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 |
|---|---|---|---|---|---|---|---|---|
2,979,018,593 | Code Clean: Remove python3.8 specific code because PyTorch now need Python3.9 and later | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150839
* #150838
* __->__ #150834
As the title stated. | true |
2,978,918,930 | Pin all root requirements to major versions | jondea | open | [
"triaged",
"open source",
"topic: not user facing"
] | 2 | CONTRIBUTOR | Builds regularly fail due to major changes in build packages (most recently #150149), should we pin all the root [`requirements.txt`](https://github.com/pytorch/pytorch/blob/a106842ea8be6eb17b368de16d9c107c12b809bc/requirements.txt) to at least major version?
I made this a draft because I didn't really know the righ... | true |
2,978,905,041 | [inductor][cpu]functorch_dp_cifar10 AOTInductor AMP multiple thread performance regression in 2025-03-24 nightly release | zxd1997066 | open | [
"oncall: pt2",
"oncall: cpu inductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
<p>AOTInductor AMP multiple thread static 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... | true |
2,978,897,433 | [Quant][PT2E][X86] Enable annotation of aten.mul.tensor with X86InductorQuantizer | Xia-Weiwen | closed | [
"open source",
"release notes: quantization",
"intel"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150831
* #151112
**Summary**
This PR adds support of annotation of `aten.mul.tensor` in `X86InductorQuantizer`.
`mul` is not annotated by default. Users need to set the following to enable annotation of `mul`:
```python
quantize... | true |
2,978,891,788 | [Inductor UT][Break XPU] Fix UTs for XPU broken by community. | etaf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"keep-going",
"ciflow/xpu"
] | 11 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150830
* #149862
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,978,771,916 | [Accelerator][Chore] Use existing `acc` when raising an error | shink | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/mps",
"ciflow/rocm"
] | 4 | CONTRIBUTOR | As the title said, `acc` already exists so we just use it instead of calling `current_accelerator()` again.
cc: @albanD @guangyey @FFFrog | true |
2,978,708,667 | [ez] dynamo fix typo in comment | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151180
* #151179
* __->__ #150828
* #150755
* #150754
* #150753
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,978,706,354 | Update torch-xpu-ops commit pin | xytintel | closed | [
"module: cpu",
"triaged",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"keep-going",
"ciflow/xpu",
"release notes: xpu",
"ci-no-td"
] | 29 | CONTRIBUTOR | Update the torch-xpu-ops commit to [655fa9bc7f88ab5bd3766b5f2fd5b43989c2caca](https://github.com/intel/torch-xpu-ops/commit/655fa9bc7f88ab5bd3766b5f2fd5b43989c2caca), including:
- Update commit pin to xpu-ops main branch
- Fixes batch_norm numeric error by adding additional boundary check
- Enable two operators: fft... | true |
2,978,669,705 | [Codemod][AddExplicitStrictExportForTrainingInferenceArg] caffe2/torch/ao | gmagogsfm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: quantization",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Differential Revision: D72615631
| true |
2,978,669,379 | [pytorch] Remove numpy dependency from Knapsack Evaluator | basilwong | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 12 | CONTRIBUTOR | Summary:
The two implementations are functionally equivalent. They both calculate the memory budget at the knee point in the Pareto frontier using the same algorithm.
1. np.linspace -> basic list comprehension
2. runtime and memory values -> lists instead of numpy arrays
3. np.ptp -> max - min
4. np.norm -> diff with ... | true |
2,978,563,434 | [MPSInductor] Naive welford_reduce implementation | malfet | closed | [
"Merged",
"Reverted",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 13 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151155
* #151152
* #151151
* __->__ #150824
* #151042
Literal Python-to-Metal translation of
https://github.com/pytorch/pytorch/blob/85549fe6de3b9a980d1dc98dc57379501bd2bb18/torch/_inductor/runtime/triton_helpers.py#L217-L225
Fixed mi... | true |
2,978,550,962 | [export] Decomp failure when running `aten.item.default` | kisenaa | open | [
"module: onnx",
"oncall: pt2",
"oncall: export"
] | 1 | NONE | ### 🐛 Describe the bug
Trying to export yolo11 model to onnx with dynamo=True. But got an error:
```
Ultralytics 8.3.103 🚀 Python-3.12.9 torch-2.8.0.dev20250405+cu128 CUDA:0 (NVIDIA GeForce RTX 4080 Laptop GPU, 12282MiB)
YOLO11n summary (fused): 100 layers, 2,616,248 parameters, 0 gradients, 6.5 GFLOPs
PyTorch: ... | true |
2,978,511,972 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_int64 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 5 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_abs_fastpath_outplace_cuda_int64&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40141680405).
... | true |
2,978,479,909 | [CI] Run test_torchinductor for MPS device | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150821
There are only 118 failures atm, mark them all with xfail to avoid new regressions
Add `xfail_if_mps_unimplemented` decorator to distinguish between tests that call unimplemented eager op vs ones that fail for some other... | true |
2,978,471,498 | [Manylinux 2.28] Correct Linux aarch64 cuda binaries wheel name | pytorchbot | closed | [] | 1 | COLLABORATOR | Related to: https://github.com/pytorch/pytorch/issues/149044#issuecomment-2784044555
For CPU binaries we run auditwheel however for cuda binaries auditwheel produces invalid results . Hence we need to rename the file. | true |
2,978,458,541 | Optimize `ConvTranspose2d` stride description | zeshengzong | closed | [
"module: nn",
"module: convolution",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: nn",
"topic: docs"
] | 10 | CONTRIBUTOR | Fixes #150775
## Test Result
### Before
### After
cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki | true |
2,978,352,998 | [CUDA] Only use vec128 if CUDA version is newer than 12.8 | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | By addressing a feedback requested at https://github.com/pytorch/pytorch/pull/145746 | true |
2,978,330,968 | Expose bicubic mode for torch::nn::functional::grid_sample in LibTorch | inventshah | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: cpp"
] | 18 | CONTRIBUTOR | When bicubic interpolation was added to grid_sampler in #44780, `GridSampleFuncOptions` was not updated to allow a user to use bicubic mode in LibTorch, even though the function could handle it. This PR fixes the parity such that LibTorch's `torch::nn::functional::grid_sample` behaves the same as PyTorch's `torch.nn.f... | true |
2,978,310,493 | Do not depend on numpy during the import | basilwong | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Summary:
Related issue: https://github.com/pytorch/pytorch/issues/149681
We can follow up with a different implementation that does not use numpy(potentially with Torch primitives).
Test Plan:
pending:
contbuild & OSS CI
Differential Revision: D72609835
| true |
2,978,303,356 | [C10D] Document object collectives limitations | wconstab | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150880
* __->__ #150815
Adds louder warning labels in the doc page and docstring for object
collectives in hopes of raising awareness of several footgun issues
including accidental creation of cuda contexts by serializing and
sending 'd... | true |
2,978,271,107 | [graph partition] reorder to reduce #partitions for simple dependencies | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 3 | CONTRIBUTOR | This PR reduces #graph partitions by reordering nodes when the `should_partition` nodes have simple dependencies. Specifically, for `should_partition` nodes:
a. If a node has no dependency or only depends on graph inputs: move to the front. Use case is when we move symints to cuda tensor for PaddedTensorSubclass
... | true |
2,978,256,630 | add reduce_scatter to symm mem ops | ngimel | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | COLLABORATOR | + a few small fixes (don't error out on 0-element tensors, a few more checks for contiguous outputs, more threads for better perf).
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @xw285cornell
| true |
2,978,250,998 | [CUDA][cuBLAS] Aten GEMM overload for FP32 output from FP16/BF16 inputs | PaulZhang12 | closed | [
"Merged",
"ciflow/trunk",
"release notes: python_frontend",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150812
Enable FP32 output from FP16/BF16 GEMMs in aten with cuBLAS. Accumulation for these GEMMs are generally already done in FP32. Adds the functionality to the following aten operators:
* mm
* bmm
* addmm
* baddmm
Follow u... | true |
2,978,233,244 | Pytorch. is_impure() does not take any argument. Removed it | elpdumont | open | [
"fb-exported",
"release notes: fx",
"fx"
] | 4 | NONE | Summary:
D72427768 introduced an argument when calling `is_impure` (defined here: https://www.internalfb.com/code/fbsource/[00b3734ebfa7]/arvr/libraries/art/python/third_party/_python3.7/_win64/torch/fx/node.py?lines=509)
This broke our conveyor:
https://fb.workplace.com/groups/CTRLEngSupport/permalink/40458432024020... | true |
2,978,151,861 | [dynamo][guards] Print relational guards only once | isuruf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #140756
* __->__ #150810
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,978,126,801 | [export] Integrate meta kernel generation with draft-export | angelayi | closed | [
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 3 | CONTRIBUTOR | If a custom operator does not contain a fake impl, currently draft-export will use the real-tensor propagation to get an output for the operator and continue tracing. However if we retrace the exported model using `ep.run_decompositions`, or `export`, or run the exported program with fake tensors, we'll still fail beca... | true |
2,978,126,717 | Fix assert_tensor_meta | angelayi | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150809
* __->__ #150808
* #150807
* #150806
| true |
2,978,126,637 | Generate meta kernel with operator profiles | angelayi | closed | [
"module: custom-operators",
"Merged",
"release notes: composability"
] | 2 | CONTRIBUTOR | Added a context manager, `torch._library.fake_profile.register_fake_profile(op_profiles)`, where given an operator profile, it will generate and register a fake impl for the operator based on the operator profile.
The input to `register_fake_profile` is a dictionary mapping operator name to a set of profiles which ... | true |
2,978,126,545 | [custom ops] Override fake registration | angelayi | closed | [
"module: custom-operators",
"Merged",
"ciflow/trunk",
"release notes: composability"
] | 3 | CONTRIBUTOR | Added a flag, `allow_override`, to allow overriding existing kernel implementations in `torch.library.register_fake` `library.impl`. The default is false, where if a user tries to register a kernel to a dispatch key that already contains a kernel, it will error. This flag doesn't apply to CustomOpDefs, where overriding... | true |
2,978,125,024 | ONNX cannot save the XGBoost binary classifier properly when trained on an imbalanced dataset. | cugurm | closed | [] | 1 | NONE | ### 🐛 Describe the bug
ONNX cannot properly save an XGBoost binary classification model when it is trained on an imbalanced dataset.
When I create the dataset for the XGBoost binary classification model like this:
```
n_instances, n_features = 100_000, 300
X = np.random.rand(n_instances, n_features)
y ... | true |
2,978,109,353 | [Inductor] assert fallback output alignment | shunting314 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150804
* #150777
Previous PR (https://github.com/pytorch/pytorch/pull/150777) fixes the alignment problem for fallback kernel assuming meta kernel is correct. This PR handles the case that meta kernel is incorrect. Assertion is adde... | true |
2,978,101,665 | TEST CACHE | muchulee8 | closed | [
"topic: not user facing",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150803
* #150276
Summary:
Test Plan:
Reviewers:
Subscribers:
Tasks:
Tags: | true |
2,978,092,419 | Fix `-Wmissing-braces` in a few files | r-barnes | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: sparse"
] | 8 | CONTRIBUTOR | Test Plan: Sandcastle
Reviewed By: wenxin0319
| true |
2,978,084,429 | ProcessGroupGloo: support lazy_init | d4l3k | closed | [
"oncall: distributed",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: distributed (c10d)",
"ci-no-td"
] | 16 | MEMBER | This adds lazy initialization support to ProcessGroupGloo via `TORCH_GLOO_LAZY_INIT` or via `create_device(..., lazy_init=True)`
This is still a draft PR as there's one race condition when doing coalesced operations that needs to be fixed upstream in Gloo first. Depends on https://github.com/facebookincubator/gloo/p... | true |
2,978,060,210 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_int32 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_abs_fastpath_outplace_cuda_int32&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40123681853).
Over ... | true |
2,978,036,797 | FSDP in hybrid mode throws _saved_grad_shard error when backward is called on cross-rank all-gathered loss | TianyiXiong1998 | open | [
"oncall: distributed",
"triaged",
"module: fsdp"
] | 3 | NONE | Hi, I’m encountering a gradient error when using FSDP in hybrid sharding mode (i.e., ShardingStrategy.HYBRID_SHARD) during training. Here’s the setup and problem:
Setup:
• I am training with multiple ensemble members, distributed across ranks.
• Each rank holds 1 or more ensemble members.
• After local predictions a... | true |
2,978,030,056 | `all_gather_object` creates context for each gpu multiple times (leaks memory) | stas00 | closed | [
"oncall: distributed"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
When using `all_gather_object` it leaks many GBs of memory with 8 gpus the first time it's being used (no problem with `all_gather`) - it creates a new context for each gpu - so 7 times too many with 8 gpus. (64 contexts instead of 8 - can be observed with `nvidia-smi` showing 64 entries instea... | true |
2,977,969,306 | Add CPython tests for iter/sort | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* __->__ #150797
* #150796
* #150795
* #150794
* #150793
* #150791
* #150790
* #150789
* #150788
Tests:
* test_iter.py
* test_sort.py | true |
2,977,969,165 | Add CPython generator/contextlib tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* __->__ #150796
* #150795
* #150794
* #150793
* #150791
* #150790
* #150789
* #150788
Tests:
* test_generator.py
* test_generator_stop.py
* test_contextlib.py | true |
2,977,969,017 | Add CPython int/float tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* #150796
* __->__ #150795
* #150794
* #150793
* #150791
* #150790
* #150789
* #150788
Tests:
* test_int.py
* test_int_literal.py
* test_float.py | true |
2,977,968,813 | Add CPython math/cmath tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* #150796
* #150795
* __->__ #150794
* #150793
* #150791
* #150790
* #150789
* #150788
Tests:
* test_math.py
* test_cmath.py | true |
2,977,968,653 | Add CPython string tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* #150796
* #150795
* #150794
* __->__ #150793
* #150791
* #150790
* #150789
* #150788
Files:
* test_grammar.py
* test_string.py
* test_userstring.py | true |
2,977,968,495 | [Set] Add CPython set tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152991
* #152990
* #152908
* #152907
* #152989
* #152906
* #152905
* #152903
* #152902
* #152901
* #152904
* #152988
* #152987
* __->__ #150792
* #152900
* #153070
Tests:
* test_set.py
cc @albanD @voznesenskym @penguinwu @EikanWang @jgong5... | true |
2,977,968,335 | Add CPython dict tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* #150796
* #150795
* #150794
* #150793
* __->__ #150791
* #150790
* #150789
* #150788
Tests:
* test_dict.py
* test_ordered_dict.py
* test_userdict.py | true |
2,977,968,186 | Add CPython list/tuple tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* #150796
* #150795
* #150794
* #150793
* #150791
* __->__ #150790
* #150789
* #150788
Tests:
* test_list.py
* test_tuple.py
* test_userlist.py | true |
2,977,968,046 | Add CPython exception tests | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* #150796
* #150795
* #150794
* #150793
* #150791
* #150790
* __->__ #150789
* #150788
----
* test_baseexception.py
* test_exceptions.py
* test_exception_variations.py
* test_raise.py
* test_sys.py | true |
2,977,967,910 | Add CPython tests for unittest | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152015
* #150797
* #150796
* #150795
* #150794
* #150793
* #150791
* #150790
* #150789
* __->__ #150788
Tests:
* test_assertions.py | true |
2,977,967,759 | Add infra to run CPython tests under Dynamo | guilhermeleobas | closed | [
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"skip-pr-sanity-checks",
"module: dynamo",
"ciflow/inductor",
"ci-no-td",
"skip-url-lint"
] | 25 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150787
cc @albanD @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,977,938,223 | [Manylinux 2.28] Correct Linux aarch64 cuda binaries wheel name | atalman | closed | [
"Merged",
"ciflow/binaries",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Related to: https://github.com/pytorch/pytorch/issues/149044#issuecomment-2784044555
For CPU binaries we run auditwheel however for cuda binaries auditwheel produces invalid results . Hence we need to rename the file. | true |
2,977,929,091 | [docs] remove --recursive flag from readme | danielvegamyhre | closed | [
"Merged",
"ciflow/trunk",
"topic: docs",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Fixes #150745
See https://github.com/pytorch/pytorch/issues/150745#issuecomment-2784216663
Cloning with `--recursive` as shown in the docs prevents users from checking out commits from before NCCL was removed as a submodule.
| true |
2,977,917,656 | [Kineto] Enable OOM observer | mzzchy | closed | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary:
# Context:
To support the investigation of OOM issue of shampoo optimizer, we want to enable OOM observer to allow memento to export the snapshot when OOM happens to figure out what has been allocated/freed before it.
Test Plan:
Run this test with next diff.
```
buck run @//mode/opt kineto/libkineto/fb/mtia... | true |
2,977,903,919 | [BE] Fix Amp.metal compilation warning | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Deleting unused `uint tid` fixes
```
[114/1416] Compiling /Users/nshulga/git/pytorch/pytorch/aten/src/ATen/native/mps/kernels/Amp.metal to Amp_30.air
/Users/nshulga/git/pytorch/pytorch/aten/src/ATen/native/mps/kernels/Amp.metal:70:10: warning: unused parameter 'tid' [-Wunused-parameter]
uint tid [[thread_positi... | true |
2,977,879,921 | [invoke_subgraph] Preserve node meta | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150717
* __->__ #150782
* #150666
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,977,842,646 | [cutlass backend] Stop using GenerateSM80 for SM90 and SM100 | henrylhtsang | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150781
Not urgent.
We don't use the GenerateSM80 ops I believe.
For SM100, we could skip SM90 as well. But I don't have data for that.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe... | true |
2,977,829,899 | [MPS] Support ArgumentBuffer bindings from C++/Python | malfet | closed | [
"Merged",
"topic: improvements",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150780
To workaround limitation of 32-arguments per kernel and being able to eventually compile something like
```python
import torch
def foo(*args):
rc = torch.empty_like(args[0])
for arg in args:
rc += arg
r... | true |
2,977,785,538 | Decorator `skipIfXpu` disables tests when used on class | exclamaforte | open | [
"high priority",
"module: ci",
"module: tests",
"triaged",
"module: regression",
"module: testing"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
`skipIfXpu` is used on classes, for example in `test_autoheuristic.py`:
```python
@skipIfXpu(msg="AutoHeuristic doesn't currently work on the XPU stack")
class AutoHeuristicTest(TestCase):
```
If you try to run the tests:
```
(pytorch) $ python test_autoheuristic.py
-------------------------... | true |
2,977,741,109 | Add config option to force disable CompiledTritonKernel cache | jamesjwu | closed | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150778
We're unfortunately still seeing some flakiness internally in specific internal models: adding a disable CompiledTritonKernels cache feature to help mitigate.
The issue seems to be sucluded to this specific model: StaticCudaL... | true |
2,977,619,534 | [Inductor] fix alignement assumption for fallback | shunting314 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150804
* __->__ #150777
Inductor right now only works properly for fallback kernels producing aligned output.
When Inductor create layout for fallback kernel output, Inductor does not add the tensor offset to the layout [link](https://git... | true |
2,977,492,712 | [Async TP] reshape error for output of fused scaled_mm reduce scatter in certain case | danielvegamyhre | closed | [
"oncall: distributed"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Can't post stack trace since it is internal code, but the error is thrown on this line: https://github.com/pytorch/pytorch/blob/06e9deabb623e004eb6024e703a976c5748d51e6/torch/distributed/_symmetric_memory/__init__.py#L1331
The error states the target tensor size is not compatible with the targ... | true |
2,977,492,288 | ConvTranspose2d documentation should clarify behavior of stride > 1 (zero insertion) | EduardoLawson1 | closed | [
"module: docs",
"module: nn",
"module: convolution",
"triaged",
"actionable"
] | 2 | NONE | ### 📚 The doc issue
## 📌 Feature Request: Improve `ConvTranspose2d` Documentation (Stride > 1)
### Summary
Currently, the documentation for `torch.nn.ConvTranspose2d` does not clearly explain the behavior of the layer when `stride > 1`. In particular, it omits the fact that transposed convolutions with `stride > 1... | true |
2,977,451,209 | [Async TP] use original output shape determined by reshape node | danielvegamyhre | closed | [
"oncall: distributed"
] | 2 | CONTRIBUTOR | cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,977,418,574 | [cuda] Add new faster gammabeta backward kernel (#148605) (Reapply with launch bounds) | ahmadsharif1 | closed | [
"ciflow/trunk",
"release notes: nn"
] | 2 | CONTRIBUTOR | This is another attempt at re-applying because https://github.com/pytorch/pytorch/pull/150625 was reverted due to internal build failure which should now be resolved.
# Changes over the previous PR
This reverts commit 61a1f09 and adds `__launch_bounds__` to the kernel.
Previously I merged 114d404 that did not... | true |
2,977,281,846 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_int16 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_abs_fastpath_outplace_cuda_int16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40089822514).
... | true |
2,977,207,691 | [CI] Add XPU compiled check in CICD | chuanqi129 | closed | [
"open source",
"Merged",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 4 | COLLABORATOR | Address the suggestion from https://github.com/pytorch/pytorch/issues/150001#issuecomment-2753407421
| true |
2,977,042,906 | [Profiler][HPU] Enable profiler.key_averages().table() for HPU devices | wdziurdz | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Fixes #150769
| true |
2,977,038,493 | [Profiler][HPU] Assertion failure when calling profiler.key_averages().table() on HPU devices | wdziurdz | closed | [
"triaged",
"intel",
"module: hpu"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
profiler.key_averages().table() should be supported for HPU devices. Currently, calling it results in an assertion failure. Example call stack below:
```python
Traceback (most recent call last):
File "torch_profiler_chrome_tracer.py", line 57, in <module>
print(profiler.key_averages().tab... | true |
2,976,761,292 | [elastic][test] fix race condition in test_barrier_timeout_rank_tracing | cdzhan | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | # Root cause
The barrier timeout set to 0.1 is too short, some threads may not have enough time to reach the barrier.
# How to reproduce
Adding some sleep will be easy to reproduce.
```python
def test_barrier_timeout_rank_tracing(self):
N = 3
store = dist.HashStore()
def run_b... | true |
2,976,646,684 | [inductor] Clean typing in codegen/common.py and codecache.py | rec | open | [
"open source",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150767
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,976,612,438 | Refactor: add initialization of math.lcm into torch_c_binding_in_graph_functions | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150766
As the title stated.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,976,611,813 | torch.compile failed to handle a custom __delattr__ method correctly | XinyiYuan | open | [
"high priority",
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 1 | NONE | ### 🐛 Describe the bug
torch.compile fails to correctly handle classes with a custom `__delattr__` method. Specifically, when a class overrides `__delattr__` to block deletion of certain attributes, the behavior is not preserved under compilation.
MRE:
```python
import torch
class MyObject:
def __init__(self, v... | true |
2,976,581,829 | Don't run NCCL/gloo distributed test without GPUs | Flamefire | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | COLLABORATOR | If there aren't any GPUs the WORLD_SIZE would be zero which does not work.
So skip those backends completely in that case.
Fix after https://github.com/pytorch/pytorch/pull/137161
It might make sense to still run the (CPU-) part of the tests by using something like `world_size = max(3, gpu_count)` or `num_gpus i... | true |
2,976,573,934 | [Dynamo][Typing] Enable `@override` for VTs [1/N] | shink | open | [
"open source",
"topic: not user facing",
"module: dynamo"
] | 8 | CONTRIBUTOR | As https://github.com/pytorch/pytorch/pull/150289#pullrequestreview-2729254192 said.
Enable `@override` for VTs:
- torch/_dynamo/variables/base.py
- torch/_dynamo/variables/builtin.py
- torch/_dynamo/variables/constant.py
- torch/_dynamo/variables/ctx_manager.py
cc @voznesenskym @penguinwu @EikanWang @jgong... | true |
2,976,229,665 | [Inductor] Set the default value of min_chunk_size to 512 | jiayisunx | open | [
"open source",
"module: inductor",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150762
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,976,136,900 | [Easy] enable PYFMT for torch/quantization/eager | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: quantization",
"topic: not user facing"
] | 8 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150761
All modifications are done through tools, the detailed commands are as follows:
```bash
lintrunner -a --take "PYFMT" --all-files
``` | true |
2,976,136,572 | Add more check for torch.ormqr | FFFrog | closed | [
"release notes: linalg_frontend"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150761
* __->__ #150760
As the title statd.
Please refer to https://github.com/pytorch/pytorch/issues/150674 for more info. | true |
2,976,113,250 | Add more check for torch.ormqr | FFFrog | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: linalg_frontend"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150759
As the title statd.
Please refer to https://github.com/pytorch/pytorch/issues/150674 for more info. | true |
2,976,104,477 | [Don't Merge] Check Regression | shiyang-weng | closed | [
"open source",
"module: inductor"
] | 2 | CONTRIBUTOR | There are regressions running ci for https://github.com/pytorch/pytorch/pull/150150
But this patch not related to the regressions.
This pr only used to check if there are regressions on master branch
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiay... | true |
2,976,080,707 | Inductor `Fatal Python error` via reduction of `None` refcount to 0 | main-horse | closed | [
"oncall: pt2"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
# TLDR
1. inductor torch.compile()'d training with torch nightly can produce `Fatal Python error: none_dealloc: deallocating None` after an indeterminate number of steps.
2. This is because some aspect of compiled autograd wrongly reduces the refcount of `None` to 0, which [triggers `Py_XDECREF... | true |
2,975,884,106 | FP8: E4M3fn: The FP8 E4M3fn result is not inf when casting a bfloat16 value larger than max normal value of FP8 E4M3 (448). It gets rounded down to 448. | varun10221 | closed | [
"triaged",
"module: float8"
] | 2 | NONE | ### 🐛 Describe the bug
import torch
vals = torch.tensor([464],dtype=torch.bfloat16)
a_f8 = vals.to(torch.float8_e4m3fn)
print(a_f8)
b_bf16 = a_f8.to(torch.bfloat16)
print(b_bf16)
print(torch.finfo(torch.float8_e4m3fn).max)
#This happens for all values from 449 ->465 , it updates to inf for values greater than that... | true |
2,975,813,845 | [ez] move GuardsContext code comment to the right place | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151180
* #151179
* #150828
* __->__ #150755
* #150754
* #150753
| true |
2,975,813,754 | [ez]][dynamo] remove useless super().__init__() | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151180
* #151179
* #150828
* #150755
* __->__ #150754
* #150753
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,975,813,639 | [ez][dynamo] some code movement | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151180
* #151179
* #150828
* #150755
* #150754
* __->__ #150753
`optimize_assert` already does the lookup for `backend` and
`backend_ctx_ctor`. This simply moves the lookups within `optimize`
lower so we don't end up calling these functions... | true |
2,975,797,813 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_float64 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_abs_fastpath_outplace_cuda_float64&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/4007220442... | true |
2,975,654,630 | [Quant][PT2E][X86] enable qconv1d-relu fusion | Xia-Weiwen | closed | [
"module: cpu",
"open source",
"Merged",
"ciflow/trunk",
"release notes: quantization",
"intel",
"module: inductor",
"ciflow/inductor"
] | 7 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150831
* __->__ #150751
**Summary**
As the title.
- The `conv1d - relu` pattern will be annotated by the `X86InductorQuantizer`.
- The pattern will be fused as `qconv_pointwise` during lowering.
**Test plan**
```
python test/induct... | true |
2,975,545,825 | Make device check error message more descriptive | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ci-no-td"
] | 21 | CONTRIBUTOR | Fixes #122757
## Test Result
```python
import torch
model_output = torch.randn(10, 5).cuda()
labels = torch.randint(0, 5, (10,)).cuda()
weights = torch.randn(5)
loss_fn = torch.nn.CrossEntropyLoss(weight=weights)
loss = loss_fn(input=model_output, target=labels)
print(loss)
Traceback (most recent ... | true |
2,975,472,077 | Add `torch.triu_indices`, `torch.tril_indices` dtype description | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: python_frontend"
] | 12 | CONTRIBUTOR | Fixes #150675
## Test Result
| true |
2,975,374,040 | [DCP][OSS] Introduce barrier util in the DistWrapper for rank local checkpointing | saumishr | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (checkpoint)"
] | 4 | CONTRIBUTOR | Summary: Introduce barrier util in the DistWrapper for rank local checkpointing. This barrier will be used at the end of the rank local checkpointing to ensure all ranks synchronize.
Test Plan: UTs
Differential Revision: D72541431
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
2,975,370,413 | DISABLED test_parity__foreach_abs_fastpath_outplace_cuda_float32 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 4 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_parity__foreach_abs_fastpath_outplace_cuda_float32&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/40065343696).
Ove... | true |
2,975,248,069 | Export QAT model is not performing as expected when compared to the original model and FX Graph QAT | Jacobdelgado1002 | closed | [
"needs reproduction",
"oncall: quantization",
"oncall: pt2",
"oncall: export"
] | 5 | NONE | ### 🐛 Describe the bug
I'm trying to perform QAT utilizing MobileNetV2 with the goal of converting it into TFLite. However, after training the model, I run a bench-marking script to compare its performance to the original model and see that the performance deprecates greatly.
Here are the important code snippets:
`... | true |
2,975,199,483 | Cannot checkout commits from when NCCL was still a submodule | danielvegamyhre | closed | [
"module: build",
"module: ci",
"triaged",
"module: nccl"
] | 5 | CONTRIBUTOR | is there a way i can checkout the commit from before NCCL was updated here: https://github.com/pytorch/pytorch/commit/4ece056791d779a6bfb0574c3a26cd6a7e600089
When I try I can an error:
```
fatal: not a git repository: ../../../.git/modules/third_party/nccl/nccl
fatal: could not reset submodule index
```
cc @seemeth... | true |
2,975,145,499 | [codemod] Fix `-Wambiguous-reversed-operator` in aten/src/ATen/cuda/tunable/Tunable.h | r-barnes | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"topic: improvements",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Summary:
`-Wambiguous-reversed-operator` warns about ambiguous reversed operators, e.g. `a < b` and `b > a` are both valid. Such operators are disallowed in C++20. This codemod fixes the warnings.
#buildsonlynotests - If this diff compiles, it works.
- If you approve of this diff, please use the "Accept & Ship" butt... | true |
2,975,094,347 | a | jlcmoore | closed | [] | 0 | NONE | null | true |
2,975,004,395 | Install pytorch from pypi using local CUDA build | ikrommyd | open | [
"module: binaries",
"oncall: releng",
"module: ci",
"triaged",
"enhancement",
"has workaround",
"needs design"
] | 5 | NONE | ### 🚀 The feature, motivation and pitch
It's great that nvidia provides wheels for the CUDA related packages and we don't need `conda/mamba` to install pytorch anymore, but those packages take up space if you install pytorch in multiple environments.
I would be nice if you could install a pytorch version from pypi th... | true |
2,974,992,843 | how to install pytorch with cuda 12.2 and py3.12 | goactiongo | closed | [] | 4 | NONE | ### 🐛 Describe the bug
I wanna know how to install pytorch with CUDA12.2
### Versions
I used the following command , and many issue occured
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia | true |
2,974,540,925 | [DTensor] Add DTensor redistribute fwd/bwd datatype conversion to enable SimpleFSDP mixed precision training | ruisizhang123 | closed | [
"oncall: distributed",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (dtensor)"
] | 7 | CONTRIBUTOR | As titled, this pr adds additional `forward_dtype` and `backward_dtype` conversion in DTensor `redistribute` API to enable SimpleFSDP's mixed precision training.
In this forward pass, the DTensor can be configured to be cast to `forward_dtype`; in the backward pass, the DTensor can be configured to be cast to `back... | true |
2,974,536,794 | [AOTI] Embed cubin files into .so | desertfire | open | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #150739
Summary: Embed cubin files so AOTI is one step closer to generate a single binary. Controlled by a flag and off as default.
Differential Revision: [D72535357](https://our.internmc.facebook.com/intern/diff/D72535357) | true |
2,974,521,493 | [CI] [Inductor] Add MPS to HAS_GPU variable | malfet | open | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150821
* __->__ #150738
* #150824
But exclude it from torch/testing/_internal/triton_utils.py (i.e. later implies `HAS_GPU` and has triton)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @w... | true |
2,974,520,904 | [MPSInductor] Fix tiled reduction logic | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #150738
* __->__ #150737
In case of tiles, index must include both reduction dimentions
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @much... | true |
2,974,440,544 | Fix missing braces for clang CUDA | r-barnes | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: sparse"
] | 4 | CONTRIBUTOR | Test Plan: Sandcastle
Differential Revision: D72469764
| true |
2,974,439,792 | Suppress `-Wunused-function` for DSA | r-barnes | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Test Plan: Sandcastle
Reviewed By: dtolnay
Differential Revision: D72458590
| true |
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