if_branch_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/py... | true |
2,910,395,496 | Does torch compile affect results ? | christopher5106 | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | ### 🐛 Describe the bug
Taking the generic example from [Flux Dev](https://huggingface.co/black-forest-labs/FLUX.1-dev)
```python
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
prompt = "A cat hold... | true |
2,910,172,042 | Move token linter code into tools/linter/adaptors/_linter/ | rec | open | [
"open source",
"topic: not user facing",
"suppress-bc-linter"
] | 5 | COLLABORATOR | This is a pure refactoring - no executable code has changed.
This is preparatory to adding considerably more functionality to this small family of "token linters" (as I call them, because they tokenize Python programs and then use that to lint them).
I centralized the code that was previously hidden in the indivi... | true |
2,910,022,699 | Fixing the pytorch profiler not working with `with_stack` flag set | arjun-choudhry | closed | [
"open source"
] | 6 | NONE | Adding call to RecordCCall such that the PyCCall Events are inserted into the queue. This ensures that the profiling doesn't break with 'with_stack' flag set.
Fixes #136817 , #101632
| true |
2,909,837,222 | DISABLED test_graph_partition (__main__.TritonCodeGenTests) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 6 | NONE | Platforms: rocm, inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_graph_partition&suite=TritonCodeGenTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38540387818).
Over the past 3 hours, it ... | true |
2,909,507,213 | Support int step for nonfused optimizer | zeshengzong | open | [
"open source",
"release notes: foreach_frontend"
] | 1 | CONTRIBUTOR | Fixes #142378
| true |
2,909,506,697 | [scan] Flattened output of HOP scan | bohnstingl | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 4 | COLLABORATOR | This is required because downstream operations expect HOPs to return a flattened list of output elements.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames @ydwu4 | true |
2,909,436,016 | Aborted (core dumped) double free or corruption (out) | Cookiee235 | open | [
"triaged",
"module: linear algebra"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class DeterministicModel(torch.nn.Module):
def __init__(self):
super(DeterministicModel, self).__init__()
self.linear = torch.nn.Linear(10, 10)
self.linear.weight.data.fill_(1.0)
self.linear.bias.data.fill_(0.0)
def forward(self,... | true |
2,909,381,135 | [dynamo][invoke_subgraph] Input aliasing and mutation check in Dynamo | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150082
* #150090
* __->__ #148953
* #150036
* #149667
* #149087
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,909,347,602 | [Dynamo] index_fill_ raise an assertionError | zhejiangxiaomai | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 2 | NONE | ### 🐛 Describe the bug
```python
import torch
def index_fill_op(inputs, index):
fwd_result = inputs.index_fill_(0, index, 17)
return fwd_result
inputs = torch.randn([2, 2, 2, 2])
inputs = inputs.contiguous(memory_format=torch.channels_last)
index = torch.tensor([1], dtype=torch.long)
index_fill_compile = ... | true |
2,909,331,956 | DISABLED test_wrap_kwarg_default_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 5 | NONE | Platforms: linux, rocm, mac, macos
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_wrap_kwarg_default_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs... | true |
2,909,303,839 | [inductor] [fake tensor] `torch.conj` crashes when `add` original complex tensor | shaoyuyoung | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 6 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: eager can pass the check while inductor throws the error
**device backend**: both CPP and triton
**repro**
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch._inductor import config
config.fallback_random = True
torch.set_grad_enabled(False)
... | true |
2,909,191,202 | `torch.distributions.Categorical(logits=...).sample()` returns -9223372036854775808 on `MPS`. Works correctly on `CPU` backend. | nipunbatra | closed | [
"module: mps"
] | 2 | NONE | ### 🐛 Describe the bug
```python
import torch
device = 'cpu'
t = torch.tensor([-0.6194, 0.2150, 0.0741, -0.5155, -0.3574, 0.1880, 0.3493, 0.2933,
0.3222, 0.1351, -0.1676, 0.2195, -0.2661, -0.1681, 0.0102, -0.2942,
0.1377, -0.3102, 0.0231, -0.3813, -0.8353, -0.0413, -0.2836, -0.0108,
... | true |
2,909,104,733 | Enable misc-use-internal-linkage check and apply fixes | cyyever | closed | [
"module: cpu",
"open source",
"better-engineering",
"module: amp (automated mixed precision)",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"ciflow/xpu"
] | 10 | COLLABORATOR | Enables clang-tidy rule [`misc-use-internal-linkage`](https://clang.llvm.org/extra/clang-tidy/checks/misc/use-internal-linkage.html). This new check was introduced in Clang-Tidy 18 and is available due to recent update of Clang-Tidy 19.
The check marks functions and variables used only in the translation unit as st... | true |
2,909,094,437 | WIP heuristic choices part 2 | exclamaforte | open | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,909,036,188 | export deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B failed | FlintWangacc | open | [
"oncall: pt2",
"oncall: export"
] | 4 | NONE | ### 🐛 Describe the bug
export deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B failed
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from torch.export import export
# Load the model and tokenizer
model_name = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
model = AutoModelForCausalLM.from... | true |
2,909,029,007 | ROCm: Enable tf32 testing on test_nn | jagadish-amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"keep-going",
"ciflow/rocm",
"ciflow/rocm-mi300"
] | 6 | CONTRIBUTOR | Add tf32 support for ROCm tests.
test command: python test/test_nn.py -v
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,908,993,816 | DISABLED test_set_nccl_pg_timeout_backend0 (__main__.ProcessGroupNCCLGroupTest) | pytorch-bot[bot] | closed | [
"oncall: distributed",
"module: flaky-tests",
"skipped"
] | 2 | NONE | Platforms: linux, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_set_nccl_pg_timeout_backend0&suite=ProcessGroupNCCLGroupTest&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38526659704).
Over the ... | true |
2,908,993,689 | DISABLED test_layer_norm_bwd_req_grad (__main__.DistMathOpsTest) | pytorch-bot[bot] | closed | [
"oncall: distributed",
"module: flaky-tests",
"skipped"
] | 3 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_layer_norm_bwd_req_grad&suite=DistMathOpsTest&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38525949394).
Over the past 3 hours, it has ... | true |
2,908,932,339 | Remove test decorations on MacOS 12 | cyyever | closed | [
"triaged",
"open source",
"Merged",
"topic: not user facing",
"ciflow/mps"
] | 3 | COLLABORATOR | MacOS 12 may reach EOL, as from https://endoflife.date/macos | true |
2,908,907,623 | Remove outdated skipIfRocmVersionLessThan decorations | cyyever | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 3 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,908,892,516 | Remove outdated skipCUDAIfCudnnVersionLessThan decoration | cyyever | closed | [
"triaged",
"open source",
"Merged",
"release notes: nn",
"topic: not user facing"
] | 3 | COLLABORATOR | Test conditions for CUDNN 7 and 8 were removed because we have moved to CUDNN 9. | true |
2,908,886,311 | Whether the transposed tensor is contiguous affects the results of the subsequent Linear layer. | pikerbright | open | [
"needs reproduction",
"module: nn",
"triaged",
"module: intel"
] | 4 | NONE | ### 🐛 Describe the bug
I found that whether the transposed tensor is contiguous affects the results of the subsequent Linear layer. I want to know if it is a bug or not?
```
import torch
from torch import nn
x = torch.randn(3, 4).transpose(0, 1) # 非连续张量（转置后）
linear = nn.Linear(3, 2)
y1 = linear(x) ... | true |
2,908,830,771 | [triton 3.3] `AOTInductorTestABICompatibleGpu.test_triton_kernel_tma_descriptor_1d_dynamic_False_cuda` | davidberard98 | closed | [
"module: crash",
"oncall: pt2",
"module: inductor",
"upstream triton",
"oncall: export",
"module: aotinductor",
"module: user triton"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
1. Update triton to `release/3.3.x` https://github.com/triton-lang/triton/tree/release/3.3.x
2. run `python test/inductor/test_aot_inductor.py -vvv -k test_triton_kernel_tma_descriptor_1d_dynamic_False_cuda`
Possibly an easier repro is
```
TORCHINDUCTOR_CPP_WRAPPER=1 python test/inductor/test_... | true |
2,908,829,486 | [AOTInductor]Only support one model instance when use AOTIModelPackageLoader load aot model? | zzq96 | closed | [
"triaged",
"oncall: pt2",
"oncall: export",
"module: aotinductor"
] | 3 | NONE | when i use aoti model in cpp, i try to infer parallel by using multi threads and multi streams, like this:
```cpp
torch::inductor::AOTIModelPackageLoader loader("model.pt2");
torch::inductor::AOTIModelContainerRunner* runner = loader.get_runner();
for thread_id in threads:
// in different threads
auto outputs = r... | true |
2,908,792,044 | Split up cub-RadixSortPairs.cu to parallelize compilation | TovlyFB | closed | [
"fb-exported",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: cuda",
"ci-no-td",
"no-runner-experiments"
] | 31 | CONTRIBUTOR | Summary: `cub-RadixSortPairs.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 20 minutes to 6 minutes.
Differential Revision: D70539649
| true |
2,908,756,112 | DISABLED test_side_effect_local_list_append_no_graph_break_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 5 | NONE | Platforms: linux, rocm, slow, mac, macos
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_side_effect_local_list_append_no_graph_break_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https... | true |
2,908,756,109 | DISABLED test_fsdp_tp_integration (__main__.TestTPFSDPIntegration) | pytorch-bot[bot] | closed | [
"oncall: distributed",
"module: flaky-tests",
"skipped"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_fsdp_tp_integration&suite=TestTPFSDPIntegration&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/38521925944).
Over the past 3 hours, it ha... | true |
2,908,743,468 | [inductor] Fix create_specialize_impl error in latest Triton | jansel | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148933
```py
$ python test/inductor/test_triton_kernels.py KernelTests.test_triton_kernel_2d_autotune_grad_False_dynamic_True_backend_inductor_grid_type_1
WARNING:torch._dynamo:Encountered an exception in identify_mutated_tensors, as... | true |
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