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Author SHA1 Message Date
Brian Hirsh
7d710403b0 Reapply "Make functionalization ViewMeta serializable with pickle. (#143712)" (#163769) 
### Summary:
NOTE: This is a re-export of https://github.com/pytorch/pytorch/pull/161994 ; the changes between these two PRs is exclusively to the buck/build files

(Summary from #161994 )
Attempted rebase of https://github.com/pytorch/pytorch/pull/143712.

This reverts commit 6c713ccb5e0df227dd5b630057cbccd373cbe7d6.

cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames Lucaskabela

imported-using-ghimport

Test Plan: Imported from OSS

Differential Revision: D81524507

Pulled By: Lucaskabela

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163769
Approved by: https://github.com/dolpm

Co-authored-by: Brian Hirsh <hirsheybar@fb.com>
 2025-09-25 10:27:37 +00:00
PaliC
29cbcbac42 [BE] Make PyObjectSlot use a global PyInterpreter (#162659) 
This pr gets rid of the pyobj_interpreter_ variable from PyObjectSlot and saves a word in the process

Gonna ask for review from @huydhn as there are some changes to CI.

Testing: imported internally and the failed android build seems to work now!

Pull Request resolved: https://github.com/pytorch/pytorch/pull/162659
Approved by: https://github.com/albanD, https://github.com/huydhn
 2025-09-25 08:53:19 +00:00
Pian Pawakapan
5f90e8c7ae [PGO] ignore extra PGO key if warm/cold cache present (#163810) 
Summary: avoids PGO profile merges

Test Plan: test_pgo

Differential Revision: D83200714

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163810
Approved by: https://github.com/bobrenjc93
 2025-09-25 07:16:05 +00:00
Klaus Zimmermann
eb7f4e0004 Add PEP 517 compliant Python source distribution to release process (#157815) 
This adds the actual creation of a standards compliant sdist along with its upload to s3 to the create release workflow.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/157815
Approved by: https://github.com/malfet, https://github.com/atalman
ghstack dependencies: #157814, #160315
 2025-09-25 07:15:52 +00:00
Klaus Zimmermann
42928876eb Add sdist handling to version finding (#160315) 
The version finding logic triggered from `setup.py` generally tries to take the git information into account.
This is fine for most situations where we are building from a checkout, but it creates a problem in the case of sdists, as here the version is determined at the time of sdist creation, taking the git information into account, but then later recalculated when building wheels or installing from the sdist, now with the git information missing.

The solution is to take the version information directly from the sdist, which this PR adds by means of parsing the `PKG-INFO` which marks an unpacked sdist.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/160315
Approved by: https://github.com/atalman
ghstack dependencies: #157814
 2025-09-25 07:15:51 +00:00
Klaus Zimmermann
c44ec9f4c2 Improve MANIFEST.in for source distribution (#157814) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/157814
Approved by: https://github.com/XuehaiPan, https://github.com/atalman
 2025-09-25 07:15:42 +00:00
Pian Pawakapan
353991dd92 [PGO] distinguish sticky PGO put (#163799) 
Summary: put_remote_code_state vs. put_extra_remote_code_state

Test Plan: test_pgo

Differential Revision: D83195687

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163799
Approved by: https://github.com/bobrenjc93
 2025-09-25 06:59:25 +00:00
Filip
2b6a74abf1 [optim] prevent unintended aliasing in lr_scheduler; update type annotations/docs (#163120) 
1. Prevents unintended aliasing of `self._last_lr`/`get_last_lr(...)` with `group["lr"]` when `group["lr"]` is a tensor.
2. Prevents unintended aliasing of `LRScheduler.base_lrs` with the `group["initial_lr"]`s.
3. Updates `test/optim/test_lrscheduler.py` to test tensor LRs.
4. Changes type annotations for `_last_lr`, `get_last_lr()`, `base_lrs`, `get_lr()`, and `_get_closed_form_lr()` from `list[float]` to `list[float | Tensor]`; adds documentation.

Fixes #163103

LR schedulers can behave in unexpected ways when using a tensor LR due to patterns like this:
```python
self._last_lr: list[float] = [group["lr"] for group in self.optimizer.param_groups]
```

This PR adds a helper to address this:
```python
def _param_groups_val_list(optimizer: Optimizer, key: str) -> list[Any]:
    """Create a list containing group[key] for each optimizer param_group.
    Prevents aliasing when group[key] could be a Tensor.
    Raises a KeyError when group[key] does not exist.
    """
    return [
        group[key].clone() if isinstance(group[key], Tensor) else group[key]
        for group in optimizer.param_groups
    ]
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163120
Approved by: https://github.com/janeyx99
 2025-09-25 06:58:58 +00:00
Bob Ren
ad869c58f5 remove allow-untyped-defs from ./torch/utils/benchmark/op_fuzzers/sparse_unary.py (#163476) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163476
Approved by: https://github.com/ezyang, https://github.com/Skylion007
ghstack dependencies: #163478, #163475, #163471
 2025-09-25 06:48:44 +00:00
Bob Ren
d5afb9e31a remove allow-untyped-defs from ./torch/ao/quantization/quantizer/utils.py (#163471) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163471
Approved by: https://github.com/Skylion007
ghstack dependencies: #163478, #163475
 2025-09-25 06:48:44 +00:00
Bob Ren
e7d6ea65ca remove allow-untyped-defs from ./torch/nn/utils/_expanded_weights/embedding_expanded_weights.py (#163475) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163475
Approved by: https://github.com/ezyang, https://github.com/Skylion007
ghstack dependencies: #163478
 2025-09-25 06:48:44 +00:00
Bob Ren
a6974195da remove allow-untyped-defs from ./torch/fx/experimental/unification/multipledispatch/core.py (#163478) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163478
Approved by: https://github.com/ezyang
 2025-09-25 06:48:44 +00:00
FFFrog
a213848703 [Code Clean] Remove deadcodes about Python3.9 [8/N] (#163728) 
As the title stated.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163728
Approved by: https://github.com/albanD, https://github.com/cyyever
ghstack dependencies: #163626, #163627, #163629, #163643, #163644, #163645, #163646
 2025-09-25 05:12:46 +00:00
dolpm
cde5c9aebd fix pickling for BitwiseFn (#163571) 
Summary:
ran into AttributeError: Can't get local object 'make_opaque_bitwise_fn.<locals>.BitwiseFn'

looks like it was fixed for UnaryFn but not BitwiseFn in https://github.com/pytorch/pytorch/pull/138395

Fixes #147841

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163571
Approved by: https://github.com/jamesjwu
 2025-09-25 04:52:11 +00:00
Sampath Victor
783a9dcb6d [6/n] Quantization with min & max bounds support - using fbgemm changes in ATen (#162924) 
Summary:
This diff uses the FBGEMM changes made in D78181177 & D81858256 to support using the provided per row min/max values while quantizaing float/half to 8-bit, 4-bit & 2-bit in ATen library.

Please find more context on this here: https://fburl.com/gdoc/yutf32a0

Test Plan:
```
buck test mode/opt caffe2/torch/fb/model_transform/splitting/tests:split_dispatcher_test
```
https://www.internalfb.com/intern/testinfra/testrun/7881299640979446

Please refer to D80905814's test plan for integration testing.

Rollback Plan:

Differential Revision: D81327342

Pull Request resolved: https://github.com/pytorch/pytorch/pull/162924
Approved by: https://github.com/jerryzh168
 2025-09-25 02:52:04 +00:00
bobrenjc93
ad2f7315ca [torchfuzz] print out tensor descriptor as comments in codegen (#163739) 
eg.

```
    # Node node_12: tensor_pointwise (depth 6)
    var_node_12 = torch.ops.aten.mul(var_node_13, var_node_34) # size=(1,), stride=(1,), dtype=complex128, device=cuda

    # Node node_10: tensor_pointwise (depth 7)
    var_node_10 = torch.ops.aten.div(var_node_11, var_node_12) # size=(1,), stride=(1,), dtype=complex128, device=cuda

    # Node node_2: tensor_pointwise (depth 8)
    var_node_2 = torch.ops.aten.div(var_node_3, var_node_10) # size=(1,), stride=(1,), dtype=complex128, device=cuda
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163739
Approved by: https://github.com/pianpwk
ghstack dependencies: #163547, #163553, #163554, #163555, #163556, #163557, #163558, #163560, #163698
 2025-09-25 01:29:29 +00:00
Nikita Shulga
cc660d38ac [CI] Install libuv for Win testing (#163797) 
Current working theory why f0078941cf caused a regression, are because Windows CI no longer could be build with distributed, as it could not find libuv
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163797
Approved by: https://github.com/wdvr
 2025-09-25 01:10:14 +00:00
Nikita Shulga
00f96dd84d [CI] Run CUDA-13 binary builds on trunk (#163787) 
There are numerous other workflows that could be used to catch CUDA-12
build regression (our CI builds are almost identical to CD ones), but not many CUDA-13 builds around, so https://github.com/pytorch/pytorch/issues/163342 are really hard to detect in CI
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163787
Approved by: https://github.com/atalman, https://github.com/huydhn
 2025-09-25 00:58:17 +00:00
Aaron Pollack
77b9aac6c2 Add rule for typechecking maintainers (#161307) 
Allow the following people merge rights on type checking configs:
  - @lolpack
  - @maggiemoss
  - @ndmitchell
  - @kinto0

Pull Request resolved: https://github.com/pytorch/pytorch/pull/161307
Approved by: https://github.com/albanD, https://github.com/ezyang
 2025-09-25 00:14:31 +00:00
Wei Wang
7163dce1e0 [CUDA] Compare major version of the runtime device arch against the built version of the pytorch binary (#161299) 
Fixes misleading warning messages when running on sm12x devices using binaries built with sm120.
PyTorch binary built with sm120 is compatible with e.g. sm121, so no need for the warning of incompatibility.

Also allow the 'matched_cuda_warn' message to show when e.g. the user is running a binary built with only sm90 on sm12x, so that the user would be prompted to get a build which supports e.g. sm120.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/161299
Approved by: https://github.com/eqy, https://github.com/atalman
 2025-09-24 23:59:19 +00:00
Sherlock Huang
4ac4a7351e Shortcut redistribution when num_shards == 1 (#163742) 
Redistribution doesn't need collectives when num_shards == 1 on a mesh dimension.
Only placement update is needed, local_tensor remains unchanged.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163742
Approved by: https://github.com/tianyu-l

Co-authored-by: tianyu-l <150487191+tianyu-l@users.noreply.github.com>
 2025-09-24 23:49:08 +00:00
Raman Kumar
65ddd91421 Fix redundant H2D/D2H memcpy in cpp_wrapper by creating scalar tensors on CPU (#160584) 
Fixes #160520

Summary:
When running Inductor with cpp_wrapper under a DeviceContext, non-tensor arguments were being wrapped with torch.tensor(arg) without specifying the device.

creating the tensor on the current active device (like CUDA), and later fetching it back to CPU via .item(), causing unnecessary host-device-host memory transfers.

PR fixes issue by explicitly creating scalar tensors on the CPU:

```
input_tensors = [
    arg if isinstance(arg, torch.Tensor) else torch.tensor(arg, device='cpu')
    for arg in args
]
```

impact: inductor, codegen

Pull Request resolved: https://github.com/pytorch/pytorch/pull/160584
Approved by: https://github.com/benjaminglass1, https://github.com/desertfire, https://github.com/mlazos, https://github.com/jeffdaily
 2025-09-24 23:40:37 +00:00
karthickai
8c98aee436 [Inductor] Update DeviceAssert op to behave like store (#163696) 
Updated the DeviceAssert operation to match the behavior of Store, it will fixes the issue mentioned in [this PR](https://github.com/pytorch/pytorch/pull/163023) and updated testcases as Elias [suggested](https://github.com/pytorch/pytorch/pull/160677#discussion_r2353834646).

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163696
Approved by: https://github.com/mlazos
 2025-09-24 23:35:56 +00:00
bobrenjc93
d927e55498 [torchfuzz] refactor multi_process_fuzzer to be more readable (#163698) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163698
Approved by: https://github.com/pianpwk
ghstack dependencies: #163547, #163553, #163554, #163555, #163556, #163557, #163558, #163560
 2025-09-24 23:32:34 +00:00
Maggie Moss
754c7e2e88 Update pyrefly configuration file (#163775) 
Related to: https://github.com/pytorch/pytorch/issues/163283

This simply updates the existing pyrefly configuration and opts out additional directories. Running `pyrefly check` with this setup will result in ~100 errors reported.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163775
Approved by: https://github.com/ezyang, https://github.com/Skylion007
 2025-09-24 23:14:39 +00:00
Jithun Nair
0ec946a052 [ROCm] Increase binary build timeout to 5 hours (300 minutes) (#163776) 
Despite narrowing down the [FBGEMM_GENAI build to gfx942](https://github.com/pytorch/pytorch/pull/162648), the nightly builds still timed out because they [didn't get enough time to finish the post-PyTorch-build steps](https://github.com/pytorch/pytorch/actions/runs/17969771026/job/51109432897).

This PR increases timeout for ROCm builds for both [libtorch ](https://github.com/pytorch/pytorch/actions/runs/17969771026)and [manywheel](https://github.com/pytorch/pytorch/actions/runs/17969771041), because both of those are close to the 4hr mark currently.

This PR is a more ROCm-targeted version of https://github.com/pytorch/pytorch/pull/162880 (which is for release/2.9 branch).

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163776
Approved by: https://github.com/jeffdaily

Co-authored-by: Jeff Daily <jeff.daily@amd.com>
 2025-09-24 23:02:08 +00:00
Rob Timpe
2b1236de61 [dynamo] Fix handling of kwargs in exception constructor (#163390) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163390
Approved by: https://github.com/guilhermeleobas
 2025-09-24 22:44:14 +00:00
Haifeng Jin
bc8680c298 Avoid at::alias in the repeat op implementation (#163455) 
Avoid `at::alias` in the `repeat` op implementation

## Summary

This PR removed the usage of `at::alias` in the implementation and just `permute`+`reshape` the tensor to fit the specs of the result.
This is a less hacky and a more readable way of implementing the op.
All the new ops we are using are view-only ops, which does not introduce overhead of changing the storage.

## Who want this

We are using `PrivateUse1` and accelerator, but this request to avoid `at::alias` in any op should be general enough for any backend who is using XLA, or who do not have explicit control over the memory allocation on the devices.

## Why we/they need this

As we support TPU, we are overriding some ATen ops by binding them to PrivateUse1.
However, it is not recommended to override the `repeat` op directly as we saw the following in `RegistrationDeclaration.h`.

```
at::Tensor repeat(const at::Tensor & self, c10::SymIntArrayRef repeats); // {"schema": "aten::repeat(Tensor self, SymInt[] repeats) -> Tensor", "dispatch": "True", "default": "True"}
```

We had to reuse the existing implementation of `repeat` to decomposite to other ops.
However, we are unable to support the current implementation, which uses `at::alias`.
It have two tensors share the same storage and modify one of them and return the other assuming it is changed, too.

As, we do not have explicit control over the memory allocation of the tensors using XLA/PJRT.

## Alternatives

We are open to alternative solutions that work for us if this PR is not in favor of the PyTorch community.
For example, we may just bind our version of `repeat` op implementation to both `PrivateUse` and `AutogradPrivateUse1`.
However, to my understanding, this would not work well with torch dynamo and `torch.compile`.

Would you mind guiding us on how to solve this?

Thanks!

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163455
Approved by: https://github.com/Skylion007
 2025-09-24 22:28:24 +00:00
Andrey Talman
1495b35d29 Remove Python 3.9 for Triton builds (#163778) 
Related to https://github.com/pytorch/pytorch/issues/161167

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163778
Approved by: https://github.com/malfet
 2025-09-24 20:19:43 +00:00
zeshengzong
90a282504e Add inference_mode hint message to use eval with inference. (#163619) 
Fixes #162923

## Test Result

### Before

<img width="985" height="889" alt="image" src="https://github.com/user-attachments/assets/41de5cfa-7b25-4ba4-ade8-a6df745dcb30" />

### After

<img width="913" height="977" alt="image" src="https://github.com/user-attachments/assets/b6c06860-8db3-4b5d-9d46-31ece01fb04d" />

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163619
Approved by: https://github.com/jbschlosser
 2025-09-24 20:07:14 +00:00
Jeff Daily
0dce2afd44 [ROCm][CI] adjust tf32 tolerance for test_compile_kernel_advanced (#163783) 
Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163783
Approved by: https://github.com/jeffdaily

Co-authored-by: Jeff Daily <jeff.daily@amd.com>
 2025-09-24 19:39:15 +00:00
Natalia Gimelshein
71eec6a0bf [dist] handle discontiguous allgather/reducescatter inputs (#163712) 
Fixes #163483

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163712
Approved by: https://github.com/ezyang, https://github.com/kwen2501
 2025-09-24 19:38:44 +00:00
Xu Han
0456b23b77 [AOTI] Add verbose error information for extract file (#163718) 
This PR optimize `extract_file` functions:
1. `normalize_path_separator` the dest path for Windows.
2. Add verbose error message:
a. On Linux, add mz_zip error string.
b. On Windows, add mz_zip error string and Windows error code.

For the UT `test_package_user_managed_weight`:
<img width="1910" height="442" alt="image" src="https://github.com/user-attachments/assets/6a63eda1-70ce-40fb-9681-adc955463884" />

It still have issue with error code `32`, checked https://learn.microsoft.com/en-us/windows/win32/debug/system-error-codes--0-499- and find the verbose is `ERROR_SHARING_VIOLATION`.

It is a little complex to debug, I will continue to working on it in further PR.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163718
Approved by: https://github.com/desertfire
 2025-09-24 19:27:30 +00:00
Benji Beck
c414f75c8b [WOQ][Inductor] Enable CUDA coverage for _weight_int8pack_mm (#163461) 
Summary:
What: Unskip the CUDA path for test_int8_weight_only_quant in test_torchinductor.py as the kernel was added by #159325.

Why: Confirm CUDA backend for _weight_int8pack_mm is registered.

Test Plan:
```
buck2 test 'fbcode//mode/opt' fbcode//caffe2/test/inductor:test_inductor_cuda
```
https://www.internalfb.com/intern/testinfra/testrun/2533275104869494

Differential Revision: D82926440

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163461
Approved by: https://github.com/jerryzh168
 2025-09-24 19:20:38 +00:00
PaulZhang12
768361e67f Add less warps config to inner reductions (#162447) 
Add less warps to ensure proper vectorization + memory coalescing for inner reductions, prefer more work per thread

<img width="1717" height="731" alt="Screenshot 2025-09-17 at 10 03 25 AM" src="https://github.com/user-attachments/assets/7b1f4a30-62f2-4bee-bb9c-122501bde63e" />

Pull Request resolved: https://github.com/pytorch/pytorch/pull/162447
Approved by: https://github.com/v0i0, https://github.com/eellison, https://github.com/shunting314
 2025-09-24 19:09:02 +00:00
Nan Zhang
9341ede617 Revert to old behaviour of not padding strides if shape or stride is dynamic (#163639) 
Differential Revision: D83053287

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163639
Approved by: https://github.com/blaine-rister
 2025-09-24 18:31:01 +00:00
Sherlock Huang
4c2c401ccf Record redistribute_local_tensor in DebugMode (#163704) 
Explicit redistribute_local_tensor API call could also results in communication, record it!

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163704
Approved by: https://github.com/ezyang
 2025-09-24 16:11:26 +00:00
Frank Lin
5d0f639234 Make Tensor.__dlpack__(stream=None) capture-safe during CUDA Graph capture (#163242) 
Many extensions (including pybind helpers) call `Tensor.__dlpack__()` without a stream argument. Before #150217, `stream=None` behaved like “no cross-stream sync” and was safe inside CUDA Graph capture. After #150217, `stream=None` maps to the legacy default stream, adding a cross-stream wait that invalidates capture when running on a non-default stream.

See this example

```
import torch
s = torch.cuda.Stream()
x = torch.randn(8, device="cuda")
g = torch.cuda.CUDAGraph()

with torch.cuda.stream(s):
    with torch.cuda.graph(g):
        _ = x + 1
        cap = x.__dlpack__()
        _ = torch.utils.dlpack.from_dlpack(cap)
```

This PR partially reverts #150217 that stream=None defaults to no sync.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163242
Approved by: https://github.com/ngimel
 2025-09-24 16:04:19 +00:00
atalman
9d0d98acfe Use cuda nvrtc so file based on cuda version used by torch (#163642) 
Fixes https://github.com/pytorch/pytorch/issues/162367

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163642
Approved by: https://github.com/msaroufim
 2025-09-24 14:23:39 +00:00
Angel Li
3b73841f43 update test_quantization tests to run weekly (#163077) 
Fixes #162854

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163077
Approved by: https://github.com/huydhn
 2025-09-24 11:31:11 +00:00
atalman
141fc7276e [CD] CUDA 13.0 fix preload logic to include nvidia/cu13/lib/ (#163661) 
Preload logic no longer works with CUDA 13.0
See the installation path:
```
ls /home/ubuntu/.venv/lib/python3.10/site-packages/nvidia/cu13/lib/
libcheckpoint.so   libcudadevrt.a      libcufft.so.12   libcufile_rdma.so.1  libcusolver.so.12    libnvJitLink.so.13  libnvperf_target.so            libnvrtc.alt.so.13    libpcsamplingutil.so
libcublas.so.13    libcudart.so.13     libcufftw.so.12  libcupti.so.13       libcusolverMg.so.12  libnvblas.so.13     libnvrtc-builtins.alt.so.13.0  libnvrtc.so.13
libcublasLt.so.13  libcudart_static.a  libcufile.so.0   libcurand.so.10      libcusparse.so.12    libnvperf_host.so   libnvrtc-builtins.so.13.0      libnvtx3interop.so.1

ls /home/ubuntu/.venv/lib/python3.10/site-packages/nvidia/
cu13  cudnn  cusparselt  nccl  nvshmem
```

Test using script from : https://github.com/pytorch/pytorch/issues/162367
```
Kernel test passed!
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163661
Approved by: https://github.com/nWEIdia, https://github.com/tinglvv, https://github.com/Camyll
 2025-09-24 11:27:05 +00:00
Robert Hardwick
b66aa1ade1 [ARM] Add test_memory_profiler to aarch64 tests (#145260) 
TestMemoryProfilerE2E.test_memory_timeline is failing on AArch64, this fixes it and enables it in the opt-in list of tests for AArch64.

Fixes #142371

Pull Request resolved: https://github.com/pytorch/pytorch/pull/145260
Approved by: https://github.com/fadara01, https://github.com/sraikund16
 2025-09-24 09:29:13 +00:00
Nick Riasanovsky
207f104594 [Triton] [Inductor] Set default configs for Blackwell Matmul Template (#163740) 
Summary: Sets the default configs for the Blackwell Matmul Templates.

Test Plan: NFC

Differential Revision: D83116342

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163740
Approved by: https://github.com/jananisriram
 2025-09-24 08:17:35 +00:00
Jason Ansel
3e1b1a30f2 Revert "[inductor] Fix issue with scalar arg handling" (#163737) 
This reverts commit a8cd437183142e17ba6fc8d7b5e9dcee462d7904.

See https://github.com/pytorch/pytorch/pull/163481#issuecomment-3326310774

This PR might also cause issues with cudagraphs.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163737
Approved by: https://github.com/ezyang
ghstack dependencies: #163386, #163398, #163387, #163414, #163415, #163419, #163434, #163393, #163412, #163422, #163481, #163520, #163482
 2025-09-24 07:33:12 +00:00
FFFrog
2390d34c9b [Code Clean] Remove deadcodes about Python3.9 [7/N] (#163646) 
As the title stated.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/163646
Approved by: https://github.com/jansel
ghstack dependencies: #163626, #163627, #163629, #163643, #163644, #163645
 2025-09-24 07:30:50 +00:00
FFFrog
a635505a99 [Code Clean] Remove deadcodes about Python3.9 [6/N] (#163645) 
As the title stated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163645
Approved by: https://github.com/albanD
ghstack dependencies: #163626, #163627, #163629, #163643, #163644
 2025-09-24 07:30:50 +00:00
FFFrog
6f34cc040f [Code Clean] Remove deadcodes about Python3.9 [5/N] (#163644) 
As the title stated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163644
Approved by: https://github.com/jansel
ghstack dependencies: #163626, #163627, #163629, #163643
 2025-09-24 07:30:50 +00:00
FFFrog
ec0cd81c38 [Code Clean] Remove deadcodes about Python3.9 [4/N] (#163643) 
As the title stated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163643
Approved by: https://github.com/albanD
ghstack dependencies: #163626, #163627, #163629
 2025-09-24 07:30:50 +00:00
FFFrog
33aabdd8ac [Code Clean] Remove deadcodes about Python3.9 [3/N] (#163629) 
As the title stated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163629
Approved by: https://github.com/albanD
ghstack dependencies: #163626, #163627
 2025-09-24 07:30:50 +00:00
FFFrog
0bca77951d [Code Clean] Remove deadcodes about Python3.9 [2/N] (#163627) 
As the title stated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163627
Approved by: https://github.com/jansel
ghstack dependencies: #163626
 2025-09-24 07:30:50 +00:00