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 |
|---|---|---|---|---|---|---|---|---|
2,908,701,098 | bootcamp task for DTensor | XilunWu | open | [
"oncall: distributed",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148932
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,908,685,839 | Enable lazy tests | cyyever | open | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,908,674,564 | [cond] don't trace fw and bw graph in autograd key | ydwu4 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 16 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148930
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,908,668,043 | [cutlass backend] Add addmm and bmm tests for AOTI | henrylhtsang | 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):
* __->__ #148929
Needs to do:
1. Expand addmm tests to cover all 4 shapes
2. Add dynamic shape support.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @... | true |
2,908,668,007 | [Codemod][AddExplicitStrictExportArg] caffe2/test/inductor | gmagogsfm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Differential Revision: D70908557
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,908,657,480 | default cudagraphable policy for custom op | BoyuanFeng | open | [
"triaged",
"module: cuda graphs",
"oncall: pt2"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Currently pytorch assumes custom op is cudagraphable. Sometime this is wrong (repro below). Since custom op details is opaque to compiler, there might be something cudagraph cannot support (e.g., cpu ops) and compiler cannot detect that. From correctness perspective, it might be good to `defaul... | true |
2,908,652,276 | Only create new tensors in `nn.Module.to_empty` if source tensor is not already on target device | ringohoffman | closed | [
"open source"
] | 2 | CONTRIBUTOR | Fixes #148843
Some `Module`s are only partially initialized on the meta-device, like with [`accelerate.init_empty_weights()`](https://huggingface.co/docs/accelerate/v0.11.0/en/big_modeling#accelerate.init_empty_weights)
to avoid needing to re-initialize non-persistent buffers that are destroyed by `nn.Module.to_e... | true |
2,908,648,115 | [modefile free][long tail] selectify fbcode/caffe2/defs.bzl | jordanzoo | closed | [
"fb-exported",
"Merged",
"topic: not user facing"
] | 12 | CONTRIBUTOR | Summary:
replace read_config with select
For more info, please refer to the [doc](https://docs.google.com/document/d/1e0Hvht8WEHhcRvlCAodq_R9xnAtKBrAhdyvxcAqQjCw/edit?tab=t.hl8j18gza0cv)
Test Plan: CI
Reviewed By: malfet
Differential Revision: D70267850
| true |
2,908,640,562 | [triton 3.3] Forward-fix mm template selection logic | davidberard98 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/rocm"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148924
Follow-up from https://github.com/pytorch/pytorch/pull/148662.
The logic from https://github.com/pytorch/pytorch/pull/148662 is incorrect; what we want is "choose the second template 'AMD-specific template' only if we're... | true |
2,908,628,503 | [dynamo][guards] Do not ID_MATCH on numpy tensors | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148923
Might help with https://github.com/pytorch/pytorch/issues/148535
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,908,604,878 | partitioner: treat inputs with static indices as free to save | bdhirsh | closed | [
"Merged",
"ciflow/trunk",
"release notes: composability",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Fixes https://github.com/pytorch/pytorch/issues/141881
internal xref: https://fb.workplace.com/groups/1075192433118967/posts/1538435030128036/?comment_id=1556782068293332
I tried to make a test case out of the code linked in that github issue. The setup + bad outcome today was as follows:
(1) you have a graph ... | true |
2,908,591,296 | fix cuDNN SDPA meta registration | eqy | closed | [
"module: cudnn",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"module: sdpa"
] | 6 | COLLABORATOR | Update `cuDNN SDPA` meta registration to matching memory layout behavior in: https://github.com/pytorch/pytorch/pull/138354
cc @csarofeen @ptrblck @xwang233 @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amja... | true |
2,908,590,506 | Rewrite cpp extension tests to not be crazy | janeyx99 | open | [
"module: cpp-extensions",
"module: tests",
"triaged",
"better-engineering"
] | 3 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Today, adding a test for a custom extension is painful because dependencies are weirdly tangled, different extensions want to test different things, and the prior attempt to consolidate all the building/installing into run_test.py is just confusing.
We also use this python set... | true |
2,908,587,920 | [testing only] Update torch.utils.checkpoint to stash and restore TLS state | soulitzer | open | [
"ciflow/trunk"
] | 5 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
2,908,569,293 | [DSD] Update the document to mention the limitation of set_optimizer_state_dict | fegin | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (checkpoint)"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148918
Summary:
Fixes https://github.com/pytorch/pytorch/issues/140898
cc @H-Huang @awgu @kwen2501 @wanchaol @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,908,532,329 | [dynamo] Remove L scoping for recompilation messages | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148917
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,908,517,027 | Print hostname for ROCm CI runners in GHA logs | jithunnair-amd | closed | [
"module: rocm",
"open source",
"topic: not user facing",
"ciflow/rocm",
"ciflow/rocm-mi300"
] | 2 | COLLABORATOR | Will help provide debug info for MI300 nodes when something goes wrong in the GHA run, since currently it only prints the ephemeral pod ID, which cannot be easily traced back to the node after-the-fact.
cc @jeffdaily @sunway513 @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,908,491,724 | fix typo | not-lain | closed | [
"module: docs",
"open source",
"ciflow/trunk",
"topic: not user facing"
] | 8 | NONE | Fixes #ISSUE_NUMBER
cc @svekars @sekyondaMeta @AlannaBurke | true |
2,908,491,638 | DISABLED test_nested_wrap_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: linux, mac, macos, rocm, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_nested_wrap_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/... | true |
2,908,446,043 | caffe2: gpu_cpp_library for :caffe2_gpu | get9 | open | [
"caffe2",
"fb-exported",
"topic: not user facing"
] | 4 | NONE | Test Plan:
#buildmore
CI
Reviewed By: christycylee
Differential Revision: D70892337
| true |
2,908,434,884 | Automate stable CUDA update and linter using min Python verison | atalman | closed | [
"Merged",
"topic: not user facing"
] | 6 | CONTRIBUTOR | 1. Fixes: https://github.com/pytorch/pytorch/issues/145571 . Cuda Stable is the same cuda version that is published to pypi, also used to set Metadata section in the rest of whl scripts and tag the docker releases with latest tag.
2. Updates min python version used in linter | true |
2,908,433,441 | [ROCm] testing: enable MEFF/FA unittests for gfx1100 | xinyazhang | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"rocm",
"ciflow/rocm"
] | 7 | COLLABORATOR | Include gfx1100, and optionally enable gfx1201/gfx950 according to env var TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,908,406,960 | log cudagraph skip reasons | BoyuanFeng | closed | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Add skip reasons to dynamo_compile so we can know popular skip reasons for cudagraph
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,908,359,787 | Skip distributed subprocess test internally as they don't work | albanD | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | Follow up from https://github.com/pytorch/pytorch/pull/146098
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,908,308,870 | Numpy v1 v2 compatibility | clee2000 | closed | [
"module: numpy"
] | 1 | CONTRIBUTOR | Whats the policy on numpy compatibility in pytorch? I see that requirements-ci.txt pins numpy==1 for <python3.13 and numpy==2 for py3.13, but later in CI numpy gets reinstalled as numpy==2.0.2 for most python versions. Is CI supposed to use v2 or v1? Does being compatible with v2 ensure compatibility with v1?
cc @mr... | true |
2,908,299,346 | [AOTI] Remove aoti_torch_cpu__weight_int4pack_mm_cpu_tensor | desertfire | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 19 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148907
Summary: shim.h is only meant for generic tensor util shim functions. We should switch to use the auto fallback generation, but it will need some extra care on the op schema.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Gu... | true |
2,908,290,089 | [Torchscript] Add a flag to use mangled names instead of demangled | RihamSelim | closed | [
"oncall: jit",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: jit"
] | 12 | CONTRIBUTOR | Summary: Optionally keep mangled names when expanding torchscript stacks
Test Plan:
```
buck2 build mode/opt //scripts/rihams/LearnPyTorch:torch_script_generate --show-full-output
/data/users/rihams/fbsource/buck-out/v2/gen/fbcode/0bd9d136228ad8a7/scripts/rihams/LearnPyTorch/__torch_script_generate__/torch_script_gen... | true |
2,908,231,257 | [ONNX] Create onnx_symbolic | justinchuby | closed | [
"module: onnx",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: new features"
] | 7 | COLLABORATOR | In the old exporter we allow users to define a symbolic() method to bypass JIT tracing for a block of logic. We can allow users to do similar things by creating symbolic ops at export.
This PR implements `torch.onnx.ops.symbolic` and `torch.onnx.ops.symbolic_multi_out` to allow users to create onnx nodes symbolicall... | true |
2,908,145,811 | [CI] Upgrade numpy? | clee2000 | closed | [
"release notes: releng"
] | 1 | CONTRIBUTOR | Gets rid of mention of py3.8, which is no longer supported
Upgrades the numpy version used in build when possible (numpy2.0.2 is the most recent version that supports py3.9)
As of right now, numpy2.2.3 is the most recent numpy version.
py3.13 already has numpy2.1.2 installed and 2.0.2 doesn't have a release for py... | true |
2,908,138,103 | [BE] Remove unused macro ENABLE_NCCL_P2P_SUPPORT | kwen2501 | open | [
"oncall: distributed",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148903
* #148900
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,908,132,670 | Remove Direct Arm Compute Libray (ACL) Integration for Quantized Matmuls: `qlinear`/`qlinear_dynamic` | fadara01 | open | [
"oncall: quantization",
"module: arm"
] | 1 | COLLABORATOR | PR https://github.com/pytorch/pytorch/pull/148585 (temporarily) introduced a direct ACL implementation for `qlinear` and `qlinear_dynamic` for AArch64 when `USE_MKLDNN_ACL` is set.
This direct ACL implementation is a lot faster than the existing implementations that utilized ACL through oneDNN (MKLDNN) due to the (curr... | true |
2,908,127,531 | DISABLED test_train_parity_multi_group_cpu_offload_eager (__main__.TestFullyShard1DTrainingCore) | pytorch-bot[bot] | open | [
"oncall: distributed",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2"
] | 3 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_train_parity_multi_group_cpu_offload_eager&suite=TestFullyShard1DTrainingCore&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/3849959669... | true |
2,908,113,128 | [RFC][BE] assume error checking is on by default (#141914) | kwen2501 | open | [
"oncall: distributed",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148903
* __->__ #148900
Summary:
Remove conditional MACRO `ENABLE_NCCL_ERROR_CHECKING` and assume that error checking is always on.
These checks were wrapped in a macro because older NCCL libraries didn't have the pre-requisite functions to... | true |
2,908,112,052 | [DRAFT] make reshape work for reshapeing 1dim unbacked non-contig to anything | laithsakka | open | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149266
* __->__ #148899
* #148893
* #148872
* #148742
* #148815
* #148809
* #148430
| true |
2,908,071,698 | [IR] adding option to enable storing namedtuple fields | felixsu2006 | open | [
"fb-exported",
"ciflow/inductor",
"release notes: export"
] | 3 | CONTRIBUTOR | Summary:
adding option to enable/disable this functionality
setting to True by default so shouldn't affect any existing use cases unless explicitly set to False
Test Plan: no functionality changes
Differential Revision: D70905747
| true |
2,908,065,282 | Enable experimentation with ephemeral runners on pull.yml | jeanschmidt | closed | [
"topic: not user facing"
] | 7 | CONTRIBUTOR | # TLDR
Adds `get-is-ephemeral` step to pull.yml workflow and enable the experimentation of `ephemeral` on `pull.yml` workflow.
The status of the experiment can be found in the [test-infra issue](https://github.com/pytorch/test-infra/issues/5132).
# What?
Enable experiment with ephemeral runners in the pull.... | true |
2,908,036,888 | [dynamo] fix bug where non-recursive disable modifies the original function | williamwen42 | closed | [
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"keep-going"
] | 7 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148896
Fixes https://github.com/pytorch/pytorch/issues/148787.
We fix this by:
- Wrapping the original function instead of directly modifying it
- When we detect that the previous frame is the non-recursive disable wrapper, the... | true |
2,908,029,449 | Remove 12.4 x86 builds and 12.6 sbsa builds from nightly | tinglvv | closed | [
"open source",
"Merged",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | https://github.com/pytorch/pytorch/issues/145570
redo https://github.com/pytorch/pytorch/pull/148625
cc @atalman @malfet @nWEIdia @ptrblck | true |
2,907,995,378 | Support uneven sharding for FSDP2 + TP | lw | closed | [
"oncall: distributed",
"release notes: distributed (fsdp)",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150393
* #150146
* __->__ #148894
| true |
2,907,993,177 | use statically known true instead of guard size oblivious in bmm and mm inductor decompositions . | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148893
this was discussed with @eellison and he recommended using statically_known_true here, the intuition is. We already have 0/1 specializations in place, if we reach those checks with dynamic shapes that are not already special... | true |
2,907,962,080 | Introduce TORCH_ABI_VERSION and a runtime aoti_torch_abi_version C shim ABI | janeyx99 | closed | [
"Merged",
"ciflow/trunk",
"release notes: cpp",
"ciflow/inductor",
"ci-no-td"
] | 5 | CONTRIBUTOR | Importable https://github.com/pytorch/pytorch/pull/148836
| true |
2,907,884,008 | Upgrading FlashAttention to V3 | drisspg | open | [
"triaged",
"module: sdpa"
] | 5 | CONTRIBUTOR | # Summary
We are currently building and utilizing FlashAttention2 for torch.nn.functional.scaled_dot_product_attention
Up until recently the files we build and our integration was very manual. We recently changed this and made FA a third_party/submodule: https://github.com/pytorch/pytorch/pull/146372
This makes it ... | true |
2,907,782,392 | Hook StaticCudaLauncher up to torch.compile (cold start) | jamesjwu | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 15 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149629
* #149442
* #149054
* __->__ #148890
This hooks up the previous PR to torch.compile. Will add a config flag to hide this behind in a bit, but for now it's useful for testing purposes to have it on by default.
Inductor will autom... | true |
2,907,697,033 | DISABLED test_make_closure_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"module: higher order operators",
"module: pt2-dispatcher"
] | 3 | NONE | Platforms: linux, mac, macos, rocm, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_make_closure_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/3... | true |
2,907,693,730 | Update RELEASE.md with latest changes to release process and release 2.7 information | atalman | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | 1. Update for Release 2.7 compatibility matrix
2. Remove mention of builder project, the scripts for release management were migrated to test-infra
| true |
2,907,582,092 | Vincent/rebase 2.5 | vincent-tr | closed | [
"oncall: distributed",
"oncall: jit",
"module: rocm",
"module: cpu",
"release notes: releng",
"fx",
"module: inductor",
"module: dynamo",
"release notes: distributed (checkpoint)"
] | 2 | NONE | Rebase `flexai/v2.5.0` from `upstream/release/2.5`
Refs: NOTICKET
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd @mi... | true |
2,907,351,246 | Unable to export model to ONNX with dynamo and dynamic batch size | Fredrik00 | closed | [
"module: onnx",
"triaged"
] | 4 | NONE | ### 🐛 Describe the bug
I have been trying to export PARSeq, a Transformer based scene text recognition model, to ONNX with torch.onnx.export and dynamo enabled. I have been successful in getting the model exported with a fixed batch size, but unfortunately not with dynamic shapes.
I have created an input tensor matc... | true |
2,907,250,810 | test_memory_profiler_viz failed on cudamallocasync | garfield1997 | open | [
"module: cuda",
"triaged",
"module: testing"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
step to reproduce the bug
```shell
# step 1
export PYTORCH_CUDA_ALLOC_CONF="backend:cudaMallocAsync"
# step 2 run test case from test_cuda.py
python test_cuda.py -k 'test_memory_profiler_viz'
```
output
```
FAIL: test_memory_profiler_viz (__main__.TestCudaMallocAsync)
--------------------------... | true |
2,907,206,658 | CrossEntropy with label smoothing does not apply the correct label smoothing | adrien-grl | closed | [] | 0 | NONE | ### 🐛 Describe the bug
The `label_smoothing` parameter of the `nn.CrossEntropyLoss` does not match the expected behavior. Instead, it seems that the label smoothing that is applied is half of the correct value.
Indeed, in the [original paper](https://arxiv.org/pdf/1512.00567) they specify that the loss is:
$$\mathca... | true |
2,907,187,294 | Pytorch2.7+ROCm6.3 is 34.55% slower than Pytorch2.6+ROCm6.2.4 | testbug5577 | closed | [
"module: performance",
"module: rocm",
"triaged"
] | 6 | NONE | The same hardware and software environment, only the versions of PyTorch+ROCm are different.
Use ComfyUI to run Hunyuan text to video：
ComfyUI：v0.3.24
ComfyUI plugin: teacache
49frames
480x960
20steps
CPU：i5-7500
GPU：AMD 7900XT 20GB
RAM：32GB
PyTorch2.6+ROCm6.2.4 Time taken: 348 seconds 14.7s/it
The VAE Decode Tile... | true |
2,907,029,068 | [Inductor][CPP] Fix expr issue in loop split | leslie-fang-intel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148882
**Summary**
Fix issue: https://github.com/pytorch/pytorch/issues/148058. In this case, there is an `indexing_expr` as an integer which doesn't have the method of `find`.
**Test Plan**
```
python -u -m pytest -s -v tes... | true |
2,906,788,379 | Update torch-xpu-ops commit pin | chunhuanMeng | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu"
] | 3 | CONTRIBUTOR | Update the torch-xpu-ops commit to [026b2c8c7c92a7b2cec5d26334006e3423251cc6](https://github.com/intel/torch-xpu-ops/commit/026b2c8c7c92a7b2cec5d26334006e3423251cc6), includes:
- Enable AOT for LNL
cc @gujinghui @EikanWang @fengyuan14 @guangyey | true |
2,906,681,453 | Refactor to use torch.accelerator.device_index instead of torch.cuda.device for generic device context manager | guangyey | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm",
"ciflow/xpu"
] | 12 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148880
* #148864
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,906,586,191 | setuptools pinning | ozanMSFT | closed | [
"module: windows",
"open source",
"Merged",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | Fixes #148877
---
On 9 March 2025, [setuptools](https://pypi.org/project/setuptools/#history) published a new version and it is causing an issue on `pytorch` with the following error:
```
AttributeError: module 'distutils' has no attribute '_msvccompiler'. Did you mean: 'ccompiler'?
```
Last known worki... | true |
2,906,577,125 | Add Half support for weight_norm on CPU | CaoE | closed | [
"module: cpu",
"open source",
"module: half",
"Merged",
"ciflow/trunk",
"release notes: nn",
"ciflow/inductor"
] | 10 | COLLABORATOR | Fixes #148867.
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,906,496,492 | setuptools error - Windows - 'distutils' has no attribute '_msvccompiler' | ozanMSFT | closed | [
"module: build",
"module: windows",
"triaged",
"module: regression"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
`setuptools` is updated on 9 March 2025. (last working version is `75.8.2`)
https://pypi.org/project/setuptools/#history
With this update, Windows nightly builds started fail with `AttributeError: module 'distutils' has no attribute '_msvccompiler'`
---
Currently `x64` builds are not affec... | true |
2,906,488,406 | Use device agnostic APIs and variable names for dtensor | amathewc | closed | [
"oncall: distributed",
"module: cpu",
"triaged",
"module: mkldnn",
"open source",
"module: amp (automated mixed precision)",
"NNC",
"release notes: quantization",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"release notes: distributed (checkpoint)",
"module: compiled auto... | 23 | CONTRIBUTOR | ## MOTIVATION
To generalize DTensor test cases for non-CUDA devices, we are replacing certain APIs with device-agnostic alternatives. Additionally, we are refactoring the code to improve modularity.
Please refer to this RFC as well: https://github.com/pytorch/rfcs/pull/66
## CHANGES
### common_dtensor.py
- Use... | true |
2,906,394,490 | Refactor `test/test_torch.py` by moving testcase to `test_indexing.py` | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"Reverted",
"topic: not user facing",
"ci-no-td"
] | 9 | CONTRIBUTOR | Fix `FIXME` in `test_torch.py` by moving test-cases to `test_indexing.py`
```python
# FIXME: move to test indexing
# FIXME: move to indexing test suite
```
- Move tests in `test/test_torch.py` to `test_indexing.py`
- Remove `FIXME` comments
## TestResult
```bash
pytest test/test_torch.py -k TestTorchDe... | true |
2,906,382,344 | `torch.device.__enter__` does not affect `get_default_device` despite taking precedence over `set_default_device` | ringohoffman | open | [
"triaged",
"module: python frontend"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Using a `torch.device` as a context manager takes precedence over `set_default_device`, but this isn't reflected by the return value of `get_default_device`.
```python
import torch
import torch.utils._device
torch.set_default_device("cuda:1")
with torch.device("cuda:0"):
print(f"get_defa... | true |
2,906,358,061 | Update slow tests | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/slow",
"ci-no-td"
] | 3 | COLLABORATOR | This PR is auto-generated weekly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/weekly.yml).
Update the list of slow tests. | true |
2,906,293,895 | convert guard_size_oblivious to runtime check in infer_size_impl | laithsakka | open | [
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152722
* __->__ #148872
its ok to check the requirement numel == newsize at runtime in case of unbacked instead of at compile time and assume that its true. | true |
2,906,283,113 | Make `torch._check` support bool tensor as `cond` param | zeshengzong | open | [
"triaged",
"open source",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Fixes #148349
## Test Result
```python
pytest test/test_torch.py -k test_check -vv
```
| true |
2,906,243,333 | DISABLED test_lift_tensors_with_shared_symbols_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: linux, mac, macos, rocm, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_lift_tensors_with_shared_symbols_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/py... | true |
2,906,200,092 | Optimize `MaxPool1d` param `ceil_mode` description | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 11 | CONTRIBUTOR | Fixes #148123
Add output shape formula based on `ceil_mode` value, according to
https://github.com/pytorch/pytorch/blob/00199acdb85a4355612bff28e1018b035e0e46b9/aten/src/ATen/native/Pool.h#L61-L75
## Test Result
### Before
![image](https://github.com/user-attachments/assets/0a175178-a104-4348-a14b-516e... | true |
2,906,148,635 | Optimize shard_dim_alltoall to use alltoall_single | wanchaol | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"ciflow/periodic",
"release notes: distributed (dtensor)"
] | 6 | COLLABORATOR | as titled, previously the shard_dim_alltoall uses `all_to_all`, which essentially could incur lots of copies if the tensor become non-contiguous during splits, and alltoall itself also incur copies
This PR uses alltoall_single instead, so that we could minimize tensor copies.
tested on all the shard dim change te... | true |
2,906,143,010 | FP16 of weight norm is slower than BF16 on CPU | jiqing-feng | closed | [
"module: nn",
"triaged"
] | 1 | NONE | ### 🐛 Describe the bug
To reproduce it.
CMD: `numactl -C 0-31 -m 0 python test.py`
```python
import time
import torch
weight_norm = torch.nn.utils.parametrizations.weight_norm
conv_layer = torch.nn.Conv1d(in_channels=192, out_channels=383, kernel_size=5, dilation=1, padding=2, dtype=torch.bfloat16)
in_layer = weig... | true |
2,906,066,198 | [Inductor] Core dumped due to invalid next size | Cookiee235 | open | [
"module: crash",
"oncall: pt2",
"oncall: cpu inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class TestModel(torch.nn.Module):
def __init__(self):
super(TestModel, self).__init__()
self.linear = torch.nn.Linear(10, 10)
def forward(self, x):
mean = torch.zeros(10, 10)
std = torch.ones(10, 10)
random_data = torch.n... | true |
2,906,017,307 | Create and send `full_tensor` on `ProcessGroup`-supported device in `_broadcast_tensors` | ringohoffman | closed | [
"oncall: distributed",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (checkpoint)"
] | 7 | CONTRIBUTOR | Fixes #138842
`device` is always the device of the `local_state_dict`, which may or may not be CPU, which is not supported by NCCL backend.
Instead, create broadcasted tensors on one of `pg._device_types` and then move the tensors back if `local_state_dict`'s `device` was not supported by the `ProcessGroup`.
c... | true |
2,905,997,322 | Add torch.accelerator.device_index as accelerator's device switch context | guangyey | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: python_frontend",
"topic: not user facing",
"ciflow/rocm",
"ciflow/xpu",
"module: accelerator"
] | 12 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148880
* __->__ #148864
# Motivation
We propose adding support for the Python with statement on `torch.accelerator.device_index` to enable device switching functionality. This enhancement would simplify writing device-agnostic code and pr... | true |
2,905,985,840 | [Doc] Update CMAKE_PREFIX_PATH for XPU windows README | Stonepia | closed | [
"module: docs",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: xpu"
] | 11 | CONTRIBUTOR | We found that the `pip install cmake` and `conda install cmake` has different behavior.
The reason is that the pip installed one doesn't find the corresponding libs under conda env. So we need to set the `CMAKE_PREFIX_PATH` for alignment.
cc @svekars @sekyondaMeta @AlannaBurke @gujinghui @EikanWang @fengyuan14 @guan... | true |
2,905,948,283 | [Inductor] Compiled model crashed when execute inference | Cookiee235 | open | [
"triaged",
"oncall: pt2"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class SimpleModel(torch.nn.Module):
def __init__(self):
super(SimpleModel, self).__init__()
self.linear = torch.nn.Linear(10, 10)
def forward(self, x):
x = self.linear(x)
eigvals = torch.linalg.eigvals(x)
eigvals_not = to... | true |
2,905,947,765 | [CPU]DNNL does not support bf16 backward on Lunar lake | gaopengff | closed | [
"triaged",
"module: mkldnn",
"module: regression",
"module: intel",
"bug"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
I have tested my ut on Intel Lunar lake cpu(Intel® Core™ Ultra Processors). It failed with error message: “**RuntimeError: DNNL does not support bf16/f16 backward on the platform with avx2_vnni_2**”. Here is the reproducer:
```python
import torch
x = torch.ones([2, 3, 8, 6], dtype=torch.float, ... | true |
2,905,932,644 | AttributeError: module 'torch.compiler' has no attribute 'save_cache_artifacts' | janak2 | closed | [
"triaged",
"oncall: pt2",
"compile-cache"
] | 4 | NONE | ### 🐛 Describe the bug
Documentation says you need pytorch > 2.4: https://pytorch.org/tutorials/recipes/torch_compile_caching_tutorial.html
I have tried with torch 2.6 but am getting the following error:
### Error logs
```
Traceback (most recent call last):
File "/pkg/modal/_runtime/container_io_manager.py", li... | true |
2,905,930,106 | [Inductor] Output mismatch shape after compilation | Cookiee235 | open | [
"triaged",
"oncall: pt2",
"module: pt2 accuracy"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class SimpleModel(torch.nn.Module):
def __init__(self):
super(SimpleModel, self).__init__()
self.conv = torch.nn.Conv2d(1, 3, kernel_size=3, stride=1, padding=1)
self.upsample = torch.nn.Upsample(scale_factor=2, mode='bilinear', align_corners... | true |
2,905,929,913 | RuntimeError: OffsetBasedRNGTracker instantiation requires the presence of CUDA/CUDA-like device | zqwenn | open | [
"oncall: distributed",
"triaged"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
This [PR](https://github.com/pytorch/pytorch/pull/147025) will cause a RuntimeError for third-party backends while using the torch.distributed.tensor._random.manual_seed function.
Here is the error stack.
```bash
Root Cause (first observed failure):
[0]:
time : 2025-03-10_09:33:40
hos... | true |
2,905,884,556 | [Flex Attention] support num_heads > 1 in block_mask | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"module: flex attention"
] | 4 | CONTRIBUTOR | Previously flex decoding errors when block mask has num_heads > 1. So users have to use num_heads=1, or explicitly mark `kernel_options={"FORCE_USE_FLEX_ATTENTION": True}`.
This PR fixes this issue. When not using grouped query attention (GQA, i.e., Hq == Hkv), we support block mask with num_heads = 1 and num_heads ... | true |
2,905,884,349 | [Inductor] RuntimeError: derivative for aten::heaviside is not implemented | Cookiee235 | closed | [
"triaged",
"oncall: pt2"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
### Reproducible script
```
import torch
class SimpleModel(torch.nn.Module):
def __init__(self):
super(SimpleModel, self).__init__()
self.linear = torch.nn.Linear(10, 10)
def forward(self, x):
x = self.linear(x)
x = torch.heaviside(x, torch.tensor([0.0... | true |
2,905,876,615 | Fix invalid format string in libfmt calls | cyyever | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"release notes: mps",
"ciflow/mps"
] | 8 | COLLABORATOR | Wrap shaderSource inside fmt::runtime because the format string is not a string literal and can't pass libfmt's compile time check in C++23 | true |
2,905,871,886 | Fix "invalid application of 'sizeof' to an incomplete type" | cyyever | closed | [
"open source",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 8 | COLLABORATOR | Fixes with C++23 and constexpr std::unique_ptr
| true |
2,905,815,888 | DISABLED test_comprehensive_nn_functional_conv_transpose3d_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 28 | NONE | Platforms: inductor, linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_nn_functional_conv_transpose3d_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytor... | true |
2,905,815,739 | DISABLED test_train_parity_multi_group_unshard_async_op (__main__.TestFullyShard1DTrainingCore) | pytorch-bot[bot] | closed | [
"oncall: distributed",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2"
] | 5 | NONE | Platforms: inductor, linux, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_train_parity_multi_group_unshard_async_op&suite=TestFullyShard1DTrainingCore&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch... | true |
2,905,815,685 | DISABLED test_capture_tracked_nested_dynamic_shapes (__main__.DynamicShapesHigherOrderOpTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: linux, mac, macos, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_capture_tracked_nested_dynamic_shapes&suite=DynamicShapesHigherOrderOpTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/ru... | true |
2,905,808,113 | [ROCm] AOTriton 0.9.2b RuntimeError Only Supports Head Dimension <=256 | Beinsezii | closed | [
"module: rocm",
"triaged",
"module: sdpa"
] | 4 | NONE | ### 🐛 Describe the bug
The latest pytorch nightly makes it impossible to run `scaled_dot_product_attention` on tensors with batch dim > 256 without manually disabling the efficient attention kernels, likely as a result of https://github.com/pytorch/pytorch/pull/148433 trying to enable 512 >= hdim > 256 support
```pyt... | true |
2,905,806,795 | fix dynamo ide | drisspg | 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):
* __->__ #148849
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,905,753,715 | [dynamo][guards] Dont guard on ephemeral numpy tensors | anijain2305 | closed | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"keep-going"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148917
* __->__ #148848
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,905,748,547 | Fix AttributeError for `_get_vc_env` with setuptools>=75.9.0 | sigvoid | open | [
"triaged",
"open source"
] | 7 | NONE | ```
File "E:\AI\ComfyUI_windows_portable\python_embeded\Lib\site-packages\torch\utils\cpp_extension.py", line 2172, in _get_vc_env
return _msvccompiler._get_vc_env(vc_arch)
^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: module 'distutils._msvccompiler' has no attribute '_get_vc_env'
```... | true |
2,905,741,079 | C++ support to print symbolic tensors as `Symbolic tensor: size=(...)` | grodranlorth | open | [
"triaged",
"open source",
"topic: not user facing"
] | 11 | NONE | Fixes https://github.com/pytorch/pytorch/issues/145491
| true |
2,905,734,501 | Unable to compile pad/unpad from Flash Attention 2 | conceptofmind | closed | [
"triaged",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 2 | NONE | ### 🐛 Describe the bug
Hello all,
I am attempting to compile a model that is unpadding and padding the input ids for an encoder with Flash Attention 2. The pad and unpad code can be found here: https://github.com/Dao-AILab/flash-attention/blob/main/flash_attn/bert_padding.py#L98
Example code:
```python
x, i... | true |
2,905,679,656 | [Export] fix automatically convert instances of _check(u>=0) to check_is_size() | SandishKumarHN | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 14 | CONTRIBUTOR | Fixes #148826
Understanding:
1. PyTorch should automatically convert instances of _check(u>=0) to check_is_size()
2. The export mechanism should suggest using check_is_size() instead of _check(u>=0) when applicable
Changes made:
1. Added a helper function to detect non-negative checks: is_non_negative_check
... | true |
2,905,654,595 | make `to_empty` a no-op if parameter/buffer already on `device` | ringohoffman | open | [
"module: nn",
"triaged",
"needs design"
] | 7 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
See also:
* https://github.com/huggingface/transformers/issues/34234#issuecomment-2429754244
When loading a model with non-persistent buffers on the meta device, the default behavior of [`accelerate.init_empty_weights()`](https://huggingface.co/docs/accelerate/v0.11.0/en/big_... | true |
2,905,569,419 | We should use max size instead of hint size when autotuning | bobrenjc93 | open | [
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | From x-ref https://fb.workplace.com/profile.php?id=61573598535425
@eellison
> At compile time (mm tuning), it will use the hint, aka first size. we should use the max size. Similarly, runtime will use max size. When the max size diverges from runtime I think we could just reuse the existing cpp_wrapper compile time t... | true |
2,905,517,776 | build pytorch2.3.0 cpu with mkldnn_acl 24.08 failed on aarch64 | Serenagirl | open | [
"module: build",
"triaged",
"module: mkldnn",
"module: third_party",
"module: arm"
] | 3 | NONE | I build acl24.08 with cmake .. -DCMAKE_BUILD_TYPE=Release -DARM_COMPUTE_OPENMP=1 -DARM_COMPUTE_WERROR=0 -DARM_COMPUTE_BUILD_EXAMPLES=0 -DARM_COMPUTE_BUILD_TESTING=0 -DCMAKE_INSTALL_PREFIX=/opt/acl cmake --build . --parallel 160
and build pytorch with python setup.py build --cmake-only
but failed
 | FabianSchuetze | closed | [
"module: onnx",
"triaged"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
The following fails for me:
```
import torch
import torchvision
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
y = torchvision.transforms.functional.resize(x, size=[1024, 1024])
return y
model = Model()
x = torch... | true |
2,905,398,382 | [MPS] Fix Wreorder-init-list | cyyever | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: mps",
"ciflow/mps"
] | 6 | COLLABORATOR | Fixes the following warning:
```
warning: ISO C++ requires field designators to be specified in declaration order; field 'value' will be initialized after field 'size' [-Wreorder-init-list]
662 | return {.value.cf = scalar.to<c... | true |
2,905,312,917 | [Inductor] Inconsistency predict results for the compiled models with the original model | Cookiee235 | closed | [] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
### After the compilation with the inductor, the compiled model outputs significantly different results (i.e., 0.05) from the original model. It seems to reveal a bug.
### The reproducible script
```python
import torch
class TestModel(torch.nn.Module):
def __init__(self):
super(T... | true |
2,905,265,327 | NVLS support in Pytorch | rajagond | open | [
"oncall: distributed",
"triaged"
] | 2 | NONE | Does PyTorch support NVLS? If not, how does it manage to call NCCL’s NVLS algorithm using `torch.distributed.all_reduce`?
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,905,247,105 | Introduce TORCH_ABI_VERSION and a runtime aoti_torch_abi_version C shim ABI | janeyx99 | closed | [
"release notes: cpp",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148836
<details>
ghstack-source-id: 9619e98a56b47312c0ddea04b9d9500dd8e554b3
Pull Request resolved: https://github.com/pytorch/pytorch/pull/148836
<details>
| true |
2,905,238,517 | [Inductor] Error detected in ReluBackward0 | Cookiee235 | closed | [
"oncall: pt2",
"module: aotdispatch",
"module: pt2-dispatcher"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
### Description
The following script failed when running it with the `torch.compile(mod, 'inductor')` under the nightly version (i.e., 2.7.0.dev20250308+cu126)!
### Reproducible script
```python
import torch
torch.set_grad_enabled(True)
class SimpleModel(torch.nn.Module):
def __init__(s... | true |
2,905,235,434 | Remove aoti_torch_cpu__weight_int4pack_mm_cpu_tensor | janeyx99 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"ciflow/inductor",
"release notes: inductor",
"ci-no-td"
] | 17 | CONTRIBUTOR | I noticed that this op was likely intended to be in the `extern "C"` portion of the file, but it was not added as such in https://github.com/pytorch/pytorch/pull/145250 which means this function is actually not stable/would get mangled by C++.
Following the thread there I am thinking there are two possible solutions... | true |
2,905,230,544 | [caffe2/torch] Fixup upstream LLVM (major version 21) API changes | HighW4y2H3ll | closed | [
"oncall: jit",
"fb-exported",
"Merged",
"NNC",
"ciflow/trunk",
"release notes: jit"
] | 8 | CONTRIBUTOR | Latest LLVM introduced two changes related to the `Triple` usage that causes build failures when building pytorch.
## Failure in llvm_codegen.cpp:
Triple is stored in Modules instead of the string: https://github.com/llvm/llvm-project/commit/979c275097a642e9b96c6b0a12f013c831af3a6e
## Failure in llvm_jit.cpp:
T... | true |
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