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 |
|---|---|---|---|---|---|---|---|---|
2,877,582,641 | [test][do not merge] Upgrade oneDNN to v3.7(3) | yanbing-j | closed | [
"module: mkldnn",
"open source",
"module: arm",
"ciflow/trunk",
"topic: not user facing",
"intel",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu",
"ciflow/linux-aarch64"
] | 2 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @gujinghui @PenghuiCheng @XiaobingSuper @jianyuh @jgong5 @mingfeima @sanchitintel @ashokei @jingxu10 @min-jean-cho @Guobing-Chen @Xia-Weiwen @snadampal @malfet @milpuz01 @voznesenskym @penguinwu @EikanWang @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8... | true |
2,877,580,935 | [test][do not merge] Upgrade oneDNN to v3.7 (2) | yanbing-j | closed | [
"module: mkldnn",
"open source",
"module: arm",
"ciflow/trunk",
"topic: not user facing",
"intel",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu",
"ciflow/linux-aarch64"
] | 2 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @gujinghui @PenghuiCheng @XiaobingSuper @jianyuh @jgong5 @mingfeima @sanchitintel @ashokei @jingxu10 @min-jean-cho @Guobing-Chen @Xia-Weiwen @snadampal @malfet @milpuz01 @voznesenskym @penguinwu @EikanWang @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8... | true |
2,877,576,911 | [test][do not merge] Upgrade oneDNN to v3.7 (1) | yanbing-j | closed | [
"module: mkldnn",
"open source",
"module: arm",
"ciflow/trunk",
"topic: not user facing",
"intel",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu",
"ciflow/linux-aarch64"
] | 2 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @gujinghui @PenghuiCheng @XiaobingSuper @jianyuh @jgong5 @mingfeima @sanchitintel @ashokei @jingxu10 @min-jean-cho @Guobing-Chen @Xia-Weiwen @snadampal @malfet @milpuz01 @voznesenskym @penguinwu @EikanWang @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8... | true |
2,877,534,181 | [inductor][user triton] comprehensive_padding + user-defined triton kernels can produce wrong results | davidberard98 | closed | [
"high priority",
"triage review",
"oncall: pt2",
"module: inductor",
"module: user triton"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
If a mm kernel produces non-contiguous outputs due to comprehensive padding, and that output is passed into a user-defined triton kernel, then the strides may be passed incorrectly to the user-defined triton kernel. Repro below:
<details>
```python
import torch
import triton
import triton.lan... | true |
2,877,486,394 | update _unsafe_set_version_counter to accept lists of tensors | zqwenn | closed | [] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
I encountered an issue that has been resolved by this [Pull Request](https://github.com/pytorch/pytorch/pull/137921). I would like to request its inclusion in version 2.6+.
### Versions
torch==2.6.0 | true |
2,877,460,832 | Inconsistent results from `is_compile_supported ` with equivalent device identifiers | default1360 | closed | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 2 | NONE | ### 🐛 Describe the bug
The `is_compile_supported` function returns inconsistent results for equivalent device identifiers:
- `is_compile_supported("cuda")` returns `True`
- `is_compile_supported("cuda:0")` returns `False`
If it's not a bug, feel free to close this issue.
```
import torch
from torch._dynamo.utils im... | true |
2,877,410,582 | Use /permissive- for torch libraries in MSVC builds | cyyever | open | [
"module: windows",
"triaged",
"open source",
"windows-triaged",
"Stale",
"release notes: jit",
"topic: not user facing"
] | 5 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremyux @Blackhex | true |
2,877,379,926 | [dynamo][optimizers] Install ID_GUARDED tensors into the Fx graph | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"keep-going"
] | 12 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147824
Earlier, with inline flag we were lifting id-guarded tensors to the inputs to the Fx graph. But this offers no benefit. Main idea behind lifting parameters as inputs was to reuse the compilation units across many instances of... | true |
2,877,362,536 | remove asserttion in expand_to_full_mesh_op_strategy | zqwenn | open | [
"oncall: distributed",
"triaged",
"open source",
"Stale",
"release notes: distributed (dtensor)"
] | 6 | CONTRIBUTOR | Fixes #147732
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,877,358,060 | `AssertionError: Mixing fake modes NYI` in FakeTensorMode context | default1360 | closed | [
"triaged",
"oncall: pt2",
"module: fakeTensor",
"module: pt2-dispatcher"
] | 2 | NONE | ### 🐛 Describe the bug
When using FakeTensorMode in conjunction with FX Graph operations in PyTorch, an AssertionError: Mixing fake modes NYI is raised. I'm not certain whether this behavior is expected or if it's a bug. If it's not a bug, feel free to close this issue.
```
import torch
from torch._subclasses import... | true |
2,877,350,911 | Use torch_compile_options for c10 libraries | cyyever | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: build",
"topic: improvements",
"ciflow/inductor",
"ciflow/rocm",
"ciflow/xpu"
] | 28 | COLLABORATOR | c10, c10_cuda, c10_hip and c10_xpu are given additional compile options by torch_compile_options, which are more restrictive and can help reveal potential bugs inside the code. | true |
2,877,347,103 | [WIP][ptd][nccl] use current-stream as nccl-stream under async=False mode | cenzhaometa | open | [
"oncall: distributed",
"fb-exported",
"Stale",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 9 | CONTRIBUTOR | Summary:
PTD current workflow:
- PTD creates its own dedicated `ncclStream` for comm operation
- it will first add a dependency on current-stream (typically the compute stream) to ensure tensors are ready before invoking collective
such stream synchronization become expensive in Inference world (cpu overhead: 70u... | true |
2,877,302,664 | [dynamo][guards] Dont insert ID and TENSOR_MATCH at the same time | anijain2305 | closed | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147824
* __->__ #147819
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,877,301,660 | Bug in `torch.ao.nn.quantized.Sigmoid` Parameter Restoration after `state_dict ` Loading | vwrewsge | open | [
"oncall: quantization"
] | 1 | NONE | ### 🐛 Describe the bug
There seems to be an issue in PyTorch's quantized `Sigmoid` module (`nnq_Sigmoid`) where the quantization parameters (`scale` and `zero_point`) are not properly restored when loading the state dictionary (`state_dict`) into a newly initialized module with different initial parameters.
Code:
``... | true |
2,877,289,439 | [test][do not merge]Upgrade oneDNN to v3.7 (VS2019) | yanbing-j | closed | [
"module: mkldnn",
"open source",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/linux-aarch64"
] | 4 | COLLABORATOR | cc @gujinghui @PenghuiCheng @XiaobingSuper @jianyuh @jgong5 @mingfeima @sanchitintel @ashokei @jingxu10 @min-jean-cho @Guobing-Chen @Xia-Weiwen @snadampal @voznesenskym @penguinwu @EikanWang @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,877,244,407 | DISABLED test_inductor_broadcast (__main__.CompileTest) | pytorch-bot[bot] | open | [
"oncall: distributed",
"triaged",
"module: flaky-tests",
"skipped",
"module: c10d",
"oncall: pt2"
] | 15 | 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_inductor_broadcast&suite=CompileTest&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37757262792).
Over the past 3 hours... | true |
2,877,232,714 | torch.compile with backend tensorrt fails with constraint violation issues | peri044 | closed | [
"oncall: pt2",
"module: dynamic shapes"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
Our basic test case is
```py
class MyModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.conv = torch.nn.Conv2d(3, 16, 3, stride=1, bias=True)
self.relu = torch.nn.ReLU()
def forward(self, x):
out = self.conv(x)
... | true |
2,877,145,081 | unbind_copy opinformation cause exception while running test_dtensor_ops.py | dayanandav | open | [
"oncall: distributed",
"triaged",
"bug",
"module: dtensor"
] | 1 | NONE | ### 🐛 Describe the bug
["unbind_copy"](https://github.com/pytorch/pytorch/blob/main/test/distributed/tensor/test_dtensor_ops.py#L435) entry under dtensor_fails(xfail) list cause below exception.
Cmd : python3 -m pytest -vs test_dtensor_ops.py --collect-only
Exception :
File "/home/pytorch/test/distributed/tensor/... | true |
2,877,057,618 | Clean temporary directory at exit | arthurlw | closed | [
"oncall: distributed",
"oncall: jit",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 8 | CONTRIBUTOR | Issue: A temporary directory is created in [pytorch/torch/distributed/nn/jit/instantiator.py](https://github.com/arthurlw/pytorch/blob/clean-temp-directory-at-exit/torch/distributed/nn/jit/instantiator.py) but is never cleaned up, leading to a ResourceWarning on program exit.
Solution: Registered an `atexit` handler... | true |
2,877,038,703 | Enable ASAN in CUDA tests | cyyever | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,877,030,757 | [cutlass backend] try fix standlone runner test | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147811
Differential Revision: [D70147859](https://our.internmc.facebook.com/intern/diff/D70147859/)
Trying to fix this test one last time, especially when mixed mm is getting removed.
cc @voznesenskym @penguinwu @EikanWang @... | true |
2,877,023,409 | [HSDP2] `TORCH_NCCL_AVOID_RECORD_STREAMS` x `use_deterministic_algorithms` => NaN Gradient | leonardo0lyj | closed | [
"oncall: distributed",
"module: fsdp"
] | 2 | NONE | ### 🐛 Describe the bug
Hey Andrew @awgu, as a big fan of FSDP2, I find an potential BC issue with `TORCH_NCCL_AVOID_RECORD_STREAMS = True` 😄
*Demand*
- HSDP (2D mesh in FSDP2)
- `TORCH_NCCL_AVOID_RECORD_STREAMS = True`
- `torch.use_deterministic_algorithms(True)`
*Result*
- After `.backward()`, sharded parameter ... | true |
2,876,993,512 | Fix crash in -[PTMCoreMLCompiler _compileModel:atPath:] | dinhvh | closed | [
"oncall: jit",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: jit"
] | 4 | CONTRIBUTOR | Summary:
We could hit one of those exceptions:
https://github.com/apple/coremltools/blob/main/modelpackage/src/ModelPackage.cpp#L205-L225
And it would make this code path crash.
Test Plan: build.
Differential Revision: D70122378
cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel | true |
2,876,874,755 | Back out "use copy2d in h2d/d2h copy when possible (#146256)" | s4ayub | open | [
"fb-exported",
"Stale",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary:
Original commit changeset: aa7d1b82ac9d
Original Phabricator Diff: D69088122
Reviewed By: banitag1, 842974287, ngimel
Differential Revision: D70118904
| true |
2,876,868,609 | [AOTI][refactor] Fix a typo | desertfire | closed | [
"module: cpu",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147803
* __->__ #147807
* #147806
* #147805
Summary: defination -> definition
Differential Revision: [D70146182](https://our.internmc.facebook.com/intern/diff/D70146182)
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu1... | true |
2,876,868,554 | [AOTI][refactor] Replace run_command_and_check with CppBuilder.build | desertfire | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147803
* #147807
* __->__ #147806
* #147805
Summary: Consolidate cpp compilation action to CppBuilder. Reland https://github.com/pytorch/pytorch/pull/147680
Differential Revision: [D70146183](https://our.internmc.facebook.com/intern/diff/D... | true |
2,876,868,501 | [AOTI][refactor] Rename use_absolute_path to use_relative_path | desertfire | closed | [
"Merged",
"ciflow/trunk",
"topic: bc breaking",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147803
* #147807
* #147806
* __->__ #147805
Summary: The option really means to compile a cpp file using its basename instead of the its full path. Reland https://github.com/pytorch/pytorch/pull/147679.
cc @voznesenskym @penguinwu @EikanWa... | true |
2,876,854,418 | [ca] side-effect free inital trace: compiled_args | xmfan | closed | [
"oncall: distributed",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: distributed (c10d)",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"keep-going",
"ciflow/slow",
"module: compiled autograd",
"ci-no-td"
] | 9 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147891
* __->__ #147804
* #147796
* #147242
const methods to prevent accidental mutation. changes mainly in Error nodes and PyNode.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @voznesenskym @pen... | true |
2,876,782,861 | [AOTI][refactor] Consolidate CppBuilder.build and CppBuilder.build_fbcode_cpu_re | desertfire | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147803
* #147807
* #147806
* #147805
Summary: Let CppBuilder handle all the cpp build logic
Differential Revision: [D70146185](https://our.internmc.facebook.com/intern/diff/D70146185)
cc @voznesenskym @penguinwu @EikanWang @jgong5 ... | true |
2,876,772,461 | Udpate hw requirement for FP64 on "Getting Started on Intel GPU" | ZhaoqiongZ | closed | [
"open source",
"Merged",
"topic: not user facing"
] | 9 | CONTRIBUTOR | Fixes #147731
| true |
2,876,714,391 | Incorrect Gradients at Boundary Points for `torch.nn.functional.hardswish` | vwrewsge | closed | [
"module: autograd",
"triaged",
"actionable"
] | 1 | NONE | ### 🐛 Describe the bug
The gradients of the hardswish function at boundary points (specifically at -3.0 and 3.0) are incorrect. The gradient at -3.0 should be 0, and the gradient at 3.0 should be 1.0. However, the current implementation produces incorrect values at these points.
# Code
```
import torch
# Test case ... | true |
2,876,704,082 | test | eellison | open | [
"Stale",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147800
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,876,678,180 | Failed to run autotuning code block: Triton Error [CUDA]: device-side assert triggered | bhack | closed | [
"triaged",
"oncall: pt2",
"module: aotinductor"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
After export I was trying to aoti compile and package a model but the process failed.
### Error logs
Here part of the inductor+ log near the failure.
[partial_inductor.log](https://github.com/user-attachments/files/18952979/partial_inductor.log)
### Versions
nightly
cc @chauhang @penguinwu... | true |
2,876,622,592 | stage 1 of depreate silent fallback of tuning gemm | henrylhtsang | closed | [
"fb-exported",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 34 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147798
Differential Revision: [D70045778](https://our.internmc.facebook.com/intern/diff/D70045778/)
context:
https://github.com/pytorch/pytorch/issues/147479
For the most part, this should not change the behavior.
For int... | true |
2,876,614,286 | [Inductor-CPU] Avoid memory allocator lock contention in the GEMM template | sanchitintel | open | [
"open source",
"Stale",
"ciflow/trunk",
"topic: performance",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | ## Summary
Use stack allocated buffer in GEMM template, whenever possible, to avoid memory allocator lock contention. It'd probably only save us a few cycles.
Based on a quick glance at the `get_cache_blocking` code, it looks like `Mc_blocks * Mr * Nc_blocks * Nr` wouldn't exceed the size of per-core L2 cache, so... | true |
2,876,567,278 | [ca] side-effect free initial trace: GraphTask | xmfan | closed | [
"Merged",
"Reverted",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"module: compiled autograd",
"ci-no-td"
] | 6 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147891
* #147804
* __->__ #147796
* #147242
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,876,549,424 | DISABLED test_inductor_all_to_all_single (__main__.CompileTest) | pytorch-bot[bot] | open | [
"oncall: distributed",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2"
] | 16 | 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_inductor_all_to_all_single&suite=CompileTest&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37743029313).
Over the pa... | true |
2,876,545,660 | Fix bug in async TP handling of "reshape -> scaled mm -> reshape" pattern for float8 row-wise scaling | danielvegamyhre | closed | [
"oncall: distributed",
"release notes: distributed (pipeline)",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Part of https://github.com/pytorch/torchtitan/issues/864
## Summary
While testing torchtitan with float8 training with rowwise scaling + async TP, a [bug](https://github.com/pytorch/torchtitan/issues/864) was discovered. The symptom was the scaling factor dims did not match the dims of the tensor the scales were t... | true |
2,876,544,438 | context_parallel fails with plain sdpa kernel SDPBackend.MATH | githubsgi | open | [
"oncall: distributed",
"triaged",
"module: sdpa",
"module: context parallel"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
torch.distributed.context_parallel fails with plain sdpa kernel with the following stack trace .
```
....../lib/python3.10/site-packages/torch/distributed/tensor/_dispatch.py", line 475, in _try_replicate_spec_for_scalar_tensor
[rank0]: raise RuntimeError(
[rank0]: RuntimeError: aten.... | true |
2,876,525,022 | Delete unused conda-aws-upload environment | malfet | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | As this environment only contains keys for Anaconda uploads | true |
2,876,502,656 | [ROCm] Remove benign warning about missing amdgpu.ids | ethanwee1 | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Fixes #144203.
We build a custom libdrm when preparing our docker image. We attempt to locate the amdgpu.ids file relative to the python binary, but this is not possible for venv installs of pytorch when the python binary is a symlink. Not finding amdgpu.ids causes `torch.cuda.get_device_name()` to return "AMD Rad... | true |
2,876,500,475 | Remove unused rand call if not fallback to eager for rand | henryhu6 | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 26 | CONTRIBUTOR | Fixes #147171
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,876,491,641 | [ci][anaconda] Remove conda from linter docker images | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Remove conda usage from the linter docker images
Handles part of https://github.com/pytorch/pytorch/issues/148110 | true |
2,876,461,365 | Make record/storage alignment in torch.save configurable | mikaylagawarecki | closed | [
"oncall: jit",
"Merged",
"release notes: jit",
"release notes: python_frontend"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148018
* __->__ #147788
* #147787
* #147786
cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel | true |
2,876,460,991 | Add information about checkpoint offset to untyped storages when torch.load under FakeTensorMode | mikaylagawarecki | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148018
* #147788
* __->__ #147787
* #147786
| true |
2,876,460,864 | Allow torch.load under FakeTensorMode to load FakeTensors with correct devices (for plain Tensors) | mikaylagawarecki | closed | [
"Merged",
"release notes: python_frontend",
"topic: bug fixes"
] | 3 | CONTRIBUTOR | This only fixes _rebuild_tensor_v2 and _rebuild_tensor_v3
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148018
* #147788
* #147787
* __->__ #147786
| true |
2,876,421,875 | torch.utils._content_store: fix error in hash_storage on XPU | benjaminglass1 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/mps",
"ciflow/xpu"
] | 13 | COLLABORATOR | See https://github.com/pytorch/pytorch/actions/runs/13508573465/job/37745227468 for an example error. This is triggering after the merge of #147541, which enabled Dynamo compilation on XPU.
| true |
2,876,416,728 | [Inductor][Optimus] Fix a corner case in split cat aten pass | mengluy0125 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"inductor_pattern_match"
] | 5 | CONTRIBUTOR | Summary: We need to further check the input of the cat to make sure all of them are from the same split node.
Test Plan:
# unit test
```
buck2 test 'fbcode//mode/dev-nosan' fbcode//caffe2/test/inductor:split_cat_fx_aten_passes -- test_split_cat_post_grad
```
Buck UI: https://www.internalfb.com/buck2/c875cbdd-5374-46... | true |
2,876,414,849 | [CacheBench] Add hf_T5 llama moco to cachebench | oulgen | 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):
* __->__ #147783
* #147782
* #147781
* #147780
* #147688
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,876,414,428 | [CacheBench] Add huggingface | oulgen | closed | [
"Merged",
"ciflow/trunk",
"release notes: benchmark",
"release notes: releng",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147783
* __->__ #147782
* #147781
* #147780
* #147688
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,876,414,299 | [CacheBench] Separate dynamic into its own option | oulgen | closed | [
"Merged",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147783
* #147782
* __->__ #147781
* #147780
* #147688
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,876,414,188 | [CacheBench] Add repeat option so that we can have more accurate cache results | oulgen | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147783
* #147782
* #147781
* __->__ #147780
* #147688
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,876,412,999 | [dynamic shapes][export] ignore when real-tensor fallback fails | pianpwk | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 7 | CONTRIBUTOR | Summary: uninspired solution to https://github.com/pytorch/pytorch/issues/147402
Test Plan: test_draft_export
Differential Revision: D70132269
| true |
2,876,335,474 | [ROCm] CK Memory-Efficient Attention (attention bias support) | alugorey | closed | [
"module: rocm",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"skip-pr-sanity-checks"
] | 18 | CONTRIBUTOR | Implements CK as the backend for memory efficient attention with a couple caveats:
- Still enabled via `torch.backends.cuda.preferred_rocm_fa_library("ck")
- Does NOT support Nested Tensors
Using the mem_eff path allows us to use attention bias with a CK sdpa backend
cc @jeffdaily @sunway513 @jithunnair-amd @pr... | true |
2,876,328,213 | Decorators like `torch.compiler.allow_in_graph` doesn't account for id reuse | StrongerXi | closed | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Context: https://github.com/pytorch/pytorch/pull/146367/files#r1964644166
Repro:
```python
import torch
@torch.compiler.allow_in_graph
def f(x):
return x + 1
del f
def g(x):
return x + 2
@torch.compile(fullgraph=True, backend="eager")
def fn(x):
return g(x)
fn(torch.ones(1))
``... | true |
2,876,305,269 | [Dynamo] Small issue in `SETUP_WITH` implementation | guilhermeleobas | closed | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 4 | COLLABORATOR | ### 🐛 Describe the bug
The CPython [docs](test_propagate_exception_inside_ctx_manager) for `SETUP_WITH` state:
> This opcode performs several operations before a with block starts. First, it loads `__exit__()` from the context manager and pushes it onto the stack for later use by `WITH_EXCEPT_START`. Then, `__ente... | true |
2,876,303,044 | cpp_builder: unbreak clang++ detection | benjaminglass1 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Fixes an issue where `_is_gcc` would match on `clang++` due to the string ending with `g++`.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,876,300,828 | Test | hashupdatebot | closed | [
"open source",
"topic: not user facing"
] | 2 | NONE | Need to see what the conclusion of the mangled workflow is | true |
2,876,293,200 | [cuda] Add new gamma beta backwards kernel | ahmadsharif1 | open | [
"Stale",
"release notes: nn"
] | 2 | CONTRIBUTOR | Context:
Prior to this PR we had 3 non-ROCM CUDA kernels to handle GammaBeta backwards pass:
1. For small M
2. 32x32 faster kernel for shapes that were divisible by 32 for both M and N
3. All other cases
This approach had several weaknesses:
1. For non-32x32 case, the performance was slow because we were not us... | true |
2,876,271,479 | torch._check doesn't work for .item() then select | ydwu4 | closed | [
"triaged",
"oncall: pt2",
"module: dynamic shapes"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Repro:
```python
import torch
# Example tensor
A = torch.tensor([
[1, 2, 3],
[4, 5, 6],
[7, 8, 9]
])
# Scalar tensor indicating the index
index = torch.tensor(1, dtype=torch.int64)
@torch.compile(fullgraph=True, dynamic=True)
def f(x, index):
idx = index.item()
torch._check... | true |
2,876,259,096 | Fix bug in FSDP wrapped module with zero argument | mori360 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (fsdp)",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Fixes https://github.com/pytorch/pytorch/issues/147531
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,876,216,176 | add pt2 testing for torch.float8_e8m0fnu | vkuzo | open | [
"Stale",
"release notes: quantization",
"fx"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147770
Summary:
Adds PT2 enablement tests for `torch.float8_e8m0fnu`, skipping tests as needed for the functionality which does not work yet:
* displaying e8m0 in TORCH_LOGS output: fixed in this PR
* uint8 -> view as e8m0 ->... | true |
2,876,183,349 | DISABLED test_custom_hsdp_all_reduce_hook (__main__.TestHSDPWithCustomHook) | jithunnair-amd | closed | [
"oncall: distributed",
"module: rocm",
"skipped"
] | 3 | COLLABORATOR | Platforms: rocm
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Fdistributed%2F_composable%2Ffsdp%2Ftest_fully_shard_init.py%3A%3ATestHSDPWithCustomHook%3A%3Atest_custom_hsdp_all_reduce_hook'%22%5D)).
cc @H-Huang @awgu @kwen2501 ... | true |
2,876,178,160 | [SDPA] Respect `sdpa_kernel`'s `priority_order` setting in `torch.compile` | eqy | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"dynamo-ctx-manager",
"module: sdpa"
] | 6 | COLLABORATOR | [https://github.com/pytorch/pytorch/pull/140467](https://github.com/pytorch/pytorch/pull/140467) added the option to specify a priority order for SDPA but the `torch.compile` path silently ignored this setting as I wasn't aware of the separate context manager handling on `torch.compile`
cc @voznesenskym @penguinwu @... | true |
2,876,173,149 | DISABLED test_custom_hook_custom_stream (__main__.TestHSDPWithCustomHook) | jithunnair-amd | closed | [
"oncall: distributed",
"module: rocm",
"skipped"
] | 2 | COLLABORATOR | Platforms: rocm
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22'test%2Fdistributed%2F_composable%2Ffsdp%2Ftest_fully_shard_init.py%3A%3ATestHSDPWithCustomHook%3A%3Atest_custom_hook_custom_stream'%22%5D)).
cc @H-Huang @awgu @kwen2501 @w... | true |
2,876,142,230 | [Inductor-CPU] Memory allocator lock contention is slowing down templated GEMMs | sanchitintel | closed | [
"module: performance",
"module: cpu",
"oncall: cpu inductor"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
# Problem
CPP GEMM template creates some per-thread local accumulation buffers within an OpenMP parallel region.
All threads contend with each other for memory allocator locks, since even tcmalloc is not completely lock-free.
The perf impact may be significant for some input shapes.
e.g. For ... | true |
2,876,128,894 | [FlexAttention] Improve error msg for embedding < 16 | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"module: flex attention"
] | 4 | CONTRIBUTOR | flex_attention uses tl.dot, which [does not support embedding < 16](https://github.com/triton-lang/triton/issues/2266) on input shapes. This PR adds explicit error message for users who are prototyping with small tensors.
Fixes #147701
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @z... | true |
2,876,114,035 | [c10d] Restrict use condition of NCCL mem pool | kwen2501 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147764
Add check to see if CUDA driver support multicast, as does in Symmetric Memory.
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,876,113,378 | [cuda] Added a correctness test for layernorm backwards | ahmadsharif1 | open | [
"module: mkldnn",
"Stale",
"release notes: nn",
"topic: not user facing",
"ciflow/linux-aarch64"
] | 3 | CONTRIBUTOR | My goal is to improve the performance of the layernorm CUDA backwards pass. That will be done in a future PR.
This PR is the first step -- I added a test for making sure the layernorm CUDA backwards pass produces accurate results.
This test passes on the baseline, which means the current implementation of the bac... | true |
2,876,108,118 | [inductor][user triton] Handle scf.yield more accurately | davidberard98 | closed | [
"Merged",
"ciflow/trunk",
"topic: improvements",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"module: user triton"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147762
**TL;DR**: Previously, the mutation analysis for scf.if/scf.for would bundle all the scf.yield arguments into a single op (the scf.yield), such that a mutation on any returned value from the scf.if/scf.for would register as... | true |
2,876,093,000 | [ROCm] Add support for gfx1102 arch to wheel builds. | naromero77amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 5 | COLLABORATOR | [gfx1102 is not officially supported](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/system-requirements.html) but most ROCm libs have gfx1102 code objects available since ROCm 5.5. Now that we're using `--offload-compress` we can fit another gfx target.
cc @jeffdaily @sunway513 @jithunnair... | true |
2,876,053,754 | [logging] Add toplevel dynamo_compile / tlparse logging for AOTI | masnesral | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Summary:
This adds the proper context managers in `compile_fx_aot` such that we get:
1) A toplevel chromium event (i.e., tlparse)
2) A single `dynamo_compile` log entry
Test Plan:
Before:
* Scuba (we only log the dynamo event): https://fburl.com/scuba/dynamo_compile/sandbox/gaqowzrd
* Perfetto trace: https://fburl.com... | true |
2,875,986,300 | Add sparse tensors constructed via legacy constructor to _sparse_tensors_to_validate | mikaylagawarecki | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | This is a redo of https://github.com/pytorch/pytorch/pull/147408 which added validation at the end of the legacy constructor calls.
The reason why I didn't land that was because in `legacy_load`, constructor would be called before storages of indices/values are set. So the tensor would not actually be validated.
... | true |
2,875,953,355 | [DCP][OSS] Rank local checkpointing in DCP without collectives | saumishr | open | [
"oncall: distributed",
"fb-exported",
"ciflow/trunk",
"release notes: distributed (checkpoint)",
"oncall: distributed checkpointing"
] | 13 | CONTRIBUTOR | Summary:
DCP metadata collectives become prohibitively expensive as the job scale grows. This PR introduces rank-local checkpointing which basically saves and loads the checkpoint without any collective. The trade off for now is the dedupe and re-sharding. Support for these would be introduced soon.
Differential Re... | true |
2,875,952,606 | compilation error on SequenceParallel'ed Dropout | bonpyt | open | [
"oncall: distributed",
"triaged",
"tensor subclass",
"oncall: pt2",
"module: dtensor"
] | 17 | NONE | ### 🐛 Describe the bug
Trying to compile a model with `Dropout` parallelised with `SequenceParallel` fails:
```
import torch
from torch.distributed.device_mesh import init_device_mesh
from torch.distributed.tensor import Shard, DTensor
from torch import nn
from torch.distributed import get_rank
from torch.distribute... | true |
2,875,883,996 | `torch.compile(flex_attention, dynamic=True)` fails with `LoweringException` | pzelasko | open | [
"triaged",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 1 | NONE | ### 🐛 Describe the bug
Minimal snippet for repro:
```python
import torch
from torch.nn.attention.flex_attention import flex_attention
flex_attention = torch.compile(flex_attention, dynamic=True)
B, T, H, C = 4, 51, 8, 128
x = torch.randn(B, H, T, C, device="cuda")
flex_attention(x, x, x)
```
Error:
```
Traceback... | true |
2,875,852,048 | DISABLED test_2d_reductions_mixed_indexing_reduction_op0_cuda (__main__.TritonBlockPointerTestGPU) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_2d_reductions_mixed_indexing_reduction_op0_cuda&suite=TritonBlockPointerTestGPU&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37715... | true |
2,875,851,951 | DISABLED test_inductor_all_reduce_single (__main__.CompileTest) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: c10d"
] | 14 | NONE | Platforms: inductor, rocm, linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_inductor_all_reduce_single&suite=CompileTest&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37722206702).
Over the past... | true |
2,875,834,693 | [RFC][c10d] Expose NCCL API for runtime estimation | kwen2501 | closed | [
"oncall: distributed",
"module: nccl",
"module: c10d"
] | 0 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
NCCL API: `ncclGroupSimulateEnd`
https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/api/group.html#ncclgroupsimulateend
Some PyTorch users would like to access it at Python level for run-time estimation of communication ops.
### Alternatives
_No response_
### Additio... | true |
2,875,746,109 | [pytree] Register normal class to register_dataclass | angelayi | closed | [
"Merged",
"ciflow/trunk",
"release notes: export"
] | 7 | CONTRIBUTOR | Fixes https://github.com/pytorch/pytorch/pull/147532#discussion_r1964365330
| true |
2,875,728,653 | Remove link to search survey | svekars | closed | [
"module: docs",
"Merged",
"ciflow/trunk",
"topic: docs",
"topic: not user facing"
] | 6 | CONTRIBUTOR | cc @brycebortree @sekyondaMeta @AlannaBurke | true |
2,875,675,799 | Modifications to RuntimeEstimator and SACEstimator | sanketpurandare | open | [
"oncall: distributed",
"open source",
"Stale",
"release notes: distributed (c10d)"
] | 2 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,875,646,503 | remove prints from partitioner | bdhirsh | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | See https://github.com/pytorch/pytorch/pull/146752/files/c57894cd742cb35161dbf888cb3880f243d167e5..22d8f9a6575db5f0400dee761b7eeb558c153676#r1968015955
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #133044
* #147561
* __->__ #147749
| true |
2,875,612,740 | Switch to using Docker Images from ECR instead of Docker Hub | ZainRizvi | closed | [
"triaged",
"module: docker"
] | 2 | CONTRIBUTOR | Switch our docker builds to pull from public ECR images instead of Docker Hub
Motivation:
Docker Hub is about to [change their rate limiting policy](https://docs.docker.com/docker-hub/usage/#rate-limit). Moreover, switching to ECR based images will likely give us more reliable docker pulls (our docker hub connection... | true |
2,875,602,926 | Adding MVP of P1 INT16 Full | Ivan-Dimitrov | open | [
"fb-exported",
"Stale",
"release notes: quantization"
] | 5 | CONTRIBUTOR | Summary:
X-link: https://github.com/ctrl-labs/src2/pull/42734
Add p1_int16 total quantization target which quantizes the input to int 16
Test Plan:
https://docs.google.com/document/d/1HMupJU8lO7CDpsV6jmSaXOTRfYN6LThMLBt8gZ3URqk/edit?usp=sharing
f698347399
Differential Revision: D69993444
| true |
2,875,563,025 | [Inductor] Fix `inductor/test_kernel_benchmark.py` for new Triton; do not duplicate parameters in `_dump_launch_params` | anmyachev | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu"
] | 8 | COLLABORATOR | The problem is that the new Triton uses the following code branch, which does not filter the call parameters, which may already be in the launcher's cfg.kwargs. This is generally expected behavior, so I just stopped adding arguments from `launcher.config.kwargs`: https://github.com/pytorch/pytorch/blob/cde12207a083f85a... | true |
2,875,529,758 | [AOTI] Extend torchgen to generate C shim with version number | desertfire | open | [
"topic: improvements",
"topic: not user facing",
"ciflow/inductor",
"suppress-api-compatibility-check",
"suppress-bc-linter",
"module: aotinductor"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147745
Summary: While it is ok to add a new arg with defaul value to a fallback op in Python, it will be BC-breaking for the C shim. This PR adds an automatic approach to update C shim files when specifying a version number with a li... | true |
2,875,374,572 | Importing torch_tensorrt causes warning for implicitly cleaned up file | ivan94fi | closed | [
"oncall: distributed"
] | 0 | NONE | ### 🐛 Describe the bug
A temporary directory is created at this line in `torch.distributed.nn.jit.instantiator` and it is never cleaned:
https://github.com/pytorch/pytorch/blob/576ed1e400d069ec2fff6162f82a71ff0bd81f7c/torch/distributed/nn/jit/instantiator.py#L20
A warning is generated by `tempfile` itself when the p... | true |
2,875,151,503 | Update torch-xpu-ops commit pin | xytintel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"keep-going",
"ciflow/xpu"
] | 7 | CONTRIBUTOR | Update the torch-xpu-ops commit to [306a0ffb6e0cae27c5bd9a3b9cd378048c8e00e7](https://github.com/intel/torch-xpu-ops/commit/306a0ffb6e0cae27c5bd9a3b9cd378048c8e00e7), includes:
- Bugfix (LayerNorm/Nonzeros)
- Update AOT target
| true |
2,874,986,066 | Update CPU tolerance for f16 triplet margin loss | GeorgeWigley | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor"
] | 7 | CONTRIBUTOR | Currently, the `test_torchinductor_opinfo` test for `nn.functional.triplet_margin_loss` fails on AArch64, this PR increases the acceptable ATOL and RTOL for this test when using F16. There is precedent for this as XPU and CUDA already increase the tolerance. Additionally, the CPU backend increases the tolerance for the... | true |
2,874,954,113 | [dynamo] Support passing arguments to `DeviceMesh.get_group` | danthe3rd | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,874,883,183 | Deterministic behaviour with torch.randn_like() on mps when tensor dimensionality exceeds some size | henry-ald | open | [
"needs reproduction",
"triaged",
"module: correctness (silent)",
"module: mps"
] | 6 | NONE | ### 🐛 Describe the bug
With `device="mps"`, `torch.randn_like()` is producing tensors with elements of identical value along a given dimension, specifically once the dimensionality exceeds a certain size. This behaviour is not present on the CPU. Here is some code demonstrating:
```python
import torch
# On MPS GPU
... | true |
2,874,777,365 | torchvision export model error:: torchvision.models.detection.retinanet_resnet50_fpn_v2 | wangqianscu | open | [
"oncall: jit"
] | 0 | NONE | ### 🐛 Describe the bug
When I use torchvision.models.detection.retinanet_resnet50_fpn() to generate the model, it raise error.
My code:
```
input_=torch.ones(3,300,400)
input_1 = torch.ones(3,500,400)
model=torchvision.models.detection.retinanet_resnet50_fpn()
print(model([input_, input_1])) # all o... | true |
2,874,752,533 | Pirater Whatsapp, récupérer un compte Whatsapp 49d0e | cindracomly99 | closed | [] | 0 | NONE | **Essayez ceci** [Appuyez ici pour continuer](https://docs.google.com/document/d/1PBHPbsbaO_-qloDueUYs5cyWstUR7Xkc9HHOnmwmDAE/edit?usp=sharing)
| true |
2,874,650,932 | [Triton upstream] [Inductor] [ROCm] UT failures "Cannot bitcast data-type of size" | jataylo | closed | [
"module: rocm",
"triaged",
"oncall: pt2",
"module: inductor",
"upstream triton"
] | 2 | COLLABORATOR | ### 🐛 Describe the bug
As seen in https://github.com/pytorch/pytorch/pull/147320 when attempting to bump triton in preparation for 3.3.
```
======================================================================
ERROR: test_comprehensive_sort_cuda_bool (__main__.TestInductorOpInfoCUDA)
------------------------------... | true |
2,874,640,602 | [Triton upstream] [Inductor] [ROCm] OpInfo quantile UT accuracy issues | jataylo | closed | [
"module: rocm",
"triaged",
"oncall: pt2",
"module: inductor",
"upstream triton"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
As seen in https://github.com/pytorch/pytorch/pull/147320 when attempting to bump triton in preparation for 3.3.
```
======================================================================
ERROR: test_comprehensive_nanquantile_cuda_float32 (__main__.TestInductorOpInfoCUDA)
----------------------... | true |
2,874,625,585 | [Triton upstream] [Inductor] [ROCm] Cooperative reduction accuracy issues | jataylo | closed | [
"module: rocm",
"triaged",
"oncall: pt2",
"module: inductor",
"upstream triton"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
As seen in https://github.com/pytorch/pytorch/pull/147320 when attempting to bump triton in preparation for 3.3.
Platform: MI200 only
```
test/inductor/test_cooperative_reductions.py::CooperativeReductionTests::test_reduction_fns_name_sum_float16 failed 0.646448212 "AssertionError: Tensor-lik... | true |
2,874,618,950 | [Triton upstream] [Inductor] [ROCm] cpp_wrapper segfaults | jataylo | closed | [
"module: rocm",
"triaged",
"module: inductor",
"upstream triton"
] | 4 | COLLABORATOR | ### 🐛 Describe the bug
As seen in https://github.com/pytorch/pytorch/pull/147320 when attempting to bump triton in preparation for 3.3.
Example failing unit test: test/inductor/test_gpu_cpp_wrapper.py::TestGpuWrapper::test_dtypeview_float32_bfloat16_cuda_gpu_wrapper'
```
TORCHINDUCTOR_COMPILE_THREADS=1 python induc... | true |
2,874,360,649 | DISABLED test_inductor_all_reduce_non_contig_input (__main__.CompileTest) | pytorch-bot[bot] | open | [
"oncall: distributed",
"triaged",
"module: flaky-tests",
"skipped",
"module: c10d",
"oncall: pt2"
] | 18 | 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_inductor_all_reduce_non_contig_input&suite=CompileTest&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37692376208).
O... | true |
2,874,223,072 | [Distribute] len(input_specs) == len(input_args_strategy) AssertionError | zqwenn | open | [
"oncall: distributed",
"triaged"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
When I try to use `register_sharding` for a custom ops, if the operation has keyword arguments (kwargs), it results in an `AssertionError`.
My custom ops is as follows:
```python
my_fusion_attention_grad(
Tensor query,
Tensor key,
Tensor value,
Tensor dy,
int head_num,
... | true |
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