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 |
|---|---|---|---|---|---|---|---|---|
2,905,222,405 | Add shim.h C API to call dispatcher on our own aten ops | janeyx99 | closed | [
"Merged",
"ciflow/trunk",
"release notes: cpp",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | This PR still needs testing through some cpp extension
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148832
* #148124
| true |
2,905,179,395 | FSDP2 and autocast compatibility issue | yjxiong | open | [
"oncall: distributed",
"triaged",
"module: fsdp"
] | 1 | NONE | ### 🐛 Describe the bug
# Bug Report: Composable FSDP (`fully_shard`) Loses Autocast Context During Checkpoint Recomputation
## Description
When using the composable FSDP API (`fully_shard`) with `torch.utils.checkpoint.checkpoint`, the autocast context is lost during the recomputation phase of the backward pass. Thi... | true |
2,905,176,430 | [import][fx] Move map_aggregate to C++ | jansel | closed | [
"ciflow/trunk",
"release notes: fx",
"fx",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Copy of #148243 for fbcode import
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,905,175,929 | torch.compile with mode = "max-autotune" raise error when using gradient checkpoint | efsotr | closed | [
"module: activation checkpointing",
"triaged",
"module: cuda graphs",
"oncall: pt2"
] | 5 | NONE | ### 🐛 Describe the bug
```python
import torch
from torch import nn
from torch.utils.checkpoint import checkpoint
class Linear(nn.Linear):
pass
# def forward(self, x):
# y = super().forward(x)
# return x + y
class Test(nn.Module):
def __init__(self):
super().__init__()
... | true |
2,905,073,976 | MiniCPM-o compilation issue | janak2 | open | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | NONE | ### 🐛 Describe the bug
MiniCPM-o model doesn't compile.
Here is the code to reproduce the error on Mac:
```python
import torch
from PIL import Image
import librosa
from transformers import AutoModel, AutoTokenizer
import os
import time
from torch._dynamo.testing import CompileCounter
from transformers.cache_utils im... | true |
2,905,037,743 | Inductor may permute inputs to flex attention, leading to assertion error | Aleko2286 | closed | [
"triaged",
"oncall: pt2",
"module: inductor",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 6 | NONE | ### 🐛 Describe the bug
For flex attention, inputs must be contiguous, but inductor seems to permute inputs under certain conditions which then results in an assertion error.
When using an Attention layer looking somewhat like this:
```python
class Attention(nn.Module):
def __init__(
self,
q_ch: ... | true |
2,905,035,734 | automatically convert _check(u>=0) to check_is_size(), export should suggest check_is_size() instead of _check(u>=0) when applicable | laithsakka | closed | [
"triaged",
"oncall: pt2",
"module: dynamic shapes",
"oncall: export"
] | 4 | CONTRIBUTOR | cc @chauhang @penguinwu @ezyang @bobrenjc93 @avikchaudhuri @gmagogsfm @zhxchen17 @tugsbayasgalan @angelayi @suo @ydwu4 | true |
2,904,983,475 | [DSD] Fix the shared parameter mismatch for optimizer state_dict when flattening FQNs are used | fegin | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (checkpoint)"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148825
Summary:
As title.
cc @H-Huang @awgu @kwen2501 @wanchaol @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,904,944,470 | Backout D70075331 | renganxu | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 12 | CONTRIBUTOR | Summary:
The AOTI lowering for model 699109736 and other new models worked before D70075331, but failed after with error "RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling cublasLtMatmul with transpose_mat1 1 transpose_mat2 0 m 4096 n 10 k 7936 mat1_ld 7936 mat2_ld 7936 result_ld 4096 abcType 2 comp... | true |
2,904,911,552 | Make dynamism code robust to NotImplementedException | bobrenjc93 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: fx",
"fx",
"ci-no-td"
] | 13 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148823
In prod many models have `@property` methods that raise
NotImplementedError. This PR updates our dynamism code to be more robust
to these types of models.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,904,821,374 | Add env for disabling meta reference on functionalization. | ysiraichi | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: lazy"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148822
Fix: https://github.com/pytorch/xla/issues/8755
This PR introduces `TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE`
environment variable. Setting this variable makes it so the
functionalization kernels won't run the meta refe... | true |
2,904,801,219 | Update decompositions_for_jvp.py | NinoRisteski | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | small typo thing that got my eye
Fixes #ISSUE_NUMBER
| true |
2,904,739,265 | Implement derivatives for nextafter operation | baskargopinath | open | [
"triaged",
"open source",
"release notes: autograd"
] | 10 | NONE | # Implement derivatives for nextafter operation
## Description
This PR implements the derivative for the `nextafter` operation, fixing issue #148814.
The derivative of `nextafter(x, y)` with respect to `x` is:
- 1.0 where x != y (since small changes in x result in proportional changes in output)
- 0.0 where x ... | true |
2,904,675,303 | addition of muon optimizer to torch.optim | SwamiKannan | closed | [
"module: optimizer",
"triaged"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
The Muon optimizer seems to be converging faster and with more stability than the Adam optimizer. Could you please consider adding it to the torch optimizers? Write-up [here](https://kellerjordan.github.io/posts/muon/) . Implementation [here](https://github.com/KellerJordan/Muo... | true |
2,904,656,471 | Fix typos in SpectralOps.cpp | csukuangfj | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | null | true |
2,904,602,180 | Remove numeric_limits::has_norm and numeric_limits::has_norm_loss | cyyever | open | [
"module: bc-breaking",
"triaged",
"open source",
"topic: not user facing"
] | 7 | COLLABORATOR | They are deprecated in C++23 and aren't used in computation.
See
https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2022/p2614r2.pdf
cc @ezyang @gchanan | true |
2,904,597,650 | Make dynamism checking code more robust | bobrenjc93 | closed | [
"fb-exported",
"release notes: fx",
"fx"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148816
Differential Revision: [D70834597](https://our.internmc.facebook.com/intern/diff/D70834597/)
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,904,591,002 | remove guard_size_oblivious from unbind. | laithsakka | open | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148815
unbind will always specialize on dim, because it determine the number of output tensors.
guard_size_oblivious is not useful there and more confusing probably for code readers
added a comment and a test that verifies th... | true |
2,904,563,055 | [Inductor] Error detected in NextafterBackward0. Traceback of forward call that caused the error | Cookiee235 | open | [
"module: autograd",
"triaged",
"oncall: pt2"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
### Reproducible Script
```python
```
### StackTrace
```
/data/qshenaf/miniconda3/envs/torch/lib/python3.13/site-packages/torch/autograd/graph.py:823: UserWarning: Error detected in NextafterBackward0. Traceback of forward call that caused the error:
File "/data/qshenaf/remote_pc/LLM4Convert... | true |
2,904,554,119 | [ONNX] Remove inaccurate test comment | justinchuby | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | Remove the comment that says jit trace strategy doesn't support dynamic shapes as dict because it does support it (which is what the test is testing)
| true |
2,904,550,506 | Bump jinja2 from 3.1.5 to 3.1.6 in /.ci/docker | dependabot[bot] | closed | [
"triaged",
"open source",
"topic: not user facing",
"dependency issue",
"python"
] | 2 | CONTRIBUTOR | Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.5 to 3.1.6.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a href="https://github.com/pallets/jinja/releases">jinja2's releases</a>.</em></p>
<blockquote>
<h2>3.1.6</h2>
<p>This is the Jinja 3.1.6 security release, which fixes security issues bu... | true |
2,904,477,750 | Custom Triton operator not registered when loading AOT-compiled .so in C++ environment | siluzhou-pku | open | [
"triaged",
"module: custom-operators",
"oncall: pt2",
"module: aotdispatch",
"module: pt2-dispatcher"
] | 2 | NONE | ### Description:
I'm encountering schema registration issues when using torch._export.aot_compile to compile a PyTorch model that includes custom Triton operators, the custom operators are not included in the compiled .so file. As a result, when the compiled .so works in Python with module imports, it fails in pure C... | true |
2,904,456,447 | avoid guard_size_oblivious in vector_norm | laithsakka | closed | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148810
* #148809
* #148430
| true |
2,904,456,407 | Remove guard_size_oblivious from vector_norm decomposition. | laithsakka | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 14 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148809
This PR remove the usage of guard_size_oblivious in vector_norm by inlining it in the runtime check,
this prevent any data dependent error from ever appearing here at the locations where guard_size_oblivious
used to exist.... | true |
2,904,437,368 | [Inductor] Inference failed with the compiled model with aminmax operator | Cookiee235 | open | [
"module: autograd",
"good first issue",
"triaged",
"oncall: pt2"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class SimpleModel(torch.nn.Module):
def __init__(self):
super(SimpleModel, self).__init__()
self.linear = torch.nn.Linear(10, 10)
def forward(self, x):
x = self.linear(x)
min_val, max_val = torch.aminmax(x)
x_normalized ... | true |
2,904,396,664 | Native Infinite Sampler for Datasets | shivakanthsujit | open | [
"feature",
"module: dataloader",
"triaged",
"module: data"
] | 0 | NONE | ### 🚀 The feature, motivation and pitch
Currently I don't think there is a native function in PyTorch that lets you sample from a fixed length dataset through an infinite length data loader. That is, if I define my ML loop in terms of number of gradient steps that I want to do, and just keep sampling batches from the... | true |
2,904,374,252 | [triton 3.3] support both specialize_impl and create_specialize_impl | davidberard98 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148806
After https://github.com/triton-lang/triton/pull/6099, we sometimes need to do `from triton.runtime.jit import specialize impl` and sometimes do `triton.runtime.jit.create_specialize_impl()`. This should fix a bunch of the new... | true |
2,904,349,072 | CUDACachingAllocator,c10d: fixes for IPC release performance | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 3 | MEMBER | This has two fixes to improve IPC tensor release performance when using torchft's BabyProcessGroupNCCL.
1. release the IpcMutex when deleting the `ExpandableSegements` object to avoid synchronizing under the lock
2. release the GIL in WorkNCCL destructor since the shared tensor will be destructed there
Test plan... | true |
2,904,342,734 | [export] Make aoti_call_delegate hop traceable | yiming0416 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: export"
] | 21 | CONTRIBUTOR | Summary: The `aoti_call_delegate` hop now uses a stateless `original_gm` for tracing with fake tensors and the OSS AOTI Runner for running with real tensors
Differential Revision: D70738393
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisu... | true |
2,904,339,202 | [export] Fix tensor_constant and buffer naming conflicts in TS converter | yiming0416 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 10 | CONTRIBUTOR | Summary: In TS converter, tensor constants are traced as BUFFER and later we will convert them back to CONSTANT_TENSOR. So we need to prevent naming conflicts during lift constant pass.
Test Plan: CI
Differential Revision: D70826426
| true |
2,904,329,514 | [CUDA][TF32] Account for tf32 in `test_efficient_conv_bn_eval` | eqy | closed | [
"module: cuda",
"open source",
"Merged",
"module: tf32",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | cc @ptrblck @msaroufim @zasdfgbnm @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,904,327,409 | [ca] always do initial trace with dynamic shapes | xmfan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 6 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149014
* #149064
* __->__ #148801
* #149030
* #148799
HUD: https://fburl.com/wzvx6tax no regressions (ignore the pass rate improvements, those come from #149030)
<img width="864" alt="image" src="https://github.com/user-attachments/assets... | true |
2,904,320,590 | [mm_logs] make aten mm info readable | YUNQIUGUO | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 16 | CONTRIBUTOR | Summary:
as title. make it into a table like
e.g. also see pic in test plan
| Name | M | N | K | Count |
| aten.mm | 16 | 6 | 16 | 1 |
...
Test Plan: {F1975907876}
<img width="1090" alt="Screenshot 2025-03-11 at 3 13 00 PM" src="https://github.com/user-attachments/assets/ffae8c56-e3... | true |
2,904,245,482 | [ca] support for dynamic shapes CopySlices | xmfan | closed | [
"Merged",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 4 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149014
* #149064
* #148801
* #149030
* __->__ #148799
i'm changing CA initial trace to always trace as dynamic, fixes these errors:
```python
This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
FAILED [0.2139s] te... | true |
2,904,243,457 | c10d/ProcessGroup: cleanup abort and shutdown | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 9 | MEMBER | This adds `abort` and `shutdown` to `Backend` and `ProcessGroup` objects. This simplifies the logic in `distributed_c10d.py` by having a default noop implementation for all PGs.
This will be useful for torchft and upcoming versions of NCCL which will handle abort correctly. Currently `torchft` would have to call int... | true |
2,904,240,844 | [cudagraph] add log for skip reasons | BoyuanFeng | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 10 | CONTRIBUTOR | Summary: Add skip reasons to dynamo_compile so we can know popular skip reasons for cudagraph
Test Plan: {F1975906635}
Differential Revision: D70820791
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchule... | true |
2,904,195,054 | [CUDA] try to abate some flakiness in `test_stream_event_nogil` | eqy | closed | [
"module: cuda",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | COLLABORATOR | threshold twiddling as one in a few dozen runs tend to fail the current threshold
cc @ptrblck @msaroufim | true |
2,904,194,620 | fix 144607, added ```SymInt``` type to the valid Layout size specification types | AmalDevHaridevan | open | [
"triaged",
"open source",
"topic: not user facing",
"module: inductor"
] | 2 | NONE | Fixes #144607
Added ```SymInt``` as a valid type for the stride specification. This type only appears as arg to the Layout ```__init___``` method when meta tensors are compiled.
# Test
```python
import os
os.environ.update(dict( TORCHDYNAMO_VERBOSE='1', ))
import torch
@torch.compile
def foobar(x):
... | true |
2,904,189,323 | Set specialized representation string for meta/fake tensor with empty construction | chajath | open | [
"Stale",
"topic: not user facing"
] | 4 | NONE | This is done so that the output of the representation is a valid pytorch code.
Now we can do:
```python
>>> import torch
>>> torch.empty((3,4), device='meta', dtype=torch.float64)
torch.empty((3, 4), device='meta', dtype=torch.float64)
```
Which allows to roundtrip repl with `eval`
Alternative is to all... | true |
2,904,182,876 | [MM] Add sm carevout to lowerings | 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):
* #148849
* __->__ #148793
# Summary
See https://github.com/pytorch/pytorch/issues/145115 for more details. I have been using
the following to verify, need to figure out how to do proper guarding
This does do the correct thing if w... | true |
2,904,180,038 | wire torch._scaled_mm with fp4 operands to the cublas nvfp4 kernel | vkuzo | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148792
* #148791
Summary:
When `a` and `b` have dtype `torch.float4_e2m1fn_x2` and `a_scale` and `b_scale` have dtype `torch.float8_e4m3fn`, makes
```python
c = torch._scaled_mm(a, b, a_scale, b_scale, out_dtype=torch.bfloat1... | true |
2,904,179,999 | add `torch.float4_e2m1fn_x2` to PyTorch | vkuzo | closed | [
"Merged",
"release notes: quantization"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148792
* __->__ #148791
Summary:
Redo of https://github.com/pytorch/pytorch/pull/146578 to get around
rebase conflicts.
Test Plan:
```
pytest test/quantization/core/experimental/test_floatx.py -s
```
Reviewers:
Subscribers:
Tasks:
Ta... | true |
2,904,161,383 | Set non-strict export as default mode | gmagogsfm | closed | [
"module: bc-breaking",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: bc breaking",
"release notes: export"
] | 35 | CONTRIBUTOR | Summary:
- Flip the default value of strict argument in torch.export.export from True to False
- Update test infra to cope with the change, some of them made the assumption of strict mode as default
- Disabled some tests that fail in non-strict mode
Test Plan: Sandcastle
Differential Revision: D70228628
cc @ezyang ... | true |
2,904,150,122 | [hop] Rework the check of Metadata in the functionalization key | bohnstingl | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 7 | COLLABORATOR | This PR is a more cosmetic rework of the metadata check performed by some HOPs.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames @ydwu4
| true |
2,904,085,492 | Add timm_efficientnet to flaky models after cuda 12.6 update in CI/CD | atalman | closed | [
"Merged",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | After https://github.com/pytorch/pytorch/pull/148612
This model have become flaky
Tracking this regression in an issue : https://github.com/pytorch/pytorch/issues/148699
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @c... | true |
2,903,978,166 | [dynamo] torch.compiler.disable(recursive=False) modifies the original function | williamwen42 | closed | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 0 | MEMBER | ```python
import torch
def f(x):
return x + 1
f_disabled = torch.compiler.disable(f, recursive=False)
torch.compile(f, backend="eager")(torch.ones(3))
```
Output:
```
TORCH_LOGS_FORMAT="" TORCH_LOGS="+dynamo" python playground.py
TorchDynamo attempted to trace the following frames: [
]
```
In this example,... | true |
2,903,946,273 | [cutlass backend][ez] Incorporate AOTI dynamic shape test into main test of MM | henrylhtsang | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148786
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,903,940,992 | [Upstream] Wrap log_2_e in tl.constexpr for new 3.3 bump | drisspg | closed | [
"Merged",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148793
* __->__ #148785
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,903,934,645 | [Minimizer] allow overriding of ShapeProp logic by subclasses of _MinimizerBase | qcyuan | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx"
] | 6 | CONTRIBUTOR | Summary:
The changes contained in this diff
- allow subclass Minimizer implementations to override the default shape propagation logic with custom logic
- copies over the meta attribute on get_attr graph nodes during the graph splitting step
- for both changes, behavior for existing classes do not change
Test Plan: CI... | true |
2,903,925,195 | [test] conda cmake | clee2000 | closed | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
2,903,872,144 | Delete duplicate entry from `docker-builds.yml` | malfet | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Regression introduced by merge conflict of https://github.com/pytorch/pytorch/pull/148612
| true |
2,903,860,174 | [Codemod][AddExplicitStrictExportArg] caffe2/test/inductor | gmagogsfm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Differential Revision: D70575053
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,903,857,402 | FSDP: use Work.wait instead of event for all reduce | d4l3k | open | [
"oncall: distributed",
"release notes: distributed (fsdp)",
"ciflow/inductor"
] | 20 | MEMBER | This uses Work.swait instead of using CUDA events for allreduce. This has some important performance considerations when using ProcessGroups that depend on CPU synchronization such as Gloo. By not calling `Work.wait` until the end this allows for all of the allreduce calls to be dispatched before we synchronize on any ... | true |
2,903,809,258 | [Export Benchmark] non-strict export doesn't work with .numpy on Kokoro model | tugsbayasgalan | open | [
"triaged",
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
class Foo(torch.nn.Module):
def forward(self, x):
a = x.numpy()
return x + x.numpy().sum()
foo = Foo()
foo(torch.randn(10, 10))
torch.export.export(foo, (torch.randn(10, 10),), strict=False)
Errors with:
File "/data/users/tmanlaibaatar/pytorch/torch/fx/exper... | true |
2,903,792,874 | Add ninja to requirements-ci for all arch | clee2000 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | So I can get ninja_logs for the builds
No negative consequences afaik | true |
2,903,709,799 | [inductor] Precompilation start time is the time when a config is added to the queue, not when executor starts compiling the config | henrylhtsang | closed | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
code pointer to start time: https://github.com/pytorch/pytorch/blob/main/torch/_inductor/select_algorithm.py#L1847
This means when we print the elapsed time, it is not accurate. https://github.com/pytorch/pytorch/blob/main/torch/_inductor/select_algorithm.py#L1808-L1812
repro:
go to select_al... | true |
2,903,701,199 | [BE] Combine `windows_arm64_binary_build.yaml.js2` with regular windows yaml | malfet | closed | [
"module: windows",
"module: ci",
"triaged",
"better-engineering"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
BE followup from https://github.com/pytorch/pytorch/pull/139760
Jinja templates are designed specifically to include/exclude shared parts based on the platform, so same template should be used for both x86 and arm64 builds
### Versions
CI
cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremy... | true |
2,903,679,596 | Calling `torch.linalg.lstsq` with a wrongly-shaped `out=output` argument does not properly reshape `output` | Bichidian | open | [
"triaged",
"module: linear algebra"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
The function `torch.linalg.lstsq` returns a named tuple `(solution, residuals, rank, singular_values)`. It accepts an `out=output` argument so the `output` is modified in-place. This `out` behavior is not documented, but it is tested in `test/test_ops.py`.
The function's main arguments are `A`... | true |
2,903,679,320 | Change nvcc arch flags for sm100 | danielvegamyhre | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"topic: build"
] | 8 | CONTRIBUTOR | ### Summary
- Addressing this comment https://github.com/pytorch/pytorch/pull/148274#discussion_r1984944012
### Test plan
- Verified building from source w/ B200s is successful
- Verified B200 tensorcores are still being utilized properly via benchmarking script
| true |
2,903,676,649 | cpp_wrapper: build non-performance-sensitive code at O1 | benjaminglass1 | open | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"release notes: inductor (aoti)"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149961
* __->__ #148773
* #144293
Builds on #148212, applying the same improvements to `cpp_wrapper` mode. Sample benchmark results on [A100](https://hud.pytorch.org/benchmark/compilers?dashboard=torchinductor&startTime=Mon%2C%2003%20Mar%2... | true |
2,903,665,951 | [torchbench] fix dynamic_shapes spec for moco | pianpwk | closed | [
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: export"
] | 7 | CONTRIBUTOR | Fixes https://github.com/pytorch/pytorch/issues/148333
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,903,612,776 | on-pr docker build stuck with `user is not authorized to BatchGetImage` | malfet | open | [
"module: ci",
"triaged",
"module: regression",
"module: docker",
"security"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
Build https://github.com/pytorch/pytorch/actions/runs/13724713611/job/38388317099?pr=148740 stuck at `Calculate docker image` step trying to check if such image already exists or not
```
+ [[ 1741362495 -lt 1741364292 ]]
+ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pyt... | true |
2,903,588,629 | the example program using libtorch is not linked against torch_cuda even when USE_CUDA is defined | mboedigh | open | [
"module: windows",
"module: cpp",
"module: cuda",
"triaged"
] | 0 | NONE | ### 🐛 Describe the bug
libtorch is not implicitly loading torch_cuda.dll.
```
#define USE_CUDA 1 // has no discernible effect. same behavior with and without.
#include <torch/torch.h>
#include <iostream>
#include <Windows.h>
int main() {
// LoadLibraryA("torch_cuda.dll"); // if this line is present, then cuda... | true |
2,903,586,226 | [inductor] fix matmul w/ torch.bucketize epilogue | davidberard98 | closed | [
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148769
See https://github.com/pytorch/pytorch/issues/148764.
Inductor was codegen-ing wrong shapes for bucketize when it was fused as an epilogue: the binary search helper function requested the shape of the input tensor, and I... | true |
2,903,580,645 | [aarch64] install ninja for docker to build triton on arm | tinglvv | closed | [
"open source",
"Merged",
"topic: not user facing"
] | 3 | COLLABORATOR | cc @atalman
| true |
2,903,566,585 | fix #147170 Sorting the input node | urstrulyvishtan | open | [
"triaged",
"open source",
"release notes: fx",
"fx"
] | 2 | NONE | Fixes #147170
This pull request makes several improvements to the `make_partition` function in the `torch/fx/passes/utils/source_matcher_utils.py` file. The changes focus on code clarity and ensuring deterministic behavior when handling input nodes.
Key changes include:
* Initialization and population of `input... | true |
2,903,553,061 | Implement `raise ... from ...` | guilhermeleobas | closed | [
"open source",
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 10 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150466
* #147990
* #146506
* #146501
* #146500
* __->__ #148766
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,903,552,852 | Set __context__/__cause__ when generator raise `StopIteration` | guilhermeleobas | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147990
* #146506
* #146501
* #146500
* #148766
* __->__ #148765
* #146505
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,903,472,585 | [inductor] torch.bucketize in fused epilogue throws `NameError('XBLOCK is not defined')` | davidberard98 | closed | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Repro:
```python
import torch
import torch
import torch._inductor.config
from torch._inductor.utils import fresh_inductor_cache
torch._inductor.config.max_autotune_gemm_backends = "TRITON"
def fn(x: torch.Tensor, y: torch.Tensor, buckets: torch.Tensor) -> torch.Tensor:
z = torch.mm(x, y)... | true |
2,903,409,776 | Suppress build warnings when gcc-11 is used | malfet | closed | [
"oncall: jit",
"Merged",
"NNC",
"release notes: jit"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148740
* __->__ #148763
By decorating the header with `C10_DIAGNOSTIC_PUSH_AND_IGNORED_IF_DEFINED("-Wmismatched-new-delete")`
that will suppress following (when building against ancient llvm-9)
```
In file included from /var/lib/jenk... | true |
2,903,322,985 | magma builds should be part of the docker image builds | malfet | open | [
"oncall: releng",
"module: ci",
"triaged",
"better-engineering",
"security"
] | 6 | CONTRIBUTOR | ### 🐛 Describe the bug
One of the followups from https://github.com/pytorch/pytorch/issues/148495
Currently magma are ingested in docker builds as unversioned artifacts
Those artifacts are produced by build-magma-linux.yml workflow that does not do any testing before publishing the binaries, nor version them, which ... | true |
2,903,179,737 | Fix redistribution cost for all-reduce | fmassa | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | MEMBER | This issue seems to have been introduced in https://github.com/pytorch/pytorch/pull/119897. With the current implementation, it might be more favorable to perform a reduce_scatter followed by an all-gather than simply an all-reduce.
Thanks @lw for the helpful discussions on getting this PR out!
cc @H-Huang @awgu @k... | true |
2,903,126,464 | Re-introduce -Wmaybe-uninitialized | cyyever | open | [
"triaged",
"open source",
"topic: not user facing",
"ciflow/periodic"
] | 2 | COLLABORATOR | See what fail | true |
2,902,858,014 | remove redundant calls to inc_pending_event_queries() and dec_pending_event_queries() in cuda graph mode | taozhiwei | closed | [
"oncall: distributed",
"open source",
"release notes: distributed (c10d)"
] | 1 | CONTRIBUTOR | In cuda graph mode, there is no need to call `inc_pending_event_queries ()` and `dec_pending_event_queries ()`
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,902,856,621 | Fix compile errors | cyyever | closed | [
"oncall: distributed",
"oncall: jit",
"open source",
"Merged",
"ciflow/trunk",
"release notes: jit",
"module: dynamo",
"ciflow/inductor"
] | 9 | COLLABORATOR | Fix
```
/usr/bin/../lib64/gcc/x86_64-pc-linux-gnu/14.2.1/../../../../include/c++/14.2.1/bits/unique_ptr.h:91:16: error: invalid application of 'sizeof' to an incomplete type 'torch::jit::AliasDb::WriteRegistry'
91 | static_assert(sizeof(_Tp)>0,
| ^~~~~~~~~~~
/usr/bin/... | true |
2,902,827,029 | Fix Wc++98-compat-extra-semi | cyyever | closed | [
"module: cpu",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,902,764,736 | FSPD ValueError: expected to be in states [<TrainingState.FORWARD_BACKWARD: 2>] but current state is TrainingState.IDLE | nikonikolov | open | [
"oncall: distributed",
"triaged",
"module: fsdp"
] | 19 | CONTRIBUTOR | I saw many reports online of this issue, but no 'minimal' reproduction. I have one below, which uses Gemma from `transformers` library. It's likely it's possible to have an even more minimal version of this (I have very limited capacity rn and couldn't minimize this even further, so bear in mind some parts might be unn... | true |
2,902,738,154 | [CD] Add triton xpu as dependency of torch xpu windows whl | chuanqi129 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 17 | COLLABORATOR | Depends on PR #147637 land
| true |
2,902,709,749 | [Inductor] Compilation the model with fold operator failed | Cookiee235 | closed | [
"oncall: cpu inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class FoldModel(torch.nn.Module):
def __init__(self, output_size, kernel_size, stride, padding):
super(FoldModel, self).__init__()
self.output_size = output_size
self.kernel_size = kernel_size
self.stride = stride
self.paddin... | true |
2,902,707,217 | Trunk workflow for Windows Arm64 | iremyux | open | [
"triaged",
"open source",
"ciflow/trunk",
"release notes: releng"
] | 7 | COLLABORATOR | This PR introduces the trunk workflow for Windows Arm64. | true |
2,902,700,689 | Compiling Flex Attention on CPU: torch._inductor.exc.InductorError: IndexError: tuple index out of range | JCBrouwer | open | [
"module: intel",
"oncall: pt2",
"module: higher order operators",
"oncall: cpu inductor",
"module: pt2-dispatcher",
"module: flex attention"
] | 6 | NONE | ### 🐛 Describe the bug
I'm interested in training with attention over variable length sequences on CPU. I'm using document masking similar to what's described here: https://github.com/pytorch-labs/attention-gym/blob/main/examples/flex_attn.ipynb
With the following code I'm running into an inductor error when compili... | true |
2,902,584,298 | [Inductor] Torch inductor pattern match breaks topological sort after replace the pattern | liji-nv | open | [
"triaged",
"oncall: pt2",
"module: inductor",
"inductor_pattern_match"
] | 0 | NONE | ### 🐛 Describe the bug
```python
import torch
import os
from typing import List, Optional, Union, Tuple
import torch
from torch._functorch.aot_autograd import aot_module_simplified
from torch._inductor.compile_fx import compile_fx
from torch.fx import Graph, GraphModule
from torch._inductor.pattern_matcher import ... | true |
2,902,574,839 | [pytree][easy] lock global registry containers properly for thread-safety | XuehaiPan | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: pytree"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148750
cc @zou3519 | true |
2,902,545,315 | Enable ASAN on inductor CUDA tests | cyyever | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | 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 |
2,902,364,563 | export deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B failed | FlintWangacc | open | [
"triaged",
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 3 | NONE | ### 🐛 Describe the bug
```python
from transformers import AutoFeatureExtractor, AutoModelForImageClassification from transforme... | true |
2,902,196,222 | How can I use inductor aot_compile to support a MoE network? | sujuyu | open | [
"oncall: pt2",
"export-triage-review",
"oncall: export",
"module: aotinductor"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
Deepseek has sparked a wave of enthusiasm for the design of Moe (Mixture of Experts) network architectures. I am often asked how to accelerate the inference of an Moe network. Undoubtedly, I thought of using Inductor's aot_compile to compile it into a dynamic library and then c... | true |
2,902,073,579 | Update torch-xpu-ops commit pin | xytintel | closed | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel",
"ciflow/xpu",
"release notes: xpu"
] | 6 | CONTRIBUTOR | Update the torch-xpu-ops commit to [ae267a5f249748adbac75d43ee36fc11040e80e4](https://github.com/intel/torch-xpu-ops/commit/ae267a5f249748adbac75d43ee36fc11040e80e4), includes:
- Bugfixes of windows build
| true |
2,902,065,280 | Fix attempt https://github.com/pytorch/pytorch/issues/148498 | pradeepfn | open | [
"oncall: distributed",
"fb-exported",
"release notes: distributed (checkpoint)"
] | 3 | CONTRIBUTOR | Differential Revision: D70757404
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,901,995,570 | [FlexDecode] causes bogus assert w/ small seq-len and not sure what for | drisspg | closed | [
"release notes: nn",
"topic: bug fixes",
"module: inductor",
"ciflow/inductor",
"module: flex attention"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148744
fixes https://github.com/pytorch/pytorch/issues/148527
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @a... | true |
2,901,989,222 | torch.unique(t, dim=1, return_counts=True) does not work | aifartist | open | [
"triaged",
"module: python frontend"
] | 5 | NONE | ### 🐛 Describe the bug
torch.unique(t, dim=1, return_counts=True) does not work
The "value" result still has dup's for each row(dim=1) and only one set of counts is returned instead of one for each row.
```
import torch
t = torch.tensor([[1, 1, 7, 3, 7, 7, 3], [2, 2, 2, 6, 6, 4, 3]])
print(torch.unique(t, dim=1, r... | true |
2,901,988,936 | [DRAFT][Reshape] Guard-free reshape for contiguous tensors to avoid data dependent errors. | laithsakka | open | [
"module: dynamo",
"ciflow/inductor",
"keep-going"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149266
* #148899
* #148893
* #148872
* __->__ #148742
* #148815
* #148809
* #148430
Main reason for refactor is to avoid data dependent error that the default path have
this is because this new path have no checks on sizes.
Does this d... | true |
2,901,954,221 | Remove some Centos7 builds | cyyever | closed | [
"triaged",
"open source",
"topic: not user facing"
] | 4 | COLLABORATOR | It should be safe to remove them. And they distract grepping keywords to debug CI issues. | true |
2,901,946,897 | [BE] Move cuda12.6 builds to gcc11 | malfet | closed | [
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"no-runner-experiments"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148740
I.e. `s/pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9/pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11/`
Which accidentally fixes undefined symbol references errors namely
```
/usr/bin/ld: /var/lib/jenkins/cpp-build/caffe... | true |
2,901,937,629 | [BE] Delete split builds | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #148740
* __->__ #148739
They has been disabled since Oct 2024, perhaps time to remove them from the workflows
See https://github.com/pytorch/pytorch/issues/138750 | true |
2,901,912,506 | Reduce the binary size of Intel GPU wheel package | chunhuanMeng | closed | [
"open source",
"topic: not user facing",
"module: xpu"
] | 9 | CONTRIBUTOR | Update the torch-xpu-ops commit to [8d58bd6c0ac86191aa375075e09e2b47fa957d39](https://github.com/intel/torch-xpu-ops/commit/8d58bd6c0ac86191aa375075e09e2b47fa957d39), includes:
- Bugfixes of windows build
cc @gujinghui @EikanWang @fengyuan14 @guangyey | true |
2,901,903,898 | gracefully handle `tokenize.TokenError` in funcname parser. Adds support for non-Python source | cat-state | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 5 | CONTRIBUTOR | This change allows defining python functions in non-python source and having them be able to compiled by torch.compile. The existing implementation already returns None for the case where the file couldn't be read, so returning None (by making an empty funcname cache) makes sense for the case of non-python source code ... | true |
2,901,896,354 | [dynamo] add recursive-only dont_skip_tracing (i.e. force_inline) | williamwen42 | closed | [
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"keep-going",
"module: compile ux"
] | 2 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148736
Implementation details:
- `external_utils._ignore_skip_function_variable` is a global that toggles whether we should ignore most skip rules.
- When active, `trace_rules.lookup_inner` will return `UserFunctionVariable` (i.... | true |
2,901,887,216 | Code Clean: Remove unnecessary code | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148735
As the title stated.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,901,885,397 | [Inductor UT][XPU] Skip test case test_cat_max_autotune_triton for known issue. | etaf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu"
] | 10 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #148734
The mm triton template/configs have not been tuned for XPU, we observer that the epilogue fusion can not speed up on XPU because of registers spill. So XPU failed on the case `test_cat_max_autotune_triton` which checks the fu... | true |
2,901,872,170 | [Inductor][Windows] add env_var switch to turn all Windows inductor UTs. | xuhancn | closed | [
"module: windows",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"intel",
"module: dynamo",
"ciflow/inductor",
"ciflow/xpu"
] | 12 | COLLABORATOR | For timeout reason, we can't turn on all Windows Inductor UTs in CI: https://github.com/pytorch/pytorch/issues/135927
And without the UTs, we can't ensure Windows inductor quality.
Intel team will do some local test for Windows inductor, but we still need to add a switch to turn on the full Windows inductor UTs.
... | true |
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