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 |
|---|---|---|---|---|---|---|---|---|
2,764,105,070 | ERROR: Could not find a version that satisfies the requirement torch (from versions: none) | ruidazeng | closed | [
"module: binaries",
"triaged",
"module: python version"
] | 2 | NONE | ### 🐛 Describe the bug
```console
ruidazeng@Ruidas-Laptop demo % pip3 install torch
ERROR: Could not find a version that satisfies the requirement torch (from versions: none)
ERROR: No matching distribution found for torch
ruidazeng@Ruidas-Laptop demo % pip3 install torch torchvision torchaudio --index-url ht... | true |
2,764,097,499 | [BE] Add stride check in `torch.max_pool1d()` | shink | closed | [
"module: cpu",
"triaged",
"open source",
"Stale"
] | 6 | CONTRIBUTOR | Fixes #142454
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,764,095,264 | Fix grad_scaler for MPS, which doesn't support FP64 | masc-it | closed | [
"triaged",
"open source",
"module: amp (automated mixed precision)",
"Stale"
] | 4 | NONE | - remove fp64 intermediate cast if on mps device
Original error:
```
scaler.unscale_(optimizer)
File "..../lib/python3.10/site-packages/torch/amp/grad_scaler.py", line 335, in unscale_
inv_scale = self._scale.double().reciprocal().float()
TypeError: Cannot convert a MPS Tensor to float64 dtype as the MP... | true |
2,764,071,912 | Torch compile scaled_dot_product_attention NAN | keilsmart | closed | [
"triaged",
"oncall: pt2",
"module: dynamic shapes",
"module: inductor"
] | 3 | NONE | ### 🐛 Describe the bug
```
def test_sdpa():
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, q, k, v):
x = torch.nn.functional.scaled_dot_product_attention(q, k, v)
return x
model = Model().cuda().eval... | true |
2,764,055,445 | [Inductor] Support parallel reduction for GroupNorm | jiayisunx | closed | [
"open source",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 8 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144020
Summary:
Support parallel reduction for GroupNorm by optimizing the parallelization heuristics: When the range of the first inner loop is much larger than the range of all outer loops, change the starting depth of paralleliz... | true |
2,764,028,942 | Remove unused setDataLoaderSignalHandlers | cyyever | closed | [
"module: dataloader",
"triaged",
"open source",
"Stale",
"ciflow/trunk",
"topic: not user facing"
] | 9 | COLLABORATOR | setDataLoaderSignalHandlers isn't used in repositories under the PyTorch organization.
cc @andrewkho @divyanshk @SsnL @VitalyFedyunin @dzhulgakov | true |
2,763,997,898 | RuntimeError: invalid dtype for bias - should match query's dtype | hayatkhan8660-maker | closed | [] | 2 | NONE | ### 🐛 Describe the bug
I am training the X-CLIP model using a multi-GPU setup (3 GPUs). However, when I start the training process, I encounter the following error:
" **RuntimeError: invalid dtype for bias - should match query's dtype** "
Here is the complete traceback of the error:
UserWarn... | true |
2,763,941,806 | Use _cvtss_sh and _cvtsh_ss for scalar conversion of Half on AVX512 | CaoE | closed | [
"module: cpu",
"open source",
"Stale",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | COLLABORATOR | Using `_cvtss_sh` and `_cvtsh_ss` on AVX512 can get better performance for scalar conversion of Half.
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @Colin... | true |
2,763,919,490 | Fix to torch.hub documentation grammar mistakes. | AriyanPandian | closed | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 5 | NONE | Proper punctuation and filler words added to the torch.hub documentation to fix the grammar mistakes.
| true |
2,763,915,936 | [inductor] [cuda] [fake tensor] `ConvTranspose` behave differently when Input type and weight type are not the same | shaoyuyoung | open | [
"triaged",
"module: type promotion",
"oncall: pt2",
"module: inductor"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**:
trigger condition1: only set the `input tensor` for cuda, but not set the `model.cuda()`
trigger condition2: `padding` param is necessary, otherwise, inductor will also raise the error.
**device**: `cuda` only
**exposed area**: `ConvTranspose1d`, `ConvTranspose2d`, `ConvT... | true |
2,763,912,055 | [18/N] Fix extra warnings brought by clang-tidy-17 | cyyever | closed | [
"module: cpu",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"ciflow/s390"
] | 3 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,763,909,869 | [inductor] [cpu] [graph optimization] output size calculation behaves differently of `ConvTranspose1d`, `ConvTranspose2d`, `ConvTranspose3d` along with `sigmoid` | shaoyuyoung | closed | [
"oncall: pt2",
"oncall: cpu inductor"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
**symptom**:
trigger condition1: for `ConvTranspose`, the output size calculation formula is: $O=(I−1)×S+K−2×P$. When the O is zero, eager will raise the error but the inductor will pass the check and return an empty tensor.
trigger condition2: `ConvTranspose` must be along with `sigmoid`... | true |
2,763,883,449 | [RFC] Add CPP Grouped GEMM Template for Inductor CPU | leslie-fang-intel | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 3 | COLLABORATOR | ### 🚀 The feature, motivation and pitch
## Motivation
Grouped GEMM is a common pattern in modeling. For example, in the `LlamaMLP` module (https://github.com/huggingface/transformers/blob/d5aebc64653d09660818109f2fac55b5e1031023/src/transformers/models/llama/modeling_llama.py#L187-L188), the `gate_proj` and `up_proj... | true |
2,763,838,638 | [AsyncMM] re-enable and adapt to cutlass 3.6.0 | yifuwang | closed | [
"oncall: distributed",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: distributed (c10d)",
"topic: not user facing",
"ci-no-td"
] | 15 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144011
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o
[D68734067](https://our.internmc.facebook.com/intern/diff/D68734067) | true |
2,763,829,050 | Native channel shuffle floating point exception | abcarlisle | closed | [
"module: nn",
"triaged",
"open source",
"Merged",
"Stale",
"ciflow/trunk",
"release notes: nn"
] | 11 | CONTRIBUTOR | Fixes #142453
Added TORCH_CHECKS to prevent the user from using the native_channel_shuffle function incorrectly and getting a "Floating point exception (core dumped)"
cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki | true |
2,763,822,967 | [CUDA] Check `size` calculation in `ilpReduce` for `softmax` | eqy | closed | [
"module: cuda",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"ciflow/periodic"
] | 17 | COLLABORATOR | For #143644
cc @ptrblck @msaroufim | true |
2,763,819,957 | Brister/always tiled reduction | blaine-rister | closed | [
"Stale",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
Test the CI with tiled reductions always on. This might catch some bugs.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,763,815,395 | [ROCm] fix torch.layer_norm invalid configuration problem when input is large tensor | hongxiayang | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda",
"ciflow/rocm"
] | 5 | COLLABORATOR | Fixes #136291
This PR is to fix the `invalid configuration argument` problem happened on ROCm when input is a large tensor when calling `torch.layer_norm`.
```
File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 2573, in layer_norm
return torch.layer_norm
RuntimeError: H... | true |
2,763,769,352 | [inductor] Add missing py312 xfail | jansel | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144006
See #144006
```py
__________________________________________ CudaReproTests.test_repeated_masked_load __________________________________________
RuntimeError: First class dim doesn't work with python 3.12
The above ... | true |
2,763,769,278 | [tp] propagate src_data_rank kwarg in TP API | wanchaol | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (dtensor)"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144005
* #143883
as titled, this PR propagates the src_data_rank in the TP API, so that
module level APIs could leverage the flexibility to choose
src_data_rank, and avoid the communication if it does not need to
cc @H-Huang @awgu @... | true |
2,763,740,997 | [inductor] Add types to compile_tasks.py and runtime_utils.py | jansel | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144044
* __->__ #144004
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aak... | true |
2,763,726,644 | [dynamo][guards][feature] Do not realize LazyVariableTracker on `isinstance` checks | anijain2305 | closed | [
"triaged",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Today, calling `isinstance` on LazyVariableTracker realizes the VT, inserting the guards. In many cases, this guard insertion is accidental and not really required for program correctness.
I am not sure how to do this exhaustively. Maybe we can look at the value of the LazyVariableTracker an... | true |
2,763,712,468 | cpp_wrapper: Precompile device-specific header files | benjaminglass1 | closed | [
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 14 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146452
* #146706
* #146424
* #146109
* #146449
* #144349
* #144293
* __->__ #144002
This saves us about a second per compilation, which is _massive_ for the OpInfo tests. Total OpInfo test runtime is down about 2x from this change alone.
... | true |
2,763,664,004 | torch.utils.flop_counter.FlopCounterMode | yaoshiang | open | [
"triaged",
"module: flop counter"
] | 1 | NONE | I found this class because it was referenced in the llama_recipes repo.
My question is whether this definition counts one addition and one multiplication and 2 FLOPs, or, if that's counted as 1 FLOP?
When reporting on GPU hardware, it's common to count the above as two flops.
But when reporting on models, it's... | true |
2,763,626,385 | [Submodule] Bump Cutlass to 3.5.1 OSS PR | drisspg | closed | [
"module: cuda",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: float8"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144180
* __->__ #144000
## Summary
Follow up PR to https://github.com/pytorch/pytorch/pull/143515. That PR added a bunch of macro switches to ensure both 3.4 and 3.5.1 built succesfully. This PR actual bumps the cutlass pin to 3.5.1.... | true |
2,763,626,321 | [cutlass-3] Update third-party/cutlass-3 from 3.4 to 3.5.1 (#143515) | drisspg | closed | [
"oncall: distributed",
"ciflow/trunk",
"release notes: sparse",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144011
* #144000
* __->__ #143999
Summary:
This commit was generated using `mgt import`.
pristine code for third-party libraries:
third-party/cutlass-3
uuid_71a50b25d7734c28883759737fadc750
This also makes updates to different repositori... | true |
2,763,617,445 | [MPSInductor] Fix multiple kernel generation | 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):
* #143966
* __->__ #143998
* #143977
* #143973
* #143949
* #143948
At the moment by generating multiple MetalLibraries
`pytest test/inductor/test_torchinductor.py -k _mps` score is 434 failed, 317 passed, 32 skipped
cc @voznesenskym @pe... | true |
2,763,601,679 | [dynamo][dicts] Guarding lazily on dict keys | anijain2305 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"keep-going",
"ci-no-td"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144342
* #144165
* __->__ #143997
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,763,567,547 | pytorch with xpu support fails to eval pre trained models | farooqkz | closed | [
"triaged",
"module: xpu"
] | 11 | NONE | ### 🐛 Describe the bug
I have installed pytorch as written here(the preview build): https://pytorch.org/docs/main/notes/get_start_xpu.html
Then I'm trying the first example code from the same page:
```
import torch
import torchvision.models as models
model = models.resnet50(weights="ResNet50_Weights.DEFAUL... | true |
2,763,535,977 | Add networkx as bazel dep to fix CI failure | clee2000 | closed | [
"Merged",
"topic: not user facing",
"ciflow/periodic"
] | 3 | CONTRIBUTOR | Add networkx as a dependency for test_bazel
Example failure: https://github.com/pytorch/pytorch/actions/runs/12551752021/job/34996706301
```
INFO: From Testing //:test_bazel:
==================== Test output for //:test_bazel:
Traceback (most recent call last):
File "/var/lib/jenkins/.cache/bazel/_bazel_j... | true |
2,763,495,538 | DISABLED test_setting_meta_device_model_broadcasting_and_memory (__main__.TestStateDict) | clee2000 | closed | [
"oncall: distributed",
"module: rocm",
"triaged",
"skipped"
] | 3 | CONTRIBUTOR | Platforms: rocm
Started probably at https://github.com/pytorch/pytorch/pull/142845
https://hud.pytorch.org/hud/pytorch/pytorch/9d026000de01bbd4d5c97bdca88cc6228507617a/3?per_page=100&name_filter=distributed&mergeLF=true
https://github.com/pytorch/pytorch/actions/runs/12409302699/job/34672198799
This test ... | true |
2,763,495,103 | Return attention weights in scaled_dot_product_attention | mseeger | closed | [
"triaged",
"module: sdpa"
] | 0 | NONE | ### 🚀 The feature, motivation and pitch
I'd like to reopen the request #119811, but for a special case, namely generative inference, where the Q tensor is very small (just a single token). The request is to return the attention weights along with the normal MHA output.
Why is this important? In order to implement ... | true |
2,763,490,748 | [CI] Multigpu 1 -> 2 shards | clee2000 | closed | [
"Merged",
"topic: not user facing",
"ciflow/periodic"
] | 3 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
It's been timing out https://github.com/pytorch/pytorch/actions/runs/12544191739/job/34977636276
They're still somewhat uneven but they're both under the limit now. It would probably be better to use run_test.py's sharding to do this, maybe in another PR | true |
2,763,486,125 | Fix flaky "Upload test stats" job | benjaminglass1 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143991
Test stat uploading was intermittently failing due to certain XML strings being opportunistically converted to numbers, when string output was expected. This PR makes the conversion behavior optional, which should fix the stat... | true |
2,763,471,382 | [AOTI] don't codegen autotune_at_compile_time for non-Triton kernels | ColinPeppler | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | `autotune_at_compile_time` is a separate codegen file specifically for autotuning Triton kernels. We can skip it for non-Triton kernels (like CUTLASS).
This test (test_aoti_workspace_ptr) checks that `workspace_0.data_ptr()` is codegen-ed correctly in AOTI.
```
// in AOTI codegen
kernels.cuda_fused_0(
(const... | true |
2,763,470,826 | [FSDP] Add workaround to fix `buffer_dtype` without root parameters | awgu | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (fsdp)",
"ciflow/inductor"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143989
Fixes https://github.com/pytorch/pytorch/issues/143900
cc @H-Huang @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,763,437,747 | Add a knob to control how many blocks are used by persistent matmul/attn kernels | lw | closed | [
"module: cuda",
"triaged",
"module: cublas",
"module: linear algebra"
] | 3 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
We train a transformer-style model using FSDP, and we have a very good overlap between the matmul kernels (from cuBLAS) and the NCCL operation in the background. However, when profiling, we have observed that the **matmuls take 2x as long** to complete when they are overlapped ... | true |
2,763,378,477 | Enable several readability checks | cyyever | open | [
"oncall: distributed",
"module: cpu",
"triaged",
"open source",
"release notes: cpp",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 5 | COLLABORATOR | They are about add const to members and parameters and other fixes.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ch... | true |
2,763,362,589 | [ROCm] Fix for ld failed to convert GOTPCREL relocation in PyTorch build | hongxiayang | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 14 | COLLABORATOR | I experienced an error while doing a DEBUG build of pytorch on rocm:
```
additional relocation overflows omitted from the output
/usr/bin/ld: failed to convert GOTPCREL relocation; relink with --no-relax
```
Based on discussions on similar issue #138427, I fixed it after adding the `--offload-compress` to the HIP... | true |
2,763,348,025 | [DTensor] Allow multiple dimensions to be sharded together (as if flattened) | lw | open | [
"oncall: distributed",
"module: dtensor"
] | 6 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
PyTorch's utilities for sequence parallelism seem to suppose that tensors will have two separate dimensions for batch (dim 0) and sequence (dim 1), and shard only along dim 1. However, if batch > 1, this means that each rank's shard will be non-contiguous. This is a problem bec... | true |
2,763,312,863 | Update torch-xpu-ops commit pin | xytintel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu"
] | 9 | CONTRIBUTOR | Update the torch-xpu-ops commit to [28cfac20ec662abdb0ac98faf122450013e8f520](https://github.com/intel/torch-xpu-ops/commit/28cfac20ec662abdb0ac98faf122450013e8f520), includes:
- Disable batch_norm vectorization path to fix accuracy issues.
- Fix the LSRM/RNN implementation error.
cc @voznesenskym @penguinwu @... | true |
2,763,266,524 | [CD] Remove redundant triton dependency for xpu wheels | pytorchbot | closed | [
"open source",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 1 | COLLABORATOR | Due to XPU CD wheels enabled pypi dependencies by https://github.com/pytorch/pytorch/pull/141135, so the PYTORCH_EXTRA_INSTALL_REQUIREMENTS has value for XPU CD wheel build.
Works for https://github.com/pytorch/pytorch/issues/139722 and https://github.com/pytorch/pytorch/issues/114850
Fixes #143838
| true |
2,763,069,223 | Enable readability-redundant-declaration | cyyever | closed | [
"oncall: distributed",
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"module: dynamo",
"ciflow/inductor"
] | 9 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,763,033,498 | Fix typo: change 'recieve' into 'receive' | loricR | closed | [
"open source",
"Stale",
"release notes: releng",
"module: dynamo"
] | 3 | NONE | Fix typo: change all occurrences of 'recieve' to 'receive'.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,762,923,074 | Fixed bug in FindMKL.cmake | mmoelle1 | closed | [
"module: build",
"triaged",
"open source",
"Stale"
] | 4 | NONE | This PR fixes the CMake error
```
CMake Error at cmake/Modules/FindMKL.cmake:195 (IF):
if given arguments:
"UNIX" "AND"
Unknown arguments specified
Call Stack (most recent call first):
cmake/Modules/FindMKL.cmake:353 (GET_MKL_LIB_NAMES)
cmake/Modules/FindBLAS.cmake:99 (FIND_PACKAGE)
CMakeLi... | true |
2,762,835,405 | [ci] Add riscv opt-int build | zhangfeiv0 | open | [
"module: build",
"triaged",
"open source",
"release notes: releng",
"module: risc-v"
] | 28 | CONTRIBUTOR | Hi, @malfet
Based on the previous discussion:
[RISCV CI support · Issue #141550 · pytorch/pytorch](https://github.com/pytorch/pytorch/issues/141550)
I have cross-compiled PyTorch for the RISC-V architecture on x86_64 Ubuntu 24.04 and created a new PR for it. Could you please help review it?
cc @malfet @seeme... | true |
2,762,764,855 | torch.compile() returns a different value than interpreted (NaN vs 1) | dcci | open | [
"module: cpu",
"module: NaNs and Infs",
"oncall: pt2",
"oncall: cpu inductor"
] | 5 | MEMBER | ### 🐛 Describe the bug
Snippet:
```python
import torch
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
x = torch.rsqrt(x)
x = torch.angle(x)
x = torch.atan(x)
x = torch.positive(x)
x = torch.sin(x)
... | true |
2,762,727,380 | [MPSInductor] Implement minimum and maximum ops | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143966
* #143998
* __->__ #143977
* #143973
* #143949
* #143948
By calling `metal::min` and `metal::max` respectively with argument
typecast to a common type to avoid ambiguous calls errors
TODO: Implement NaN propagation for both eage... | true |
2,762,725,089 | `torch.maximum` and `torch.minimum` do not propagate nans on MPS | malfet | closed | [
"triaged",
"module: NaNs and Infs",
"module: mps"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Consider running the following
```python
import torch
x = torch.rand(32, device="mps")
y = torch.rand(32, device="mps")
x[3] = torch.nan
y[5] = torch.nan
print(x.isnan().any().item(), torch.minimum(x, y).isnan().any().item())
```
It will print `True False`, but should have `True True`
... | true |
2,762,692,608 | [Inductor UT] Generalize newly introduced device-bias hard code in | etaf | closed | [
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/xpu",
"ci-no-td"
] | 7 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143975
test_pattern_matcher.py
Fix #143974
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @... | true |
2,762,691,348 | [Break XPU] Hard code “cuda” in GPU test case cause failure on XPU. | etaf | closed | [
"triaged",
"module: xpu"
] | 0 | COLLABORATOR | ### 🐛 Describe the bug
The PR #139321 introduce a new test case `torch/_inductor/pattern_matcher.py:test_duplicate_search` which is not specified requires_cuda but hard code device type `cuda`, cause it fails on XPU.
https://github.com/pytorch/pytorch/blob/2ed4d65af0a1993c0df7b081f4088d0f3614283e/test/inductor/... | true |
2,762,687,827 | [MPSInductor] Fix index generation for transpose | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: improvements",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143966
* #143998
* #143977
* __->__ #143973
* #143949
* #143948
Alas, PythonPrinter would not work here, not would CppPrinter, so start building MetalPrinter.
`pytest test/inductor/test_torchinductor.py -k _mps` score is 474 failed, 277... | true |
2,762,650,199 | [DCP] dcp.load leads to param type mismatch. | nanlliu | closed | [
"oncall: distributed",
"oncall: distributed checkpointing"
] | 4 | NONE | ### 🐛 Describe the bug
I tried to load a dcp saved checkpoint on a single GPU.
However, when I loaded optimizer state using `set_optimizer_state_dict` and it led to following error:
I'd expect `BytesStorageMetadata` is the same as`torch.distributed.checkpoint.metadata.BytesStorageMetadata`?
```
Checkpoin... | true |
2,762,648,306 | [ROCm] enable CK backend for bf16/fp16 on gfx11 | jfactory07 | closed | [
"module: rocm",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 30 | CONTRIBUTOR | this change enables enable CK backend for fp16 on Gfx11
@jeffdaily
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,762,601,723 | [AOTI] Not use AOTI_TORCH_CHECK in non AOTI mode. | etaf | 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):
* __->__ #143970
Fix #143967
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aa... | true |
2,762,600,557 | [distributed] parallelize_module error with `SequenceParallel` | gameofdimension | open | [
"oncall: distributed",
"triaged"
] | 5 | NONE | ### 🐛 Describe the bug
repro code:
run with `torchrun --nproc-per-node=8 --local-ranks-filter=1 -m bad_match`
```python
import os
from typing import Optional, Tuple
import torch
import torch.distributed as dist
from torch import nn
from torch.distributed.device_mesh import init_device_mesh
from tor... | true |
2,762,599,514 | change import relative paths due to internal build failures | wdvr | closed | [
"module: cpu",
"Merged",
"ciflow/trunk",
"release notes: quantization"
] | 4 | CONTRIBUTOR | Internal builds failing due to #143355, changing imports to be relative, similar to other imports
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,762,590,304 | [AOTI] run without AOTI but get "unresolved external symbol aoti_torch_check referenced in function kernel" on Windows. | etaf | closed | [
"module: windows",
"triaged",
"oncall: pt2",
"oncall: export",
"module: aotinductor"
] | 0 | COLLABORATOR | ### 🐛 Describe the bug
Hi, I ran into an AOTI problem while running CPU Inductor on Windows, but I'm not using AOTI, the error is: “unresolved external symbol aoti_torch_check referenced in function kernel”.
The root cause is in cpp kernel codegen `CppKernel::assert_function`, we always use AOTI_TORCH_CHECK for... | true |
2,762,586,049 | [WIP] Enable MPS inductor testing | malfet | closed | [
"Stale",
"ciflow/trunk",
"topic: not user facing",
"ciflow/mps",
"keep-going"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143966
| true |
2,762,583,066 | test case got killed file_based_local_timer_test.py test_get_timer_recursive | garfield1997 | open | [
"module: tests",
"triaged"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
test case get killed when running test file_based_local_timer_test.py::FileTimerTest::test_get_timer_recursive
output
```
python file_based_local_timer_test.py -k 'test_get_timer_recursive'
Killed
```
### Versions
main
cc @mruberry @ZainRizvi | true |
2,762,546,651 | [Submodule] Bump flatbuffers to v24.12.23 | cyyever | closed | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 4 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,762,513,145 | Enable more readability-redundant checks | cyyever | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cpp",
"module: dynamo",
"ciflow/inductor"
] | 7 | COLLABORATOR | They are helpful to simplifying code.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,762,483,143 | Nightly pytorch wheel for prerelease version 2.6 is build with C++11 ABI on, at least for CPU | jeffhataws | closed | [
"module: binaries",
"module: abi",
"triaged"
] | 12 | NONE | ### 🐛 Describe the bug
When we install nightly pytorch 2.6 and test it with torch-xla 2.6, it appears the CPU version is build with C++11 ABI on, causing error with torch-xla.
```
(aws_neuron_venv) [ec2-user@ip-10-1-17-115 ~]$ pip install --force-reinstall --no-deps torch --index-url https://download.pytorch.org... | true |
2,762,456,333 | [poc][not-ready-for-review] visualize dynamic shapes shape env mutations over time | bobrenjc93 | closed | [
"Stale",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 11 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143961
logs to /tmp/ds.txt and you can copy and paste it into https://stateviz.vercel.app/
Differential Revision: [D69164764](https://our.internmc.facebook.com/intern/diff/D69164764)
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @... | true |
2,762,346,118 | torch.dist is more numerical unstable on scalar input after torch.compile | meetmul | closed | [
"module: numerical-stability",
"triaged",
"oncall: pt2"
] | 0 | NONE | ### 🐛 Describe the bug
It seems that torch.dist is more numerical unstable after torch.compile. Interestingly, this issue only occurs when `a` and `b` are scalar. If `a` or `b` contains more than one element, torch.dist has consistent result (and consistent numerical stability) after torch.compile.
To reproduce
`... | true |
2,762,321,912 | Defaults to C++20 in CMake torch targets | cyyever | open | [
"module: cpp",
"module: cpu",
"open source",
"NNC",
"release notes: build",
"topic: not user facing",
"ciflow/periodic",
"topic: build",
"ciflow/s390"
] | 2 | COLLABORATOR | Some initial attempts.
cc @jbschlosser @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @EikanWang | true |
2,762,304,100 | using more descriptive alt text for accessibility | netra212 | closed | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 3 | NONE |
## Changes Made:
### Updated alt text for images to provide more descriptive and contextually relevant descriptions.
Example: Changed "Tensor illustration" to "Illustration of a Tensor operation in PyTorch."
This will ensure the alt text aligns with accessibility best practices & enhancing clarity and inclusivit... | true |
2,762,281,852 | Enable readability-qualified-auto in clang-tidy | cyyever | closed | [
"oncall: distributed",
"open source",
"release notes: cpp",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 1 | COLLABORATOR | Auto * indicates that the type is pointer. Another benefit is const when possible.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amj... | true |
2,762,194,100 | Add ability to skip compute capability checks for Triton | sasha0552 | closed | [
"triaged",
"open source",
"Stale",
"topic: improvements",
"module: inductor",
"release notes: inductor"
] | 6 | NONE | This PR adds an environment variable `TORCH_TRITON_SKIP_CC_CHECKS` that allows to skip CUDA compute compatibility checks, which is useful if the user is using [a custom Triton build](https://github.com/sasha0552/pascal-pkgs-ci) that does support older hardware.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing... | true |
2,762,112,534 | Issue with aten::_sparse_coo_tensor_with_dims_and_tensors on Apple Silicon GPU (MPS) Backend when Using Whisper Model | Proton1917 | open | [
"module: sparse",
"feature",
"triaged",
"module: mps"
] | 0 | NONE | ### 🐛 Describe the bug
## Description
Error occurs while running Whisper model on MPS. The operation `aten::_sparse_coo_tensor_with_dims_and_tensors` fails to fallback to CPU with `PYTORCH_ENABLE_MPS_FALLBACK=1`.
### Minimal Code to Reproduce the Issue
```python
import whisper
device = "mps" if torch.b... | true |
2,762,098,764 | No ONNX function found for <OpOverload(op='quantized_decomposed.dequantize_per_channel', overload='default')> | ruixupu | open | [
"module: onnx",
"triaged",
"OSS contribution wanted"
] | 3 | NONE | ### 🐛 Describe the bug
We tried to leverage per_channel quantization in QAT and exported the trained model in onnx format.
```py
model = dummy pytorch model
export_model = torch.export.export_for_training(
model, example_inputs).module()
quantizer = XNNPACKQuantizer().set_global(get_symmetric_quantiz... | true |
2,762,094,866 | Missing 'torch' wheel for version '1.8.2' in official index | hwhsu1231 | closed | [
"module: binaries",
"oncall: releng"
] | 1 | NONE | ### 🐛 Describe the bug
Recently, I tried to install Torch [1.8.2](https://github.com/pytorch/pytorch/tree/v1.8.2) package with following command:
```bash
pip install torch==1.8.2 --index-url=https://download.pytorch.org/whl --progress-bar=off --verbose
```
However, it failed with the following error:
```... | true |
2,762,060,575 | RegisterCPU.cpp likely needs to be sharded | swolchok | closed | [
"module: build",
"triaged"
] | 0 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
We shard other generated files, but apparently not this one. I attempted to build PyTorch on Raspberry Pi 5 and came back hours later to an unresponsive Pi 5 with "Building CXX object caffe2/CMakeFiles/torch_cpu.dir/__/aten/src/ATen/RegisterCPU.cpp.o" on the screen (suggestin... | true |
2,762,059,678 | [inductor] Make generated kernels deterministic | jansel | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143951
`"compile_id"` had slipped into our generated Triton code (in the
metadata), which will defeat caching because the same kernels generated
in a different order would not cache hit with eachother.
cc @voznesenskym @penguinwu @E... | true |
2,762,058,344 | Remove aten/src/ATen/core/Array.h | cyyever | closed | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 5 | COLLABORATOR | It's not used in OSS and not part of public API. | true |
2,761,980,859 | [MPS] Fix `torch.add(x,y, alpha=2)` crash | malfet | closed | [
"Merged",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143966
* #143977
* #143973
* __->__ #143949
* #143948
TODO: as followup PR replace this weird logic with shaders
Fixes https://github.com/pytorch/pytorch/issues/143932
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @Xiaob... | true |
2,761,980,841 | [MPS] Fix crash when mm is invoked with mixed dtypes | malfet | closed | [
"Merged",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143966
* #143977
* #143973
* #143949
* __->__ #143948
Simply by copy-n-pasting check from
https://github.com/pytorch/pytorch/blob/a7915c56f6a62266490be355b3d823b1e447a475/aten/src/ATen/native/cuda/Blas.cpp#L254-L257 | true |
2,761,909,094 | Add differentiable flag to SGD | EmmettBicker | open | [
"module: optimizer",
"triaged"
] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
When using SGD on cuda, it defaults to the foreach implementation. Because SGD is so simple, this often doesn't call any non differentiable operations, but when using weight_decay, it calls _foreach_add which is nondifferentiable.
Currently, to make cuda SGD w/ weight_dec... | true |
2,761,909,086 | Support getattr for tensor subclasses in pre-dispatch export via patching tensor.getattr | tugsbayasgalan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"release notes: export"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143946
Previous discussion: https://github.com/pytorch/pytorch/pull/143671#issuecomment-2560112499 and https://github.com/pytorch/pytorch/pull/143671
Differential Revision: [D67693609](https://our.internmc.facebook.com/intern/dif... | true |
2,761,909,051 | Fix subclass unwrapping bug | tugsbayasgalan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143946
* __->__ #143945
I noticed a small bug in tensor subclass unwrapping logic. cc @IvanKobzarev
It seems easier if we just implement it recursively so that it is easier to track the inner attrs to corresponding plain tensors and both ... | true |
2,761,815,361 | remove allow-untyped-defs from _export/pass_infra/proxy_value.py | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"release notes: export"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143944
| true |
2,761,815,337 | remove allow-untyped-defs from onnx/_internal/_lazy_import.py | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143944
* __->__ #143943
| true |
2,761,815,323 | remove allow-untyped-defs from torch/_size_docs.py | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143944
* #143943
* __->__ #143942
| true |
2,761,815,307 | remove allow-untyped-defs from _inductor/compile_worker/watchdog.py | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143944
* #143943
* #143942
* __->__ #143941
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @deser... | true |
2,761,806,414 | Fix assertion failure in pytorch profiler | kadeng | closed | [
"fb-exported",
"oncall: profiler",
"Merged",
"ciflow/trunk",
"release notes: profiler",
"topic: bug fixes",
"topic: not user facing"
] | 55 | CONTRIBUTOR | Summary:
Attempt to fix the following exception which occurred when profiling a Pytorch model ( Meta-internal LLM ) that also involved a ThreadPoolExecutor in the background:
```
Exception Found: !stack.empty() INTERNAL ASSERT FAILED at "fbcode/caffe2/torch/csrc/autograd/profiler_python.cpp":987, please report a bug... | true |
2,761,794,768 | Add "enabled=True" argument to DistributedDataParallel.no_sync() | avihu111 | closed | [
"oncall: distributed",
"triaged",
"open source",
"Stale",
"release notes: distributed (ddp)"
] | 8 | NONE | The `ddp.no_sync(enabled=True)` allows easier implementation of gradient accumulation/syncing mechanisms and will help to prevent code duplications.
It is a small and backward-compatible change.
Additional Details in Issue #143721
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p... | true |
2,761,787,624 | Modify old differentiable optimizer tests to use optim_db | EmmettBicker | closed | [
"module: optimizer",
"module: tests",
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 8 | CONTRIBUTOR | Fourth PR in a larger project to broaden differentiable optimizer support with @janeyx99 ! This one is the first step in Step 0.
This PR replaces the 14 old differentiable tester functions with one differentiable tester function that uses optim_db and assures that the gradient can flow through the optimizer wrt para... | true |
2,761,774,245 | [BE][Ez]: Update fmtlib submodule to 1.11.1 | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | * Exactly the same as previous fmtlib except it fixes an edgecase that could affect ABI compatibility between fmtlib versions.
* Seems safe to update | true |
2,761,632,431 | pytorch v2.3.1 build failed - CUDA kernel function | lida2003 | closed | [
"module: build",
"triaged",
"module: jetson",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention",
"module: sdpa"
] | 5 | NONE | ### 🐛 Describe the bug
pytorch v2.3.1 build for nvidia jetson orin nano 8GB failed - CUDA kernel function
After fixing [the memory(increased to 8GB sawp file) issue](https://github.com/pytorch/pytorch/issues/143856), I still can't compile the code. The issue seems to be related to a missing return statement in a C... | true |
2,761,578,763 | [MPS] Fix fmin/fmax for scalar argument | malfet | closed | [
"Merged",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #143934
CPU scalar promotion to GPU is allowed for CUDA and shoudl be allowed for MPS as well (at the very least it should not crash)
Fixes https://github.com/pytorch/pytorch/issues/143933 https://github.com/pytorch/pytorch/issues... | true |
2,761,562,753 | torch.fmax() between MPS tensor and CPU scalar crashes | malfet | closed | [
"module: crash",
"triaged",
"module: regression",
"module: mps"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Discovered while running `python ../test/inductor/test_torchinductor.py -v -k test_fmin_fmax_mps`
But could be reproduced as single line:
```
python -c "import torch;print(torch.fmax(torch.rand(7, device='mps'), torch.tensor(.3)))"
```
### Versions
2.5.1, nightly
cc @kulinseth @alb... | true |
2,761,534,399 | `torch.add` between float and int crashes when alpha is specified | malfet | closed | [
"module: crash",
"triaged",
"module: mps"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Discovered while attempted to run test_torchinductor.py
```
% python test/inductor/test_torchinductor.py -v -k test_add_const_int_mps
test_add_const_int_mps (__main__.GPUTests.test_add_const_int_mps) ... (mpsFileLoc): /AppleInternal/Library/BuildRoots/b11baf73-9ee0-11ef-b7b4-7aebe1f78c73/Lib... | true |
2,761,388,595 | The model compiled with torch.compile encounters an error when run. | WangGewu | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | ### 🐛 Describe the bug
I have an LLM and I used torch.compile to compile the function for each step of decoding. After that, I encapsulated a server-side interface using Flask. When I make two concurrent calls, I encounter an error as follows:
```
nknown:0: unknown: block: [1,0,0], thread: [32,0,0] Assertion `ind... | true |
2,761,372,603 | [Torch.package] Add support for UntypedStorage tensors | henryhu6 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: package/deploy"
] | 11 | CONTRIBUTOR | Summary: fp8 uses untyped storage. Add support for torch.package by using the same logic as in serialization.py
Differential Revision: D67684033
| true |
2,761,361,576 | [Codemod][AddExplicitStrictExportArg] caffe2/test/inductor | gmagogsfm | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Differential Revision: D67682313
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,761,351,564 | Fix an unnecessary CPU to GPU copy within flex_attention | VivekPanyam | closed | [
"module: nn",
"triaged",
"open source",
"Stale",
"module: flex attention"
] | 5 | CONTRIBUTOR | There are a few unnecessary CPU to GPU copies within flex_attention that cause unnecessary `cudaStreamSynchronize`s to occur. This decreases GPU utilization.
The existing code creates a `-inf` tensor on CPU and copies it to GPU (along with a synchronize).
The updated code no longer causes a cudaStreamSynchronize ... | true |
2,761,350,605 | Unnecessary CPU to GPU copies within flex_attention | VivekPanyam | closed | [
"triaged",
"oncall: pt2",
"module: pt2-dispatcher",
"module: flex attention"
] | 3 | CONTRIBUTOR | There are a few unnecessary CPU to GPU copies within flex_attention that cause unnecessary `cudaStreamSynchronize`s to occur. This decreases GPU utilization.
## Note
The below is based on a profiling run without `torch.compile`. I haven't looked at profiles of the compiled version in depth yet, but based on a qui... | true |
2,761,336,059 | [dynamo] Separate out GetItemSource and DictGetItemSource | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"keep-going"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143997
* __->__ #143926
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,761,279,040 | [export] Support module inputs for non strict mode. | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 15 | CONTRIBUTOR | Summary:
Add experimental support for torch.nn.Module as input types.
Before this change, we don't support module inputs but recently we saw some interesting use cases like gpt-fast https://github.com/pytorch-labs/gpt-fast/blob/main/generate.py#L68 where we directly pass in a module input for different variants of the... | true |
2,761,235,921 | [dynamo] Make ConstDictKeySource a subclass of ChainedSource | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #143926
* __->__ #143924
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
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