id int64 2.74B 3.05B | title stringlengths 1 255 | user stringlengths 2 26 | state stringclasses 2
values | labels listlengths 0 24 | comments int64 0 206 | author_association stringclasses 4
values | body stringlengths 7 62.5k ⌀ | is_title bool 1
class |
|---|---|---|---|---|---|---|---|---|
3,001,967,148 | [inductor][cpu] pytorch_CycleGAN_and_pix2pix AMP/AMP_FP16 multiple thread performance regression in 2025-04-07 nightly release | zxd1997066 | open | [
"oncall: pt2",
"oncall: cpu inductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
<p>AMP dynamic shape default wrapper</p><table border="1" class="dataframe table">
<thead>
<tr style="text-align: right;">
<th>suite</th>
<th>name</th>
<th>thread</th>
<th>batch_size_new</th>
<th>speed_up_new</th>
<th>inductor_new</th>
<th>eager_n... | true |
3,001,908,347 | Cuda error on RTX 5090d: ImportError: ImportError: cannot import name 'EPOCH_OUTPUT' from 'pytorch_lightning.utilities.types' | paomian001 | closed | [] | 2 | NONE | ### 🐛 Describe the bug
ImportError: cannot import name 'EPOCH_OUTPUT' from 'pytorch_lightning.utilities.types'
### Versions
PyTorch version: 2.8.0.dev20250416+cu128
Is debug build: False
CUDA used to build PyTorch: 12.8
ROCM... | true |
3,001,789,741 | Fix `InstanceNorm` wrong suggestion in warning message | zeshengzong | open | [
"triaged",
"open source"
] | 5 | CONTRIBUTOR | Fixes #109652
## Changes
- Change misleadning suggestion in warning message of `_InstanceNorm`
## Test Result
```python
import torch
m = torch.nn.InstanceNorm1d(64)
input = torch.randn(4, 80, 300)
output = m(input)
/home/zong/code/pytorch/torch/nn/modules/instancenorm.py:115: UserWarning: input's siz... | true |
3,001,767,845 | [Intel GPU] Enable XPU depthwise convolution | ZhiweiYan-96 | open | [
"module: cpu",
"open source",
"topic: not user facing",
"ciflow/inductor",
"ciflow/xpu",
"module: xpu"
] | 7 | COLLABORATOR | # Motivation
This PR enables XPU depthwise convolution by using overrideable backend implemented at `aten/src/ATen/native/mkldnn/xpu/Conv.cpp`. The implementations would treat it as a common convolution with `groups=channels_in`.
# Verification
```
DNNL_VERBOSE=1 python test/xpu/test_conv.py TestConvolutionNN... | true |
3,001,744,590 | [Easy] Optimize `clip_grad` param description | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: nn",
"topic: docs"
] | 5 | CONTRIBUTOR | Fix missing optional description in `clip_grad_norm_` and `clip_grad_value_`
## Test Result
### Before
### After
![ima... | true |
3,001,676,707 | [WIP] Deprecate getPinnedMemoryAllocator use getHostAllocator instead | guangyey | open | [
"open source",
"release notes: cpp"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151531
* #151916
* #151913
| true |
3,001,670,073 | Add pack support and use micro gemm for Half flex attention on CPU | CaoE | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | COLLABORATOR | Add pack support and use micro gemm for the second gemm to improve the performance for Half flex attention on CPU.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,001,621,435 | Add hint message when parameters is empty in clip_grad_norm_ | zeshengzong | open | [
"triaged",
"open source",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Fixes #148259
## Changes
- Add print warning message when `parameters` generator exhausted
## Test Result
### print warning
```python
import torch
import torch.nn as nn
import torch.optim as optim
class SimpleModel(nn.Module):
def __init__(self):
super(SimpleModel, self).__init__()
... | true |
3,001,582,503 | [Inductor] Suppress cuda init error for CPU only Inductor | leslie-fang-intel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150669
* __->__ #151528
**Summary**
After https://github.com/pytorch/pytorch/pull/151255, invoking `torch.compile` on a non-CUDA device prints the following error:
`E0416 23:39:55.953000 418833 torch/_inductor/codegen/cuda/cuda_env.py... | true |
3,001,530,205 | Use device agnostic APIs and variable names for dtensor | amathewc | open | [
"oncall: distributed",
"triaged",
"open source",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | This PR contains the original three files where were added and approved in https://github.com/pytorch/pytorch/pull/148876 . During rebase, other unrelated files were added by mistake to that PR and hence it was closed before merging.
## MOTIVATION
To generalize DTensor test cases for non-CUDA devices, we are repla... | true |
3,001,510,417 | Extend the error type for dynamo logging | houseroad | closed | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 13 | MEMBER |
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,001,467,744 | [inductor] [cpu] [silent incorrectness] `nn.LazyConvTranspose2d-torch.randn-F.linear-torch.argmax` output incorrect results on CPU inductor | shaoyuyoung | open | [
"oncall: pt2",
"oncall: cpu inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: `nn.LazyConvTranspose2d-torch.randn-F.linear-torch.argmax` output incorrect results on CPU inductor
**device backend**: only CPP
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch._inductor import config
config.fallback_random = True
torch.set_... | true |
3,001,424,823 | [inductor] [silent incorrectness] Multiple internal `torch.rand` can lead to inconsistent results with eager | shaoyuyoung | open | [
"high priority",
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: If we just use one-time `torch.rand` in forward function, the output is right. However, output is inconsistent when we use at least two times `torch.rand`. The multiple uses of internal `torch.rand` don't respect the fallback_random (?)
**device backend**: both CPP and triton
```py... | true |
3,001,400,241 | [inductor] [cpu] `nn.Conv2d-F.hardshrink-.view-torch.mv` throws `CppCompileError` on CPU inductor | shaoyuyoung | closed | [
"oncall: pt2",
"oncall: cpu inductor"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: `nn.Conv2d-F.hardshrink-.view-torch.mv` throws `CppCompileError` on CPU inductor
**device backend**: only CPP
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch._inductor import config
config.fallback_random = True
torch.set_grad_enabled(False)... | true |
3,001,366,652 | [inductor] `.to_sparse()-.to_dense()` throws `LoweringException: NotImplementedError:` | shaoyuyoung | closed | [
"high priority",
"triaged",
"oncall: pt2"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: `.to_sparse()-.to_dense()` throws `LoweringException: NotImplementedError:` while eager can execute successfully.
**device backend**: both CPP and triton
**repro**
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch._inductor import config
confi... | true |
3,001,348,753 | [FlexAttention] Remove old constraint that was causing assert failure | drisspg | closed | [
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"module: flex attention"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151521
* #151846
# Summary
Fixes: https://github.com/pytorch/pytorch/issues/148827
This one is strange, I could have sworn this was a real constraint, but I verified and did some performance checks and this constraint isn't re... | true |
3,001,333,591 | DISABLED test_builtin_score_mods_float16_score_mod3_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_float16_score_mod3_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40676327185)... | true |
3,001,333,590 | DISABLED test_builtin_score_mods_different_block_size_float32_score_mod7_BLOCK_SIZE_256_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float32_score_mod7_BLOCK_SIZE_256_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,001,333,351 | DISABLED test_builtin_score_mods_different_block_size_float32_score_mod4_BLOCK_SIZE2_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float32_score_mod4_BLOCK_SIZE2_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/... | true |
3,001,333,320 | DISABLED test_non_equal_head_dims_score_mod2_bfloat16_head_dims1_cuda_bfloat16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_non_equal_head_dims_score_mod2_bfloat16_head_dims1_cuda_bfloat16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/run... | true |
3,001,333,257 | DISABLED test_builtin_score_mods_float16_score_mod0_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_float16_score_mod0_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40688574924)... | true |
3,001,333,256 | DISABLED test_builtin_score_mods_different_block_size_float32_score_mod5_BLOCK_SIZE_128_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float32_score_mod5_BLOCK_SIZE_128_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,001,333,173 | DISABLED test_builtin_score_mods_different_block_size_float16_score_mod2_BLOCK_SIZE_256_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float16_score_mod2_BLOCK_SIZE_256_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
3,001,333,102 | DISABLED test_non_equal_head_dims_score_mod2_float32_head_dims0_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_non_equal_head_dims_score_mod2_float32_head_dims0_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/... | true |
3,001,333,064 | DISABLED test_remove_noop_view_default_cpu (__main__.CpuTests) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: fx"
] | 7 | NONE | Platforms: mac, macos, rocm, asan, linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_remove_noop_view_default_cpu&suite=CpuTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40693605627).
... | true |
3,001,333,014 | DISABLED test_remove_noop_view_default_cuda (__main__.GPUTests) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: fx"
] | 6 | NONE | Platforms: rocm, linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_remove_noop_view_default_cuda&suite=GPUTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40693605634).
Over the past 3 h... | true |
3,001,249,322 | [inductor] [cpu] [edge case] When processing `torch.nan_to_num-.long()`, inductor outputs the `reciprocal` of eager | shaoyuyoung | open | [
"oncall: pt2",
"oncall: cpu inductor"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**: First, using `torch.nan_to_num` to process `float("inf")` outputs correct res. But after using `.long()` to convert the dtype. CPU inductor outputs **reciprocal** results.
**device backend**: only CPP
**repro**
```python
import torch
import torch.nn as nn
import torch.nn.functiona... | true |
3,001,234,292 | [Inductor] Remove singleton tiling splits when prefer_nd_tiling=True | blaine-rister | closed | [
"topic: not user facing"
] | 2 | CONTRIBUTOR | # Issue
Users who want block pointers are like to use the config settings `{"trition.use_block_ptr": True, "triton.prefer_nd_tiling": True, "triton.max_tiles": 3}` . Among other things, these settings allow us to generate 3D block pointers for broadcasts. However, broadcasts often end up introducing a superfluous tili... | true |
3,001,225,119 | [Inductor] Remove singleton tiling splits when prefer_nd_tiling=True | blaine-rister | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | # Issue
Users who want block pointers are likely to use the config settings `{"trition.use_block_ptr": True, "triton.prefer_nd_tiling": True, "triton.max_tiles": 3}` . Among other things, these settings allow us to generate 3D block pointers for broadcasts. However, broadcasts which don't truly require 3D often end up... | true |
3,001,217,597 | [BE] follow autoformating and linter | XilunWu | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 11 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151507
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,001,210,864 | [inductor][test] Skip triton tests for MPS as well, also change reason for skipping SM89 to not IS_BIG_GPU | henrylhtsang | closed | [
"Merged",
"Reverted",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148622
* __->__ #151506
Differential Revision:
[D73162091](https://our.internmc.facebook.com/intern/diff/D73162091/)
Combining / improving https://github.com/pytorch/pytorch/pull/150485 and https://github.com/pytorch/pytorch/pull/15034... | true |
3,001,208,223 | FSDP2 tutorial outline | weifengpy | open | [
"oncall: distributed",
"triaged"
] | 5 | CONTRIBUTOR | ### 📚 The doc issue
draft the FSDP2 turorial similar to FSDP1's https://pytorch.org/tutorials/intermediate/FSDP_tutorial.html, with code example in [pytorch/examples](https://github.com/pytorch/examples)
basics using [Transformer model](https://github.com/pytorch/pytorch/blob/f5851efed99db3f3509982dda8680c1b60882c6e... | true |
3,001,203,942 | [inductor][test] Skip triton tests for MPS as well, also | henrylhtsang | closed | [
"fb-exported",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151504
Differential Revision: [D73162091](https://our.internmc.facebook.com/intern/diff/D73162091/)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chen... | true |
3,001,155,646 | [DDP] add one option to allow skipping all reduce unused parameters | zhaojuanmao | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)",
"release notes: distributed (checkpoint)"
] | 9 | CONTRIBUTOR | Summary: add one option to allow skipping all reduce unused parameters, this could help improve training throughput significantly when the number of unused parameters is large in the model.
Test Plan: unit tests, CI
Differential Revision: D72282069
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wcon... | true |
3,001,154,526 | [standalone_compile] Some misc fixes | zou3519 | 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):
* __->__ #151502
* #151551
* #151501
This PR fixes two things.
The first problem is that in the vLLM style standalone_compile is
called from within a custom torch.compile backend. If there already is a
FakeTensorMode (which there is), we shou... | true |
3,001,154,465 | [standalone_compile] Don't check if path is directory if it doesn't exist | zou3519 | closed | [
"Merged",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151502
* #151551
* __->__ #151501
os.path.isdir(path) will return False if the path doesn't exist.
Test Plan:
- new test
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisun... | true |
3,001,127,472 | deferring unbacked floats runtime assrtions not working ! | laithsakka | open | [
"triaged",
"oncall: pt2"
] | 2 | CONTRIBUTOR | repo:
```
import torch
torch._dynamo.config.capture_scalar_outputs = True
@torch.compile(fullgraph=True)
def func(a, b):
# f
torch._check(b.item()*2==11)
return b*10
with fresh_inductor_cache():
func(torch.tensor([100]), torch.tensor([5.5]))
func(torch.tensor([5]), torch.tensor([1.8]))
```
c... | true |
3,001,124,705 | [ez] fix code owners typo | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151422
* #151421
* __->__ #151499
| true |
3,001,119,517 | [SymmMem] Add all-to-all | kwen2501 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151993
* #151819
* __->__ #151498
* #151261
Add an all-to-all impl based on NVSHMEM's on-stream API `nvshmemx_alltoallmem_on_stream`.
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,001,119,495 | [cp] dispatch flex_attention to CP impl in TorchDispatchMode | XilunWu | open | [
"oncall: distributed",
"ciflow/inductor",
"module: context parallel",
"release notes: context parallel"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152311
* __->__ #151497
## Test
`pytest test/distributed/tensor/test_attention.py -s -k test_ring_flex_attention`
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,001,119,456 | [BE] follow autoformating and linter | XilunWu | closed | [
"oncall: distributed",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151497
* __->__ #151496
* #151495
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,001,119,415 | [dtensor][view_op] add as_strided op support to DTensor in FakeTensorMode | XilunWu | open | [
"oncall: distributed",
"topic: not user facing",
"ciflow/inductor",
"module: dtensor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151495
## Introduction
`flex_attention`'s FakeTensor propagation `flex_attention_fake_impl` [permutes](https://github.com/pytorch/pytorch/blob/fb6ac2f16132f7953711ce6924bc2ee4a033228c/torch/_higher_order_ops/flex_attention.py#L... | true |
3,001,086,170 | Do not do proper const fold during tensorify_python_scalars | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151494
Chatting with Bob the goal of this is to const fold the floats that where tensorified by calling
guard_scalar(val) on them and then replacing their usages by their values.
Hence we do not need to do this for nodes with no ... | true |
3,001,062,536 | [executorch hash update] update the pinned executorch hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | COLLABORATOR | This PR is auto-generated nightly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/nightly.yml).
Update the pinned executorch hash. | true |
3,001,045,667 | Fix has_free_symbols | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151604
* #151494
* __->__ #151492
* #151171
* #151170
used to fail for
self.assertFalse(has_free_symbols(sympy.S.true))
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
3,001,043,324 | [dynamic shapes] data-dependent error when backed + unbacked expression resolves statically | pianpwk | open | [
"triaged",
"oncall: pt2",
"module: dynamic shapes"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Reported by @ColinPeppler
Getting this log, suggesting we can simplify the expression to False with the backed hint, but still data-dependent errors out:
```
torch.fx.experimental.symbolic_shapes.GuardOnDataDependentSymNode: Could not guard on data-dependent expression False (unhinted: Ne(Mod... | true |
3,001,026,302 | faster gather implementation | ngimel | closed | [
"oncall: distributed",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: cuda",
"ciflow/rocm",
"ci-no-td"
] | 12 | COLLABORATOR | So far it's only for `gather`, but we'll move index_select and index to this implementation too. Torchtitan and fbgemm have noticed that gather/index_select perf is bad, this PR brings core implementation to be on par with those customized implementations. Added benefits: all dtypes are supported, a bit less strict on ... | true |
3,001,006,754 | Use reusable binary docker build action for manywheel | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | This is part of splitting up https://github.com/pytorch/pytorch/pull/150558 into smaller chunks, please see that for more context
Similar to https://github.com/pytorch/pytorch/pull/151483 but for manywheel
Changed the job name
s390x doesn't have access to aws ecr so it doesn't use the action. manylinuxs390x-b... | true |
3,000,962,991 | Use reusable binary docker build action for libtorch | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | This is part of splitting up https://github.com/pytorch/pytorch/pull/150558 into smaller chunks, please see that for more context
Similar to https://github.com/pytorch/pytorch/pull/151483 but for libtorch
Changed the job name
Testing:
Can't really test since PRs don't have the credentials to push to docker io... | true |
3,000,934,385 | Add option to use mempool on OOM | dsjohns2 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 16 | CONTRIBUTOR | MemPool is a separate pool of memory handled by the caching allocator. This PR adds the option let the caching allocator try to use this pool as a last resort instead of OOMing by associating a use_on_oom bool with each MemPool.
Usage:
Users can optionally specify a ``use_on_oom`` bool (which is False by default) d... | true |
3,000,910,675 | RuntimeError: d.is_cuda() INTERNAL ASSERT FAILED at "/pytorch/c10/cuda/impl/CUDAGuardImpl.h" | Javen-W | open | [
"module: dataloader",
"module: cuda",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
I'm trying to train a Diffusion model but I'm inconsistently encountering segfaults, system crashes, or the following RuntimeError specifically in the `train_one_epoch()` and `mix_data()` functions, preventing any progress from being made. I've tried different versions of Python, PyTorch, Linux... | true |
3,000,885,440 | c10d/Store: add nonblocking mode to queue_pop | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 18 | MEMBER | This adds a non-blocking mode to queue_pop. This allows for workers to poll if work is ready without blocking the main loop. This is useful for the case where you want to have a GPU have maximum utilization when something only periodically is sent on the queue.
We also expose a `torch.distributed.QueueEmptyError` so... | true |
3,000,873,749 | Add torch.cuda._compile_kernel() | msaroufim | closed | [
"module: cuda",
"Merged",
"ciflow/trunk",
"release notes: cuda"
] | 15 | MEMBER | Followup work on top https://github.com/pytorch/pytorch/pull/149480
Wrapper on top of nvrtc inspired by https://gist.github.com/malfet/2c9a25976dd7396430c38af603f791da from @malfet
Compiling toy kernels with this setup takes 0.01s vs 90s using `load_inline()` on my local H100. This was primarily motivated by the ... | true |
3,000,858,764 | Use reusable binary docker build action for almalinux, clean up script | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | This is part of splitting up https://github.com/pytorch/pytorch/pull/150558 into smaller chunks, please see that for more context
Use the binary docker build action from https://github.com/pytorch/pytorch/pull/151471
Change the workflow trigger to be all of .ci/docker so it will make a new image + tag whenever it... | true |
3,000,841,141 | [MegaCache] Rename the PGO artifact when used between different jobs | oulgen | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151482
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,000,822,982 | inductor.config.descriptive_names = False is not actually supported (#145523) (#146051) | exclamaforte | open | [
"fb-exported",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: deprecation",
"module: inductor",
"ciflow/inductor",
"release notes: inductor",
"ci-no-td"
] | 11 | CONTRIBUTOR | Summary:
This config is not supported (it throws an error when set), and doesn't really make sense imo.
Approved by: https://github.com/eellison
Test Plan: contbuild & OSS CI, see https://hud.pytorch.org/commit/pytorch/pytorch/edf266e9bbbf6063f7c4a336ffb50234e11a0a82
Reviewed By: masnesral
Differential Revision: D... | true |
3,000,812,947 | Some way to branch on dynamic vs static shapes in user code | zou3519 | closed | [
"triaged",
"oncall: pt2",
"module: dynamic shapes",
"vllm-compile"
] | 0 | CONTRIBUTOR | Motivation: Sometimes users want to say "if shape is provably greater than X, use an optimized kernel. otherwise fall back to a more general kernel". When they're compiling over said code using dynamic shapes, it's fine to fallback to the general kernel. When they compile with static shapes, they want the best perf an... | true |
3,000,812,284 | [map] defer importing AOTConfig and create_joint dependency | ydwu4 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 8 | CONTRIBUTOR | Summary:
We reverted D72896450 due to a weird error happens at a seemingly unrelated test "buck2 run apf/data/tests:preproc_state_serializer_test -- --filter-text "test_load_artifact"
"
I did some investigation and found that moving import AOTConfig and create_joint inside the create_fw_bw_grap causes a delay of impo... | true |
3,000,803,372 | [PT2] torch.layer_norm errors in eager but runs fine in backend=aot_eager_decomp_partition | weifengpy | open | [
"module: error checking",
"triaged",
"enhancement",
"oncall: pt2",
"module: decompositions"
] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
torch.layer_norm throws error when input and weight are in different dtypes. However, it runs fine with backend=aot_eager_decomp_partition, because of decomposation of torch.layer_norm into fp32 ops
we run into this because online job disable pt2, but offline training requires... | true |
3,000,776,759 | [fake tensor cache] Support index with non bool/int8 indices | anijain2305 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"ci-no-td"
] | 19 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152062
* #151961
* #151957
* __->__ #151477
* #151633
* #151409
| true |
3,000,760,837 | [export] export doesn't save custom meta for constant tensors | angelayi | closed | [
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
def test_run_decomp_custom_constant(self):
class M(torch.nn.Module):
def __init__(self):
super().__init__()
self.b = torch.ones(3, 3)
def forward(self, x):
return self.b + x
... | true |
3,000,729,945 | [c10d][fr] Fix script for uneven reduce scatter and update test cases | fduwjj | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151475
Somehow the type string for reduce scatter is "REDUCE_SCATTER" not "REDUCESCATTER". This PR fixed it and added more test cases.
cc @H-Huang @awgu @wanchaol @fegin @wz337 @wconstab @d4l3k
Differential Revision: [D7314124... | true |
3,000,721,229 | Use more efficient row/col computation | aartbik | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | This change addresses the first/second time/mem "spike" observed in
https://github.com/pytorch/pytorch/issues/151351
Fixes #151351
| true |
3,000,720,162 | Update README.md - James has the wrong github link. | ebetica | open | [
"triaged",
"open source",
"topic: not user facing",
"merging"
] | 5 | CONTRIBUTOR | Unless I'm wrong, the James on the pytorch paper is not the account linked to in the README.md. | true |
3,000,711,150 | [MegaCache] Encode key in base64 | oulgen | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151472
I have noticed that there are some errors like
```
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x95 in position 169302: invalid start byte
```
I havent been able to repro this locally yet, this change should fix... | true |
3,000,709,486 | Action for building docker binary builds | clee2000 | closed | [
"Merged",
"topic: not user facing"
] | 4 | CONTRIBUTOR | This is part of splitting up https://github.com/pytorch/pytorch/pull/150558 into smaller chunks, please see that for more context
Uses calculate docker image with the new custom tag prefix, so the naming convention of the docker images is slightly different for images built on PR
based off of https://github.com/p... | true |
3,000,676,892 | Key error for _tensorify_python_scalars | BoyuanFeng | open | [
"triaged",
"oncall: pt2",
"module: dynamic shapes"
] | 2 | CONTRIBUTOR | Repro:
```python
import torch
torch._dynamo.config.capture_scalar_outputs = True
def f(x, y):
x1 = x + 1
y_scalar = y.item()
z = x1 + y_scalar
return z, y_scalar
f = torch.compile(f)
f(torch.randn(2,3, device='cuda'), torch.tensor(3.0, device='cuda'))
```
Error:
```
/data/users/boyuan/pytorch/torc... | true |
3,000,667,037 | Include post grad gm and fx runnable in cache artifacts for tlparse | oulgen | 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):
* __->__ #151469
Fixed #151462
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,000,625,237 | Bug At `d\\dependencies\\libtorch\\include\\ATen\\core\\jit_type_base.h":289` | tslever | open | [
"oncall: jit"
] | 0 | NONE | ### 🐛 Describe the bug
I receive the following log when running https://github.com/tslever/Settlers_Of_Catan/tree/main/back_end as of commit `cb8e64063c91ef9c9b78829f577d5e52816b0623` in Debug mode.
`[INFO][Wed Apr 16 13:52:59 2025]d\\dependencies\\libtorch\\include\\ATen\\core\\jit_type_base.h":289, please report a... | true |
3,000,594,091 | [nativert] Add utility function to convert strings into numbers. | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 29 | CONTRIBUTOR | Summary:
nativert RFC: https://github.com/zhxchen17/rfcs/blob/master/RFC-0043-torch-native-runtime.md
To land the runtime into PyTorch core, we will gradually land logical parts of the code into the Github issue and get each piece properly reviewed.
This diff adds a small library to convert strings into number... | true |
3,000,542,953 | Use /var/tmp instead of /tmp for torch cache directory on fbcode | oulgen | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Summary:
We've been noticing that cache directory has been getting cleaned underneath us, lets use /var/tmp which is supposed to be cleaned less frequently.
https://fb.workplace.com/groups/257735836456307/posts/883428143887070
Test Plan: unit tests
Reviewed By: masnesral
Differential Revision: D73008663
cc @voz... | true |
3,000,535,393 | [ROCm] Initial plumbing for CK Gemm Perf Improvement | alugorey | open | [
"module: rocm",
"triaged",
"open source",
"ciflow/rocm",
"ciflow/rocm-mi300"
] | 2 | CONTRIBUTOR | Re-organizes CK gemm code into it's own folder as well as adds logic to call ck gemm with specific templates based on the size of the input tensors.
Logic pulled for gemm selection was pulled directly from:
https://github.com/pytorch/FBGEMM/blob/main/fbgemm_gpu/experimental/gen_ai/src/gemm/ck_extensions.hip#L197-L2... | true |
3,000,522,564 | [ez] Don't always pass HF token to fsspec | ankitageorge | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"release notes: distributed (checkpoint)"
] | 8 | CONTRIBUTOR | Summary: The HF storage reader/writer component can work for any back-end in theory, so we shouldn't enforce the token to be passed into fsspecreader/writer, because the specific fsspec implementation may not handle tokens. Specifically, manifold doesn't accept a token arg, but we're passing one in always, which is thr... | true |
3,000,513,810 | Inconsistent Output from nn.Conv2d with padding_mode='circular' When Using MKLDNN on a AVX2_Processor | alino93 | open | [
"module: cpu",
"triaged",
"module: mkldnn"
] | 0 | NONE | ### 🐛 Describe the bug
I have encountered an issue with the `PyTorch nn.Conv2d` layer when using `padding_mode='circular'`. The output from the convolution operation differs depending on the state of `torch.backends.mkldnn.enabled`. Specifically, the outputs are inconsistent when MKLDNN is enabled versus when it is d... | true |
3,000,508,514 | inductor post_grad graphs are missing from tlparse on an FxGraphCache hit | bdhirsh | closed | [
"oncall: pt2"
] | 1 | CONTRIBUTOR | here's an example tlparse i'm trying to debug: https://manifold.edge.x2p.facebook.net/v0/read/tree/logs/f710880237-TrainingApplication_D9U2F/attempt_2/version_0/rank_0/index.html?bucketName=tlparse_reports&apiKey=tlparse_reports-key&withPayload=1&timeoutMsec=10000
I would really like to see what the post_grad graphs l... | true |
3,000,493,291 | CreateBlockMask producing invalid XBLOCK shape | drisspg | open | [
"high priority",
"triaged",
"oncall: pt2",
"module: inductor",
"vllm-compile"
] | 0 | CONTRIBUTOR | # Summary
Similar to: https://github.com/pytorch/pytorch/issues/145074
Repro:
https://github.com/vllm-project/vllm/pull/16078
``` Python
VLLM_USE_V1=1 VLLM_ATTENTION_BACKEND=FLEX_ATTENTION_VLLM_V1 VLLM_ENABLE_V1_MULTIPROCESSING=0 python benchmarks/benchmark_throughput.py --input-len 1024
```
Produces:
```Shell
[rank... | true |
3,000,447,622 | [MPS] Migrate `bitwise_not` to unary operator | malfet | closed | [
"Merged",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150661
* __->__ #151460
That kills to birds with one stone:
- Makes implementations more standartized (and faster for strided inputs/outputs)
- Fixes bug strided inplace bitwise_not
I.e. before this change
```python
import torch
x=torch.... | true |
3,000,328,931 | FlexAttention add decorator for large test cases | drisspg | 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):
* __->__ #151459
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,000,220,727 | Simplify symints before passing to FXGraphCache | jamesjwu | closed | [
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151458
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,000,102,812 | When distributed.destroy_process_group() is executed, new memory usage will be generated on device 0, which may cause OOM under extreme conditions and thus abnormal exit. | Staten-Wang | open | [
"oncall: distributed",
"triaged"
] | 1 | NONE | ### 🐛 Describe the bug
You should adjust max_i so that mem_consumer almost completely consumes GPU memory.
At this time, executing distributed.destroy_process_group() may cause OOM.
From what I've observed, this seems to be related to the order in which different 'ranks' execute destroy_process_group.
You can see t... | true |
3,000,078,957 | Add OIDC permissions to bazel workflow | zxiiro | open | [
"triaged",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ci-no-td"
] | 11 | COLLABORATOR | Update workflow to use OIDC authentication to access AWS resources rather than assuming the runner's default role. This is part of the multicloud effort to prepare jobs to support being run in non-AWS clouds.
The JWT ID token requires `id-token: write` in order to create the token for the job. See: https://docs.gith... | true |
2,999,997,751 | Add OIDC permissions to xpu workflow | zxiiro | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu"
] | 8 | COLLABORATOR | The reusable workflow requires OIDC authentication to work and is configured via it's only caller xpu.yml however setting it here too to clarify that it is required. This setting also flags jobs that call this workflow without the required permissions set to remind them it need to be set.
JWT ID token requires `id-t... | true |
2,999,996,794 | Broken Links GHA | sekyondaMeta | closed | [
"module: docs",
"release notes: releng"
] | 1 | CONTRIBUTOR | Adding Github Action that runs monthly and checks for broken links in repo. If broken links exist, it creates an issue with a list of the links
<img width="1319" alt="Screenshot 2025-04-15 at 13 39 51" src="https://github.com/user-attachments/assets/d42ba1ee-83ce-422c-8ac4-f5267e887b52" />
cc @svekars @AlannaBurk... | true |
2,999,927,479 | [BE] Remove outdated script to check namespace BC | janeyx99 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"suppress-bc-linter"
] | 6 | CONTRIBUTOR | Now that we have bc_lint in CI, this script is no longer needed (nor has it ever been conclusive). I've already updated the Runbook to not need this script.
Suppressing bc_lint as this script is not shipped as a part of torch--it is not user facing! For context, this script is (rarely) used by the release notes mana... | true |
2,999,913,231 | Add default value for `serialization_format` in `_write_item` function for better compatibility | BestJuly | open | [
"oncall: distributed",
"triaged",
"open source",
"release notes: distributed (checkpoint)"
] | 2 | NONE | The [861d2cc](https://github.com/pytorch/pytorch/commit/861d2cc02cce860d789cfda644a366abb95b53a5) commit by @ankitageorge introduced `serialization_format` argument to replace the original `safe_tensors` argument in `_write_item` function. It is fine to use this in pytorch. However, for many other projects, e.g., a wid... | true |
2,999,822,361 | update fx.Interpreter error logging to check if submodules are GraphModules | bdhirsh | open | [
"fb-exported",
"release notes: fx",
"fx"
] | 2 | CONTRIBUTOR | Summary: update fx.Interpreter error logging to check if submodules are GraphModules
Test Plan: CI
Differential Revision: D73069078
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,999,768,273 | Compilation of the post-training quantized model using Nvidia ModelOpt is failing with the error: Unsupported — 'inline in skipfiles: QuantLinearConvBase.quantize_weight | abhayaps | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | NONE | ### 🐛 Describe the bug
Hi Team,
I’ve been experimenting with NVIDIA’s `modelopt` library for post-training quantization of the [Feature Tokenizer Transformer model](https://github.com/yandex-research/rtdl). I was able to successfully quantize the model using the following setup and code snippets:
---
### **Environ... | true |
2,999,759,565 | [MPSInductor] Add pow, log2 and FloorToInt ops | malfet | closed | [
"Merged",
"topic: improvements",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151449
That enables `test_pow_by_natural_log2_dynamic_shapes_mps`
Not sure why log2 printer function suffix is `OpaqueUnaryFn_log2`, rather than just `log2`
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @Xiaob... | true |
2,999,672,402 | CUDA error on RTX 5090: no kernel image is available for execution on the device | thecangel | closed | [] | 3 | NONE | ### Summary
When trying to use PyTorch with an NVIDIA RTX 5090 GPU and CUDA 12.1, I receive the following error:
`RuntimeError: CUDA error: no kernel image is available for execution on the device`
This happens even when using the latest PyTorch Nightly builds:
### System Info
- GPU: NVIDIA RTX 5090 (sm_90)
- OS: Wi... | true |
2,999,626,711 | Allow to byteswap data when reading saved torch jit data | AlekseiNikiforovIBM | open | [
"oncall: jit",
"triaged",
"open source",
"release notes: jit"
] | 4 | COLLABORATOR | It looks like some pickled data is endian-dependent. Byteswap such data when needed.
Add testcases.
Fixes #151428
cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel | true |
2,999,571,695 | DISABLED test_max_autotune_cuda (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_max_autotune_cuda&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40636603929).
Over the past 3 hours, it has ... | true |
2,999,571,279 | DISABLED test_non_equal_head_dims_score_mod1_bfloat16_head_dims0_cuda_bfloat16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_non_equal_head_dims_score_mod1_bfloat16_head_dims0_cuda_bfloat16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/run... | true |
2,999,571,278 | DISABLED test_builtin_score_mods_different_block_size_float32_score_mod6_BLOCK_SIZE_128_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_different_block_size_float32_score_mod6_BLOCK_SIZE_128_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.c... | true |
2,999,411,947 | isin() on MPS backend raises error with mixed dtypes, unlike CPU/CUDA | manueldeprada | closed | [
"triaged",
"module: mps"
] | 2 | NONE | ### 🐛 Describe the bug
The MPS implementation of `torch.isin()` is not consistent with the CPU or CUDA behavior when input tensors have different but compatible dtypes (e.g., `int64` and `int32`).
```
> torch.isin(torch.tensor([1,2,3], dtype=torch.int64), torch.tensor(1,dtype=torch.int32))
tensor([ True, False, Fals... | true |
2,999,397,919 | Some PyTorch tensor functions silently change the default locale encoding | youkaichao | open | [
"module: cuda",
"triaged",
"module: jiterator"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
A minimal reproducible example:
```python
import locale
import torch
def main():
print(locale.getpreferredencoding())
x = torch.tensor(1., device='cuda')
x.erfinv_()
print(locale.getpreferredencoding())
if __name__ == '__main__':
main()
```
Calling `erfinv_` will change th... | true |
2,999,314,370 | Implement fast exp for AVX2 and AVX512 for the flash attention | timocafe | open | [
"module: cpu",
"triaged",
"open source",
"topic: not user facing",
"module: sdpa"
] | 4 | NONE | **Implement fexp for avx2 and avx512**
Cristiano and all propose a clever exp using the IEEE representation with a fine control of the precision, especially useful
for mix computation of the flash attention.
- Implement Fast Exponential Computation on SIMD Architectures
A. Cristiano I. Malossi, Yves Ineichen,... | true |
2,999,292,982 | Inexact results of VMap operation due to optimization in linalg.solve | Flamefire | open | [
"module: numerical-stability",
"triaged",
"module: linear algebra",
"module: vmap",
"module: functorch"
] | 6 | COLLABORATOR | ### 🐛 Describe the bug
I've investigated #151113 and #114868 and traced the issue to `_linalg_solve_ex_out`.
It only happens on AMD CPUs but not on Intel CPUs in the scale that fails the test. It happens with both OpenBLAS and MKL although the differences are slightly different.
There is an ["optimization"](https:/... | true |
2,999,250,051 | Add is_pinned to host allocator | guangyey | open | [
"open source",
"ciflow/trunk",
"release notes: cpp",
"ciflow/mps",
"ciflow/rocm",
"ciflow/xpu"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151439
# Motivation
This PR aims to add the `is_pinned` functionality into the `HostAllocator` class, which enables centralized pinned memory verification through calls like `at::getHostAllocator(at::kCUDA)->is_pinned(ptr)`.
Benef... | true |
2,999,214,821 | add split sizes info dump for uneven all2all bw calculation | sanshang-nv | closed | [
"oncall: distributed",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)",
"skip-url-lint"
] | 24 | CONTRIBUTOR | Add split sizes info to dumped execution trace and kineto trace for bw calcuation of uneven all2all.
Take input data as an example from case below, although we know input size of Rank-0 is 50 elements, actual data size that Rank-0 sends out is (12+13+14)=39 elements. Rank-0 doesn't send the 1st chunk of 11 elements ... | true |
2,999,205,462 | Deprecate host allocator legacy APIs | guangyey | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151531
* #151439
* __->__ #151437
* #151431
# Motivation
This PR aims to deprecate the host allocator legacy API and recommend users to use the unified API `getHostAllocator(device_type)` APIs, such as:
```cpp
at::getHostAllocator(devic... | true |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.