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 |
|---|---|---|---|---|---|---|---|---|
2,851,838,818 | [export] Add meta for aten.bincount | angelayi | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Fixes https://github.com/pytorch/pytorch/issues/147094 | true |
2,851,835,028 | DISABLED test_output_match_linalg_cholesky_ex_cpu_float32 (__main__.TestConsistencyCPU) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"module: macos",
"skipped",
"module: mps"
] | 2 | NONE | Platforms: mac, macos
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_output_match_linalg_cholesky_ex_cpu_float32&suite=TestConsistencyCPU&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37174505386).
Ov... | true |
2,851,829,486 | [cond] support output sizes mismatch in front end | ydwu4 | closed | [
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147127
* #147045
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,851,803,230 | [export] Generate printers/parsers for serialization enum values. | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 4 | CONTRIBUTOR | Summary:
Generate two helper functions for enum classes in generated_serialization_types.h
printEnum: will convert enum values into strings.
parseEnum: will convert strings into enum values.
Test Plan: CI
Differential Revision: D69604850
| true |
2,851,785,088 | Remove outdated comment in ATen/mkl/Sparse.h about lack of Windows support | gajanan-choudhary | closed | [
"triaged",
"open source",
"Merged",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Fixes #147124.
* #102604 added support for Intel oneMKL Sparse BLAS APIs so there was an outdated comment left around in the codebase that can now be removed. | true |
2,851,779,444 | Windows support of Intel oneMKL Sparse BLAS APIs and possible outdated comment | gajanan-choudhary | closed | [
"triaged"
] | 0 | CONTRIBUTOR | * This is a minor issue about there being a possibly misleading comment in the codebase.
* oneMKL Sparse BLAS APIs were not supported on Windows in the past, see #97352.
* Support for oneMKL Sparse BLAS APIs on Windows was later enabled in #102604.
* Therefore, I believe that the comment at https://github.com/pytorch/p... | true |
2,851,760,693 | [ddp] decouple python reducer from compilation mode | xmfan | closed | [
"oncall: distributed",
"module: ddp",
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: distributed (miscellaneous)"
] | 10 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147123
Current implementation reads as: we will only actually use the "python_reducer" config if the DDP forward is compiled. Otherwise, we will silently fallback to C++ reducer + no DDPOptimizer.
I'm changing this behavior to al... | true |
2,851,758,877 | PyTorch build with numpy version incompatibility | H-Huang | closed | [
"module: build",
"oncall: quantization",
"has workaround"
] | 2 | MEMBER | I'm building the latest PyTorch using `TORCH_CUDA_ARCH_LIST="8.0 9.0" BUILD_TEST=0 USE_CUDA=1 USE_DISTRIBUTED=1 python setup.py install`
But when I `import torch` I get:
```
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.2.2 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules ... | true |
2,851,749,033 | [AMD] Compile Failure with triton templates | eellison | closed | [
"triaged",
"oncall: pt2",
"module: inductor",
"rocm"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
See pr [here](https://github.com/pytorch/pytorch/pull/146293) with special casing for amd triton template.
### Versions
master
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8... | true |
2,851,708,369 | Make torch.cuda.gds APIs public | mikaylagawarecki | closed | [
"Merged",
"ciflow/trunk",
"release notes: cuda",
"topic: new features"
] | 3 | CONTRIBUTOR | Follow up to https://github.com/pytorch/pytorch/pull/145748 that turned USE_CUFILE on for CUDA 12.6 and 12.8 binaries
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147120
| true |
2,851,665,252 | [Edited] Add docstring to improve documentation | MayureshMore | closed | [
"oncall: distributed",
"oncall: jit",
"module: rocm",
"module: cpu",
"module: mkldnn",
"open source",
"release notes: quantization",
"release notes: releng",
"fx",
"module: inductor",
"module: dynamo"
] | 3 | NONE | Changes made in branch: **MayureshMore:2.1-dynamic-doc**
[Edited] Add docstring to improve documentation
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jata... | true |
2,851,646,018 | padding fails on view from large tensor | rtyasdf | open | [
"module: cuda",
"triaged",
"module: 64-bit",
"module: padding",
"module: edge cases"
] | 0 | NONE | ### 🐛 Describe the bug
Call to padding function (`torch.nn.functional.pad`) in `reflect` mode on view of a tensor with number of elements exceeding 2^32 may lead to unexpected behavior, which best illustrated by following snippet:
```python
import torch
import torch.nn.functional as F
DEVICE = torch.device('cuda:0'... | true |
2,851,624,535 | [torch][amdsmi] Look for amdsmi in ROCM_HOME/ROCM_PATH before using rpath | danzimm | closed | [
"module: rocm",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 6 | CONTRIBUTOR | Summary: ROCm uses ROCM_HOME/ROCM_PATH to specify which version of rocm the user wants to use. This is especially important in multi-version setups. Let's respect that behavior when loading amdsmi.
Test Plan:
CI
```
NCCL_DEBUG=INFO NCCL_DEBUG_SUBSYS=INIT,COLL MSCCL_ALGO_DIR=~/2fbsource/third-party/rccl/develop/tools/m... | true |
2,851,618,730 | [DCP] Cache save plans: planner helpers and interface updates | saumishr | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: new features"
] | 20 | CONTRIBUTOR | Summary:
This PR updates the planner interface and introduces the class variables to cache the local and global plans.
Two new helpers are also introduced which will be used to compare if the plans have changed across save attempts and merge the delta plans.
Test Plan: UTs
Differential Revision: D69224488
cc @H-... | true |
2,851,576,077 | Unable to print in a branch run by torch.cond | xadupre | open | [
"triaged",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher"
] | 2 | COLLABORATOR | ### 🐛 Describe the bug
The code run by torch cond has more constraints than the other part of the model. So even before exporting the model, it may not work because of logging, printing, ... The following script returns:
```python
import torch
class SubThen(torch.nn.Module):
def forward(self, x):
retur... | true |
2,851,541,853 | [PT][FSDP] support custom all reduce hook across FSDP units | xunnanxu | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (fsdp)",
"ciflow/inductor"
] | 29 | CONTRIBUTOR | This change adds an API `set_all_reduce_hook` to the `FSDPModule` to
support customized all reduce either in native HSDP (2d mesh) setup or custom HSDP (1d FSDP + custom AR across replicas)
* For native HSDP, the original AR would still run as is and this hook allows for additional gradient modification post all redu... | true |
2,851,510,392 | Add quantized BatchNorm1d module | mattpitkin | open | [
"triaged",
"open source",
"release notes: quantization"
] | 4 | CONTRIBUTOR | Fixes #147112.
| true |
2,851,509,393 | Add quantized version of BatchNorm1d module | mattpitkin | open | [
"oncall: quantization"
] | 0 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Currently, there are quantized versions of the `BatchNorm2d` and `BatchNorm3d` modules, but not for `BatchNorm1d`. This is despite there being a quantized op for `batch_norm1d`. It would be useful to have the quantized `BatchNorm1d` included.
### Alternatives
_No response_
#... | true |
2,851,508,759 | [dsutil] shape-env logging | bobrenjc93 | closed | [
"fb-exported",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Differential Revision: D69355332
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,851,435,783 | s390x: add cleanup for cancelled docker image builds | AlekseiNikiforovIBM | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | When podman image build is cancelled,
a couple of processes are left behind,
and their existence prevents
proper shutdown of runner container.
Add cleanup step at the end of workflow
using new option recently introduced in podman:
https://github.com/containers/podman/pull/25102
Example of job preventing s390... | true |
2,851,338,544 | torch.nan_to_num does not support complex64 data type under torch.compile | meetmul | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | ### 🐛 Describe the bug
When receiving complex64 tensor, `torch.nan_to_num` works normal under eager, however it will raise not supported error under torch.compile.
code:
```python
import torch
input = torch.randn(1,1).to(torch.complex64)
try:
res = torch.nan_to_num(input)
print("Successfully run torch.nan_t... | true |
2,851,298,314 | Inconsistent data type casting decision when using `torch.addmv` under torch.compile and eager | meetmul | open | [
"triaged",
"bug",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | ### 🐛 Describe the bug
I think this is caused by the inconsistent type casting between torch.compile and eager. When `input` is float but `mat` and `vec` are integer, the **output under eager mode is integer but the output under torch.compile is float**. This inconsistent type casting will lead to inconsistent result... | true |
2,851,261,401 | Use 2022 as default VC_YEAR for windows tests | atalman | open | [
"Stale",
"topic: not user facing"
] | 2 | CONTRIBUTOR | Same as: https://github.com/pytorch/pytorch/pull/147053
New Windows AMI does not have Visual Studio 2019. Hence use 2022 as default.
See: pytorch/test-infra#6226
| true |
2,851,087,439 | [inductor][refactor] Make _compile_file only used for fbcode | desertfire | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Summary: _compile_file in codecache.py only handles specific cpp compilation in fbcode. The next step is to consolidate it with cpp_builder.
Test Plan: CI
Differential Revision: D69592025
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy... | true |
2,851,077,715 | [AOTI] Update test runner to use the new APIs | desertfire | closed | [
"oncall: distributed",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 11 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147105
Summary: Switch to the newer aoti_compile_and_package APIs. Some tests still kept using legacy APIs, and will follow up with internal test refactoring.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4... | true |
2,851,016,823 | [ARM] Unit test TestSelectAlgorithmCPU.test_linear_with_embedding fails on non-bf16 Aarch64 | robert-hardwick | open | [
"module: tests",
"triaged",
"module: arm"
] | 2 | COLLABORATOR | ### 🐛 Describe the bug
https://github.com/pytorch/pytorch/actions/runs/13290922608/job/37112338971
```
=================================== FAILURES ===================================
_ TestSelectAlgorithmCPU.test_linear_with_embedding_batch_size_384_in_features_196_out_features_384_bias_False_cpu_bfloat16 _
Traceba... | true |
2,850,953,651 | DISABLED test_output_match_linalg_cholesky_cpu_float32 (__main__.TestConsistencyCPU) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"module: macos",
"skipped"
] | 1 | NONE | Platforms: mac, macos
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_output_match_linalg_cholesky_cpu_float32&suite=TestConsistencyCPU&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37150595954).
Over ... | true |
2,850,949,299 | Fix init CUDA preload: get correct versions (#147001) | aowenson-imm | open | [
"triaged",
"open source",
"topic: not user facing"
] | 3 | NONE | Fixes #147001
Main change is in `cuda_libs` dict. For each lib, specify two patterns:
1) specific version e.g. `libcudart.so.12*`
2) the original less-specific pattern, as a backup
Supporting change in `_preload_cuda_deps`, sorting multiple matches by version to prefer newer lib. | true |
2,850,898,326 | Optimize `_inductor/debug.py` *args : Any with typing_extensions.TypeVarTuple | zeshengzong | open | [
"triaged",
"open source",
"Stale",
"topic: not user facing",
"module: inductor"
] | 3 | CONTRIBUTOR | Fixes part of #146249
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,850,835,369 | [inductor] SIGSEGV due to missing negative stride check in `torch.as_strided` | WLFJ | open | [
"module: crash",
"triaged",
"bug",
"oncall: pt2",
"topic: fuzzer"
] | 0 | NONE | ### 🐛 Describe the bug
When running the following test case with `torch.compile`, a segmentation fault (SIGSEGV) occurs. Without `torch.compile`, the expected `RuntimeError` is raised instead.
# Test Case:
```python
import torch
@torch.compile
def f(*args):
sym_0, sym_1, sym_2, sym_3 = args
var_374 = torc... | true |
2,850,818,722 | Optimize `graph.py` typing | zeshengzong | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor"
] | 12 | CONTRIBUTOR | Optimize `graph.py` methods type annotation.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,850,802,960 | The unit of the return value of torch.cuda.clock_rate | cdzhan | closed | [
"module: docs",
"module: cuda",
"triaged"
] | 6 | CONTRIBUTOR | ### 🐛 Describe the bug
According to 
The unit of the return value should be MHz.
```bash
root@cambricon-PowerEdge-C4140:/workspace# python -c "import torch;print(torch.cuda.clock_rate())"
1312
root@cambricon-PowerEdge-C4140:/wo... | true |
2,850,797,173 | Remove code for Python < 3.9 | cyyever | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"module: dynamo",
"ciflow/inductor"
] | 3 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @chenyang78 @kadeng @chauhang @amjames @StrongerXi | true |
2,850,583,714 | [torch.export] Exporting PaliGemma2 model fails due to data-dependent guarding issue | chohk88 | closed | [
"oncall: pt2",
"oncall: export"
] | 9 | NONE | ### 🐛 Describe the bug
**Title:** [torch.export] Exporting PaliGemma2 Model Fails Due to Data-Dependent Guarding Issue
**🐛 Describe the bug**
Attempting to export the `google/paligemma2-3b-pt-224` model using `torch.export` fails due to a data-dependent guard. The error originates from https://github.com/huggingfac... | true |
2,850,565,577 | Fix the Problems About Defining Static Variable in Inline Function | FFFrog | open | [
"oncall: distributed",
"oncall: jit",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: cpp",
"ci-no-td"
] | 34 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147095
Refer to https://github.com/pytorch/pytorch/issues/125465 for more informations
- Remove unused header files
- Move the inline function that defines the static variable to .cc
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz33... | true |
2,850,536,732 | [torch.export] torch._dynamo.exc.Unsupported: dynamic shape operator: aten.bincount.default | riestmo-nxp | closed | [
"oncall: pt2",
"oncall: export"
] | 0 | NONE | ### 🐛 Describe the bug
When trying to export a model that uses the torch.bincount operation, I get the following error:
```
torch._dynamo.exc.Unsupported: dynamic shape operator: aten.bincount.default; Operator does not have a meta kernel that supports dynamic output shapes, please report an issue to PyTorch
```
Th... | true |
2,850,493,389 | DISABLED test_view_dtype_upsize_errors_xla_uint8 (__main__.TestViewOpsXLA) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR | Platforms: <fill this in or delete. Valid labels are: asan, linux, mac, macos, rocm, win, windows.>
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_dtype_upsize_errors_xla_uint8%22%2C%22TestViewOpsXLA%22%5D)). | true |
2,850,493,238 | DISABLED test_view_dtype_upsize_errors_xla_uint8 (__main__.TestViewOpsXLA) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR | Platforms: <fill this in or delete. Valid labels are: asan, linux, mac, macos, rocm, win, windows.>
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_dtype_upsize_errors_xla_uint8%22%2C%22TestViewOpsXLA%22%5D)). | true |
2,850,491,826 | DISABLED test_view_dtype_upsize_errors_xla_uint8 (__main__.TestViewOpsXLA) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR | Platforms: <fill this in or delete. Valid labels are: asan, linux, mac, macos, rocm, win, windows.>
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_dtype_upsize_errors_xla_uint8%22%2C%22TestViewOpsXLA%22%5D)). | true |
2,850,491,031 | DISABLED test_view_dtype_upsize_errors_xla_uint8 (__main__.TestViewOpsXLA) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_dtype_upsize_errors_xla_uint8%22%2C%22TestViewOpsXLA%22%5D)). | true |
2,850,487,623 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR | Platforms: <fill this in or delete. Valid labels are: asan, linux, mac, macos, rocm, win, windows.>
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,487,384 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,487,151 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,486,877 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,486,677 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,486,416 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,486,174 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,485,537 | OpenReg: Run test_openreg in CI | Zhenbin-8 | open | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 2 | CONTRIBUTOR | The current CI will skip the test codes under test/cpp_extensions, so I move `test_openreg.py` to the test directory to allow the CI to run.
| true |
2,850,484,371 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,484,052 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,483,328 | DISABLED test_conj_imag_view_lazy_complex128 (__main__.TestViewOpsLAZY) | ankurneog | closed | [
"skipped"
] | 1 | CONTRIBUTOR |
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22test_view_ops.py%3A%3ATestViewOpsLAZY%3A%3Atest_conj_imag_view_lazy_complex128%22%5D)). | true |
2,850,468,304 | [torch][cuda] Remove redundant getting of pynvml handler | cdzhan | open | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
2,850,407,457 | [inductor] SIGSEGV when using `torch.compile` with `torch.as_strided_copy` | WLFJ | open | [
"module: crash",
"module: error checking",
"triaged",
"oncall: pt2",
"topic: fuzzer"
] | 1 | NONE | ### 🐛 Describe the bug
When running the following test case with `torch.compile`, a segmentation fault (SIGSEGV) occurs. Without `torch.compile`, the expected `RuntimeError` is raised instead.
# Test case
```python
import torch
@torch.compile
def f(*args):
input, sym_1, sym_2 = args
return torch.as_strided... | true |
2,850,407,244 | How to check grads in each step of model? | ElinLiu0 | closed | [
"module: onnx",
"triaged"
] | 7 | NONE | Hi there:
I've implement a Pytorch version of [Retrieval-based-Voice-Conversion(RVC for short)](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI) at [here](https://github.com/ElinLiu0/RVCTorch/blob/master/POC_Torch.ipynb).
The question is,when i wanna export my implementation pipeline into ON... | true |
2,850,364,581 | [inductor] Performance Degradation and Hang in `torch.diff` | WLFJ | open | [
"module: performance",
"triaged",
"oncall: pt2",
"module: inductor",
"topic: fuzzer"
] | 0 | NONE | ### 🐛 Describe the bug
I encountered a significant performance issue when using `torch.diff` within a `torch.compile` function. The issue occurs when increasing the `n` parameter of `torch.diff`, leading to extreme slowdowns.
test case:
```python
import torch
@torch.compile
def f(*args):
sym_0, sym_1, sym_2 = ... | true |
2,850,307,769 | [DONT MRGE][XPU] Add arl-h AOT target for windows cd | chuanqi129 | closed | [
"triaged",
"open source",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 9 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,850,284,758 | [DO NOT MERGE] Update oneDNN to the latest main branch | jiayisunx | open | [
"module: mkldnn",
"open source",
"topic: not user facing",
"ciflow/linux-aarch64"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147855
* #147360
* __->__ #147073
cc @gujinghui @PenghuiCheng @XiaobingSuper @jianyuh @jgong5 @mingfeima @sanchitintel @ashokei @jingxu10 @min-jean-cho @yanbing-j @Guobing-Chen @Xia-Weiwen @snadampal | true |
2,850,252,220 | [Inductor] Set prop_kind to forward_inference when grad is not needed for mkldnn_linear_pointwise and mkldnn_convolution_pointwise | jiayisunx | closed | [
"module: cpu",
"open source",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147855
* #147360
* #147359
* #147073
* __->__ #147072
Summary:
The `prop_kind` of `mkldnn._linear_pointwise`, `mkldnn._linear_pointwise.binary`, `mkldnn._convolution_pointwise.binary` and `mkldnn._convolution_pointwise_.binary` ar... | true |
2,850,232,112 | [Inductor][CPU] SIGSEGV in `torch.slice_copy` with large step value | WLFJ | closed | [
"high priority",
"module: crash",
"bug",
"oncall: pt2",
"oncall: cpu inductor",
"topic: fuzzer"
] | 2 | NONE | ### 🐛 Describe the bug
The following test case causes a SIGSEGV (Segmentation Fault) when run with `torch.compile`:
```python
import torch
@torch.compile
def f(input):
var_17 = torch.slice_copy(input, dim=0, start=449, end=None, step=9223372036854775807)
return torch.reciprocal(var_17)
input = torch.randn(... | true |
2,850,183,262 | [inductor][cpu] SIGILL with `torch.randint` | WLFJ | closed | [
"module: crash",
"bug",
"oncall: pt2",
"oncall: cpu inductor",
"topic: fuzzer"
] | 1 | NONE | ### 🐛 Describe the bug
When running the following test case with `torch.compile`, a SIGILL (Illegal Instruction) error occurs:
```python
import torch
@torch.compile
def f(*args):
sym_0, sym_1 = args
return torch.randint(high=sym_0, size=sym_1)
res = f(0, (3960,))
```
This leads to:
```
fish: Job 2, 'pyth... | true |
2,850,141,267 | [Inductor][CPP] Avoid transpose with cpp micro-gemm for FlexAttention | CaoE | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147069
* #147068
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,850,141,006 | [Inductor][CPP] Add transposed B matrix support for CppMicroGemmFP32Vec | CaoE | closed | [
"module: cpu",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147069
* __->__ #147068
* Add transposed B support for CppMicroGemmFP32Vec.
* Add support for cases where N is not divisible by `block_n`.
Expand CppMicroGemmFP32Vec to generate gemm kernel that supports transposed B and N of arbitrary s... | true |
2,850,140,775 | Separate transpose from memory load/store and add load size support for convert_to_int32 | CaoE | closed | [
"module: cpu",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147069
* #147068
* __->__ #147067
Separate transpose from memory load/store and add load size support for convert_to_int32 to facilitate the expansion for CppMicroGemmFP32Vec.
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei ... | true |
2,850,136,211 | OpenReg: Fix releasing tensor issue when using pin_memory | Zhenbin-8 | open | [
"triaged",
"open source",
"topic: not user facing"
] | 2 | CONTRIBUTOR | # Fail when exiting process
When executing the following code:
```
import pytorch_openreg
import torch
if __name__ == "__main__":
a = torch.tensor(1).pin_memory()
```
The process will exit with error. This is the same issue as https://github.com/pytorch/pytorch/pull/140936
# Fail when exiting python ge... | true |
2,850,132,294 | Issue with FBGEMM Operators in Exported PyTorch AOT Model When Running in C++: Cound not find schema for fbgemm:xxx | siluzhou-pku | closed | [
"oncall: pt2",
"oncall: export",
"module: aotinductor"
] | 1 | NONE | ### 🐛 Describe the bug
**Description**
I am encountering an issue when exporting a PyTorch model that uses `torch.ops.fbgemm.asynchronous_complete_cumsum` and running it in C++. The model works correctly in Python after adding `import fbgemm_gpu`, but fails when running in a C++ environment.
---
**Steps to Repro... | true |
2,850,090,484 | [torch/elastic] unexpected behavior of torch elastic | shinytang6 | open | [
"oncall: distributed",
"triaged",
"module: elastic"
] | 17 | NONE | ### 🐛 Describe the bug
Hi all, I conducted some simple tests using torch elastic to understand its behavior under node failures, and I encountered several unexpected outcomes against the official doc.
## Fault Tolerance & Elasticity test
Master node A command:
```shell
$ torchrun --nnodes=1:2 --nproc-per-node=1 -... | true |
2,850,086,396 | [DEBUG ONLY] vec flex attention and add UT | chunyuan-w | closed | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/periodic",
"module: inductor",
"ciflow/inductor"
] | 1 | 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 |
2,850,040,979 | [Feature Request] Release original parameters by layer when turning on `freezing_discard_parameters` | leslie-fang-intel | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 8 | COLLABORATOR | ### 🚀 The feature, motivation and pitch
`Freezing` is an Inductor configuration that converts input arguments into frozen parameters and applies constant folding to transform frozen parameters accordingly. There is an additional flag, `freezing_discard_parameters`, which, when enabled, discards parameters from the ea... | true |
2,849,963,534 | try print stacktrace for error | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Differential Revision: D69573525
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,849,951,908 | check if config.autotune_fallback_to_aten before using aten as a fallback | henrylhtsang | closed | [
"fb-exported",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Differential Revision: D69213269
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,849,938,625 | AttributeError: type object 'torch._C._distributed_c10d.BackendType' has no attribute 'XCCL'. | oraluben | open | [
"oncall: distributed",
"triaged",
"module: xpu"
] | 8 | CONTRIBUTOR | ### 🐛 Describe the bug
Found on 2.6+cu126 on aarch64
```
(venv) root@7dc30e9f3e4f:/workspace# pip3 install torch --index-url https://download.pytorch.org/whl/cu126
Looking in indexes: https://download.pytorch.org/whl/cu126, https://pypi.ngc.nvidia.com
Collecting torch ... | true |
2,849,870,079 | DISABLED test_comprehensive_nn_functional_interpolate_linear_cuda_float16 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_nn_functional_interpolate_linear_cuda_float16&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs... | true |
2,849,869,647 | DISABLED test_comprehensive_nn_functional_interpolate_bilinear_cuda_float64 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 6 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_nn_functional_interpolate_bilinear_cuda_float64&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/ru... | true |
2,849,837,329 | [Inductor][CPP] Fix node name for wgt delete | leslie-fang-intel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147056
**Summary**
This is a regression issue caused by a change in the FX node name. In commit 71010bf0972834e35a155e6a187e5c6649a5a36b, both the node name and target for the `get_attr` node in `V.graph.graph.nodes` were `_frozen_... | true |
2,849,836,496 | INTERNAL ASSERT FAILED or SEGFAULT when JITting a function that can return different types | MaigoAkisame | open | [
"oncall: jit"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Put the following code in `foo.py`. The `wtf` function may return either an int or a list.
```python
import torch
from typing import Any
@torch.jit.script
def wtf(flag: bool) -> Any:
return 1 if flag else list((2,))
```
Run `python foo.py`, and it'll trigger an `INTERNAL ASSERT FAILED` er... | true |
2,849,832,933 | Fix for issue #142834, Segmentation fault in replication_pad2d_backward | AmalDevHaridevan | open | [
"module: cpu",
"triaged",
"open source",
"Stale"
] | 3 | NONE | Fixes #142834
# Before fix
```python
import torch
grad_output = torch.full((2, 0, 6, 8,), 1, dtype=torch.float)
self = torch.full((2, 2, 4, 4,), 1, dtype=torch.float)
padding = [2, 2, 1, 1]
print("="*50)
print("input_tensor:")
print(self)
print("="*50)
print("output_tensor:")
print(grad_output)
print("... | true |
2,849,817,138 | Use 2022 as default VC_YEAR for windows builds | atalman | open | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ci-no-td"
] | 11 | CONTRIBUTOR | New Windows AMI does not have Visual Studio 2019. Hence use 2022 as default.
See: https://github.com/pytorch/test-infra/pull/6226 | true |
2,849,802,615 | [ONNX] Implement aten.stft | justinchuby | open | [
"module: onnx",
"triaged",
"OSS contribution wanted"
] | 4 | COLLABORATOR | Otherwise it is decomp to unfold and fft, which is more memory consuming I think. | true |
2,849,788,364 | Inductor Triton Gemm Autotune broke on the latest Triton | xuzhao9 | closed | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
On Triton latest main branch (commit 06941f490322679231aae20bfe20b61e9885ad4) and the latest PyTorch nightly branch, run the following script:
```
import torch
import torch._inductor.config as inductor_config
import triton
M = 20120
K = 512
N = 1536
a = torch.randn([M,N]).cuda()
b = torch.r... | true |
2,849,727,585 | More precise check for shared storage check in inductor/reinplace pass | laithsakka | 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):
* __->__ #147050
Currently if two tensor share storage we have some logic to avoid re-inplacing. Before this PR two tensors share storage if use same underlying storage even if they do not overlap. This diff enhance the checks to avoid cases ... | true |
2,849,715,553 | fake_tensor: Handle op errors more gracefully | c00w | open | [
"Stale",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"keep-going"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147049
if we have a operator error (i.e. incompatible dimensions etc... from
torch._check) within a faketensor, then it fails with
torch._dynamo.exc.TorchRuntimeError rather than gracefully falling back to be
unimplemnted and letting... | true |
2,849,687,783 | Feature Request: rsample for Von Mises distribution | dario-loi | open | [
"module: distributions",
"triaged",
"needs research"
] | 0 | NONE | ## 🚀 The feature, motivation and pitch
The von Mises-Fisher distribution implemented in `torch.distribution` should get an `.rsample()` method.
## Motivation
Backpropagating through vMF is essential to train Hyperspherical VAEs, which have drastically better performance for directional data, for example in graph re... | true |
2,849,683,648 | DISABLED test_comprehensive_sub_cuda_float16 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_sub_cuda_float16&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/37064610656).
Over the past... | true |
2,849,677,907 | [dynamo] Make SliceVariable a subclass of VariableTracker | 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):
* __->__ #147046
* #146995
* #146819
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames @StrongerXi | true |
2,849,666,326 | [cond] make cond call fake kernel in dynamo | ydwu4 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147130
* __->__ #147045
* #146954
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @Stronger... | true |
2,849,656,944 | Clean up backend_type_map from distributed_c10d | H-Huang | open | [
"oncall: distributed",
"triaged",
"better-engineering",
"module: c10d"
] | 0 | MEMBER | Try to remove `backend_type_map` since it doesn't look needed anymore and validate CI / internal tests pass.
https://github.com/pytorch/pytorch/blob/67cbbb29e075af848d95c936eca79e6645208107/torch/distributed/distributed_c10d.py#L282
cc @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,849,644,440 | UNSTABLE pull / win-vs2022-cpu-py3 / build | huydhn | closed | [
"module: windows",
"module: ci",
"triaged",
"unstable"
] | 2 | CONTRIBUTOR | The failure shows up after the new AMI ami-0403662469a2d1e25 rolls out. cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremyux @Blackhex @seemethere @malfet @pytorch/pytorch-dev-infra @atalman @Camyll
Same as https://github.com/pytorch/pytorch/issues/147041 | true |
2,849,631,166 | UNSTABLE trunk / win-vs2022-cuda12.1-py3 / build | huydhn | closed | [
"module: windows",
"module: ci",
"triaged",
"unstable"
] | 2 | CONTRIBUTOR | The failure shows up after the new AMI ami-0403662469a2d1e25 rolls out. cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremyux @Blackhex @seemethere @malfet @pytorch/pytorch-dev-infra @atalman @Camyll
Same as https://github.com/pytorch/pytorch/issues/147041 | true |
2,849,629,955 | UNSTABLE trunk / win-vs2022-cpu-py3 | huydhn | closed | [
"module: ci",
"triaged",
"unstable"
] | 2 | CONTRIBUTOR | The failure shows up after the new AMI `ami-0403662469a2d1e25` rolls out. cc @seemethere @malfet @pytorch/pytorch-dev-infra @atalman @Camyll | true |
2,849,627,598 | Updated test_cuda.py to rerun tests | BLOrange-AMD | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"keep-going",
"ciflow/rocm"
] | 13 | CONTRIBUTOR | Initially test_cuda::TestCudaMallocAsync::test_clock_speed and test_cuda::TestCudaMallocAsync::test_power_draw are skipped in this [commit](https://github.com/ROCm/pytorch/commit/d4871750d9ea0c36cfd5ff8a19a0b6aeedb729ad).
Pulled ROCm nightly image and verified these two tests run fine locally. Filed this PR to enabl... | true |
2,849,607,029 | [DCP] Introduce process based async checkpointing | MeetVadakkanchery | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: new features",
"release notes: distributed (checkpoint)",
"oncall: distributed checkpointing"
] | 26 | CONTRIBUTOR | Summary:
### Context
Background checkpoint upload thread interfering with trainer thread:
In [async save API](https://github.com/pytorch/pytorch/blob/main/torch/distributed/checkpoint/state_dict_saver.py#L239-L248), the background thread spends a considerable amount of time on CPU-bound tasks (pickling/unpickling ... | true |
2,849,595,740 | [Inductor] Graph Partition | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"topic: new features",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 3 | CONTRIBUTOR | This PR implements inductor graph partition. Previously, 1 dynamo graph is mapped to 1 inductor graph, and further mapped to 1 call function. In this PR, we allow 1 dynamo graph mapped to multiple inductor graphs and multiple `graph_partition` functions in the generated code. This allows applying different further opti... | true |
2,849,591,699 | Add CUDA 12.8 windows nightly build | tinglvv | closed | [
"open source",
"Merged",
"ciflow/binaries",
"topic: not user facing"
] | 10 | COLLABORATOR | https://github.com/pytorch/pytorch/issues/145570
windows AMI is deployed to prod today, prepping the windows cuda 12.8 build
cc @atalman @malfet @ptrblck @nWEIdia | true |
2,849,587,639 | test - bump up benchmarked epi choices | eellison | open | [
"Stale",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147036
* #147008
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,849,577,638 | fix pt2e block wise quantization test | cccclai | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: quantization"
] | 4 | CONTRIBUTOR | Differential Revision: D69559217
https://github.com/pytorch/pytorch/pull/145941 breaks the unit test added for prepare pt2e + block wise quantization. Fixing
| true |
2,849,573,447 | [ROCm] [TunableOp] Enable logging of BLAS parameters | naromero77amd | closed | [
"module: rocm",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 3 | COLLABORATOR | This PR supports a logging feature that is being requested.
```
PYTORCH_TUNABLEOP_BLAS_LOG=1
```
Enables the logging of BLAS parameters with either offline or online (in-situ) tuning.
The BLAS parameters are written to the CSV file.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr... | true |
2,849,556,310 | [Inductor-CPP] If all of the activation scale dims are 1, make it a 0D tensor | sanchitintel | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 10 | COLLABORATOR | For int8 dynamically quantized activation & int8 quantized weights, add a workaround for some indexing issue that expected an empty index ( so, was expecting a 0D tensor) in epilogue creator when the activation scale was sized [1, 1] by converting it into a 0D tensor.
The issue was discovered while running LLaMA2 qu... | true |
2,849,555,123 | [NJT] fix flop counter for SDPA & test | davidberard98 | closed | [
"module: nestedtensor",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"release notes: nested tensor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147032
Fixes 3 issues:
1. The test wasn't actually testing SDPA: both were checking cuda, and the inputs to SDPA were not transposed.
2. FlopCounterMode has been renamed _FlopCounterMode (and a wrapper named FlopCounterMode has been ... | true |
2,849,539,442 | Add self to CODEOWNERS for fx/proxy.py; warn against adding new node arg types | zou3519 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"fx"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #147031
* #147013
* #147012
* #147016
Not sure if there's a better way
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,849,539,316 | [inline_inbuilt_nn_modules] Move export to inline_inbuilt_nn_modules | anijain2305 | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
For export, we should not lift the parameters and buffers as inputs. We can register them in the Dynamo Fx graph. This will maintain the input signature constraint required by the export.
### Error logs
_No response_
### Versions
NA
cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 ... | true |
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