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 |
|---|---|---|---|---|---|---|---|---|
2,785,869,806 | Handle meta tensors in FX quantization | kausv | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: quantization",
"release notes: AO frontend"
] | 11 | CONTRIBUTOR | Summary:
D66895899 got reverted in D67565250 because of pytorch OSS linter failure.
Adding back with the format the linter suggested
https://github.com/pytorch/pytorch/actions/runs/12443655335/job/34743090791
Test Plan: buck run fbcode//mode/dev-nosan fbcode//torchrec/fb/quant/tests:test_embedding_modules
Reviewed By... | true |
2,785,808,532 | update IS_JETSON check | Fuzzkatt | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | COLLABORATOR | update IS_JETSON check to include the latest SM
cc @eqy @tinglvv @nWEIdia | true |
2,785,783,528 | ck: add explicit addmm test | coconutruben | closed | [
"fb-exported",
"Stale",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Summary:
# Why
keep https://github.com/pytorch/pytorch/pull/144519 from regressing
# What
run addmm through CK only with a shape that previously caused a segfault
Test Plan:
```
buck2 test mode/dev-nosan-amd-gpu fbcode//caffe2/test/inductor:test_ck_backend -- --exact 'caffe2/test/inductor:test_ck_backend - test_add... | true |
2,785,770,901 | Drop unused num_elements variable | c-p-i-o | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 4 | CONTRIBUTOR | Summary:
With the recent enforcement of unused variable as an error in D67329035, certain tests like
https://www.internalfb.com/intern/test/562950135258426?ref_report_id=0
can't build citing:
```
Action failed: fbcode//caffe2:libtorch_cuda (cfg:linux-x86_64-fbcode-platform010-clang17-no-san#2a7259832b2f5c67) (cxx_compi... | true |
2,785,760,479 | [Intel GPU] Support SparseCsrXPU codegen | cfgfung | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu"
] | 24 | CONTRIBUTOR | Adding a new dispatch key - `SparseCsrXPU` to enable Intel GPU support for SparseCsr Tensor.
Similar PR: https://github.com/pytorch/pytorch/pull/139267 | true |
2,785,748,597 | Add tests for different dtypes with max autotune | exclamaforte | open | [
"Merged",
"Reverted",
"Stale",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 15 | CONTRIBUTOR | cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov @BoyuanFeng | true |
2,785,717,403 | fixup top | soulitzer | closed | [] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144720
* #141842
* #141841
* #144719
| true |
2,785,717,315 | Support FunctionalTensor subclass in is_fake and maybe_get_fake_mode | soulitzer | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #141842
* #141841
* __->__ #144719
| true |
2,785,709,316 | [xpu] Compilation of pytorch failed, unable to generate RegisterSparseXPU.cpp | jgtong | closed | [
"triaged",
"module: xpu"
] | 3 | NONE | ### 🐛 Describe the bug
Description: pytorch installation cannot generate the file `RegisterSparseXPU.cpp`
Back trace of the error:
```
[4/617] Generating ../../../xpu/ATen/XPUFunctions.h, ../../../xpu/ATen/RegisterXPU.cpp, ../../../xpu/ATe...xtend/c_shim_xpu.h, /home/jaytong/pytorch/torch/csrc/inductor/aoti_torch/g... | true |
2,785,704,570 | assert size/strides for fallback kernel | shunting314 | closed | [
"high priority",
"good first issue",
"triaged",
"oncall: pt2",
"module: inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Inductor right now does not generate size/stride asserts for fallback kernel. This makes issue like [this](https://fb.workplace.com/groups/1075192433118967/posts/1567334737238065) very hard to debug (this is a meta internal link).
Actually in ir.FallbackKernel, we have the following code whose... | true |
2,785,677,267 | [BE] [CD] Remove pygit2 dep for aarch64_wheel build | malfet | closed | [
"Merged",
"release notes: releng",
"topic: improvements",
"ciflow/binaries_wheel"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144698
* __->__ #144716
As it's incompatible with 3.13t and only used to fetch the branch name, which could be done by running
```
git rev-parse --abbrev-ref HEAD
```
Also, remove yet another reference to long gone `master` branch... | true |
2,785,624,580 | [mps/inductor] Add support for `ceil` | dcci | closed | [
"Merged",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 4 | MEMBER | inductor/test_index_dynamic_shapes passes after this change.
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @ch... | true |
2,785,611,635 | [cutlass backend] cexpr the arg before writing to cpp file | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 15 | CONTRIBUTOR | Summary: The problem is for certain shapes, see unit test, one of the dimensions is like `s0 // 2`. If we use cutlass backend, this means writing that to C++ file, which would lead to C++ compilation error.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-... | true |
2,785,608,446 | [dynamo] Delete DictKeysVariable - already have DictKeySetVariable | anijain2305 | closed | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144485
* __->__ #144713
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,785,586,534 | [dynamo] skip frame recursively when no graph is traced | williamwen42 | closed | [
"Stale",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144712
Fixes https://github.com/pytorch/pytorch/issues/144360. cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames @ydwu4
... | true |
2,785,573,645 | Tensor Stride Inconsistent (?) Behavior When One of the Dimension is 1 | HanGuo97 | open | [
"triaged",
"module: memory format"
] | 0 | CONTRIBUTOR | Hi,
I noticed that when a Tensor has `1` in one of its dimensions, its `stride` exhibit inconsistent (?) behavior under transformations + `.contiguous()` compared to a new tensor initialized with the final shape.
Granted, since the dimension in question is `1`, we are never supposed to use index other than `0`. That ... | true |
2,785,566,841 | Allow ROCm runner to upload benchmark results if found | huydhn | closed | [
"module: rocm",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"test-config/default",
"ciflow/rocm"
] | 3 | CONTRIBUTOR | https://github.com/pytorch/pytorch/wiki/How-to-integrate-with-PyTorch-OSS-benchmark-database. This will unblock AMD when they try to run benchmark MI300 benchmarks on CI.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,785,548,881 | [aoti] Deduplicate "V.aot_compilation" and "V.graph.aot_mode" flags. [1/n] | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Summary:
According to angelayi, these two flags indicated different things when we have two-pass codegen but since now we basically keep the two flags all the same, we should merge two flags.
This can prevent some bug (e.g. we change value of aot_mode which will not cover branches like if V.aot_compialtion is True) fr... | true |
2,785,533,964 | [PT][PG] fix build error `nused variable 'num_elements'` | tianfengfrank | closed | [
"oncall: distributed",
"fb-exported",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 9 | NONE | Summary: fix the build error revealed in D68075676. Build error exposed by added new `-Werror ` flag https://github.com/pytorch/pytorch/pull/136965
Test Plan: CI
Differential Revision: D68120898
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,785,463,492 | functional compiled autograd | zou3519 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"skip-pr-sanity-checks",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 13 | CONTRIBUTOR | This PR squashes together the following commits:
https://github.com/pytorch/pytorch/pull/144115
https://github.com/pytorch/pytorch/pull/143417
https://github.com/pytorch/pytorch/pull/143405
https://github.com/pytorch/pytorch/pull/143387
https://github.com/pytorch/pytorch/pull/143304
https://github.com/pytorch/p... | true |
2,785,456,089 | Revert "Upload METADATA file with whl binaries (#143677)" | clee2000 | closed | [
"Merged",
"ciflow/binaries",
"topic: not user facing"
] | 3 | CONTRIBUTOR | This reverts commit 3eb3f4ed5580010a7961d996ccc6ee19c7ccbb5e.
Also reverts https://github.com/pytorch/pytorch/pull/144164
Manual revert because the above causes merge conflicts
Reverting in favor of https://github.com/pytorch/test-infra/pull/6159 | true |
2,785,310,766 | int_mm seems broken due to Triton upgrade | cpuhrsch | closed | [
"high priority",
"triaged",
"oncall: pt2",
"module: inductor",
"upstream triton"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
from torch._higher_order_ops.out_dtype import out_dtype
def quantized_matmul(x_vals_int8, x_scales, w_vals_int8):
return out_dtype(torch.ops.aten.mm.default, torch.int32, x_vals_int8, w_vals_int8) * x_scales
x_vals_int8 = torch.randn(65536, 144).to(dtype=torch.int... | true |
2,785,233,817 | Leave SCCACHE_S3_KEY_PREFIX empty to share the cache among all build jobs | huydhn | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | This is a follow-up of https://github.com/pytorch/pytorch/pull/144112#pullrequestreview-2528451214. After leaving https://github.com/pytorch/pytorch/pull/144112 running for more than a week, all build jobs were fine, but I failed to see any improvement in build time.
So, let's try @malfet suggestion by removing the... | true |
2,785,105,673 | [XPU] Fix AOTI Runner Syntax Error | ratnampa | closed | [
"open source",
"topic: not user facing",
"module: xpu"
] | 6 | CONTRIBUTOR | Syntax error in xpu aoti runner from commit: https://github.com/pytorch/pytorch/pull/142213/ leads to XPU build failure.
cc @gujinghui @EikanWang @fengyuan14 @guangyey | true |
2,785,082,412 | [PP] Don't allow for num_microbatches > num_stages for single stage schedules | H-Huang | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (pipeline)"
] | 8 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144702
There is an edge case where `Schedule1F1B` will hang when num_microbatches=1 (https://github.com/pytorch/torchtitan/issues/775). For validation it makes sense to check that the number of stages should be >= number of microb... | true |
2,785,072,714 | [Pipelining] Update all schedules to use _PipelineScheduleRuntime | H-Huang | open | [
"triaged",
"better-engineering",
"module: pipelining"
] | 0 | MEMBER | We have a new runtime for pipeline schedules that the existing schedules should be transitioned to.
Things we need to do:
- Update the `_step_microbatches` for each Schedule class to call into the `_PipelineScheduleRuntime._step_microbatches()`
- Update the `Schedule1F1B` and `ScheduleGpipe` to generate the pipeline_... | true |
2,785,016,599 | inductor_config_logging: Don't drop keys | c00w | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 15 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144700
This bit me while I was trying to debug some trace issues.
In general this config is already quite large when dumping, so adding
more fields doesn't make it significantly worse.
Also a number of the items we are type checking... | true |
2,785,011,820 | inductor `full_like` decompositions give incorrect strides | bdhirsh | open | [
"high priority",
"triaged",
"actionable",
"module: correctness (silent)",
"oncall: pt2",
"module: inductor",
"ubn"
] | 14 | CONTRIBUTOR | min repro:
```
import torch
def f(x):
return torch.full_like(x, 3)
x = torch.randn(4, 5, 6).transpose(1, -1)
out = f(x)
out_compiled = torch.compile(f, backend="aot_eager_decomp_partition")(x)
print(out.stride())
print(out_compiled.stride())
# prints
# (30, 1, 6)
# (30, 5, 1)
```
This seems like the root cause o... | true |
2,784,983,615 | [CD] Enable python3.13t builds for aarch64 | malfet | closed | [
"Merged",
"release notes: releng",
"topic: improvements",
"ciflow/binaries_wheel",
"no-runner-experiments"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144698
* #144716
But make sure that right numpy version is picked (2.0.2 does not support 3.13)
| true |
2,784,975,450 | [EZ] [CD] Add 3.13 to FULL_PYTHON_VERSIONS | malfet | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144698
* __->__ #144697
* #144696
Separation was necessary for Conda codegen, but now it's gone | true |
2,784,974,975 | [EZ] [CD] Eliminate stale TODO | malfet | closed | [
"Merged",
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144698
* #144697
* __->__ #144696
As 3.13 has been enabled across the board, which one can verify by running `./github/regenerate.sh` and observe that non of the configs have changed
| true |
2,784,957,840 | Output of nonzero is transposed, fix fake tensor | ezyang | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: bug fixes",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"ci-no-td"
] | 18 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144695
Needs this companion executorch PR: https://github.com/pytorch/executorch/pull/7657
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe ... | true |
2,784,942,012 | Fix inductor periodic smoke test wrong artifact | huydhn | closed | [
"Merged",
"topic: not user facing",
"test-config/default",
"ciflow/inductor-periodic",
"test-config/inductor_torchbench_smoketest_perf"
] | 5 | CONTRIBUTOR | I'm not entirely sure why this failure starts to show up in periodic since Friday https://github.com/pytorch/pytorch/actions/runs/12716967189/job/35463656803. The artifact was uploaded to S3, but `use-gha: anything-non-empty-to-use-gh` was set and it was working. Maybe this is related to https://github.com/pytorch/py... | true |
2,784,926,778 | [PagedAttention] Support different input position for each batch index | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"module: flex attention"
] | 6 | CONTRIBUTOR | In LLM inference, each request usually has different prefill length, leading to different input position for each batch index. This PR adds such support for paged attention.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78... | true |
2,784,895,369 | ROCm: Skip tests in elastic/utils/distributed_test | jagadish-amd | closed | [
"oncall: distributed",
"module: rocm",
"open source",
"Merged",
"topic: not user facing",
"ciflow/periodic"
] | 7 | CONTRIBUTOR | The tests are failing on ROCm machines due to the below error. The client socket has timed out after 1000ms while trying to connect to (gpu4f67.jax.cs.cpe.ice.amd.com, 0)
Disabling the tests.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @jeffdaily @sunway513 @jithunnair-am... | true |
2,784,863,760 | torch.cond + torch.non_zero does not work with torch.export.export | xadupre | closed | [
"oncall: pt2",
"oncall: export"
] | 14 | COLLABORATOR | ### 🐛 Describe the bug
I can't export the following model after rewriting the code with torch.cond. I tried with different configurations all listed below. None worked.
```python
import torch
class Model(torch.nn.Module):
def forward(
self,
input_ids,
image_features,
vocab_size,... | true |
2,784,701,156 | Support new CUDA conda package layout natively in cpp_extension.CUDAExtension | vyasr | open | [
"module: cpp-extensions",
"module: cuda",
"triaged",
"enhancement"
] | 5 | NONE | ### 🚀 The feature, motivation and pitch
[`torch.utils.cpp_extension.CUDAExtension`](https://pytorch.org/docs/stable/cpp_extension.html#torch.utils.cpp_extension.CUDAExtension) is designed to simplify compiling extension modules that require CUDA. To facilitate CUDA usage, it adds library/include/etc paths and passes ... | true |
2,784,695,373 | DISABLED test_tcp (__main__.WorkerServerTest) | jeffdaily | open | [
"oncall: distributed",
"module: rocm",
"triaged",
"skipped"
] | 1 | COLLABORATOR | Platforms: rocm
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22distributed%2Felastic%2Ftest_control_plane.py%3A%3AWorkerServerTest%3A%3Atest_tcp%22%5D)).
There is some setup issue with the ROCm CI self-hosted runners that blocks this p... | true |
2,784,672,782 | topK for sparse Vectors | arthur-75 | open | [
"module: sparse",
"triaged"
] | 1 | NONE | ### 🚀 The feature, motivation and pitch
Hello, Thanks for this great package. is it possible to have topk with sparse vectors ?
Thanks
### Alternatives
_No response_
### Additional context
_No response_
cc @alexsamardzic @nikitaved @pearu @cpuhrsch @amjames @bhosmer @jcaip | true |
2,784,639,505 | Loading sparse tensors in a `DataLoader` raises CUDA initialization error since `2.5.0` | douglas-boubert | closed | [
"module: sparse",
"module: dataloader",
"module: cuda",
"triaged",
"module: regression"
] | 16 | NONE | ### 🐛 Describe the bug
```python
import torch
from torch.utils.data import Dataset, DataLoader
def create_sparse_tensor():
tensor = torch.randn(5, 5)
sparse_tensor = tensor.to_sparse().to("cpu")
torch.save(sparse_tensor, "sparse_tensor.pth")
class OperatorDataset(Dataset):
def __init__(self):
... | true |
2,784,601,231 | [export] Load side info about pos/kw argument kind for serialization. | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 8 | CONTRIBUTOR | Summary:
Fixing issue of nodes like
```
torch.ops.aten.linear.default(x, w, b)
```
being deserialized as
```
torch.ops.aten.linear.default(x, w, bias=b)
```
which breaks roundtripping.
Test Plan:
buck test mode/opt caffe2/test:test_export -- -r TestDeserialize
buck test mode/opt caffe2/test:test_export -- -r TestSeria... | true |
2,784,571,322 | [RelEng] Add `--ami` option to build_aarch64 | malfet | closed | [
"Merged",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Which should be mutually-exclusive with OS
For example, one can use the following to alloc one-off instance
```
./build_aarch64_wheel.py --alloc-instance --instance-type g5.4xlarge --key-name nshulga-key --ami ami-0f51103893c02957c --ebs-size 200
```
TODO:
- Figure out EBS volume name depending on the AMI (... | true |
2,784,544,778 | [export] Fix torchbind constant folding | yiming0416 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: export"
] | 6 | CONTRIBUTOR | Summary: `CallTorchBind` should not be folded during constant folding
Test Plan:
```
buck2 run mode/dev-nosan sigmoid/inference/test:test_passes -- -r test_const_folding_torchbind
```
Reviewed By: henryoier
Differential Revision: D67721272
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSup... | true |
2,784,500,397 | torch.export treats two of the same parameters as the same node | jackzhxng | open | [
"oncall: pt2",
"oncall: export"
] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
`torch.export` where the same tensor is used for multiple args in the example inputs, e.g. (self.x, self.x) results in a confusing graph where the two parameters seem to be treated as the same node. As a basic example, when I would pass in something like ep.module()(torch.zeros... | true |
2,784,393,208 | [BE]: Improve typing inference with TypeIs | Skylion007 | closed | [
"oncall: distributed",
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 4 | COLLABORATOR | cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @LucasLLC @MeetVadakkanchery @mhorowitz @pradeepfn @ekr0 | true |
2,784,131,177 | Add heuristic to fail block pointer match early | kundaMwiza | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor"
] | 8 | CONTRIBUTOR | This PR adds a heuristic to potentially fail the block pointer match early. Expressions like below take a long time to match using sympy (e.g. > 100 seconds)
```python
# torch._inductor.config.triton.use_block_ptr = True
# torch._inductor.config.triton.prefer_nd_tiling = True
# Expression from pytest -k test_max_po... | true |
2,783,989,203 | [BE][Easy] improve submodule discovery for `torch.ao` type annotations | XuehaiPan | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"release notes: AO frontend"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144680
| true |
2,783,926,028 | Improve softmax's perf in cuda | ywq880611 | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda"
] | 8 | CONTRIBUTOR | Fixes #144645
| true |
2,783,810,200 | torch.distributed. pipelining source code page is not accessible. | kyoungbinkim | closed | [
"module: docs",
"triaged"
] | 2 | NONE | ### 📚 The doc issue
https://github.com/pytorch/pytorch/blob/main/docs/source/distributed.pipelining.rst?plain=1#L424C1-L491C21
https://pytorch.org/docs/stable/distributed.pipelining.html#torch.distributed.pipelining.pipeline
When accessing the source code page, a 404 error appears.
thanks
<img width="1458" alt=... | true |
2,783,582,709 | Tensorboard SummaryWriter.add_hparams doesn't log hparam metrics dictionary | eren-ture | open | [
"triaged",
"module: tensorboard"
] | 1 | NONE | ### 🐛 Describe the bug
When trying to add_params, I cannot get the tensorboard to display the metrics.
```python
from torch.utils.tensorboard import SummaryWriter
import numpy as np
with SummaryWriter(r'.\runs\test_01') as writer:
for i in range(4, 7):
for j in range(3, 6):
batch_size, lr = ... | true |
2,783,576,231 | Allow KGEModel.test to collect hits@k for several values of k at once | ACHinrichs | closed | [] | 1 | NONE | ### 🚀 The feature, motivation and pitch
Currently, `KGEModel.test` takes an optional integer-parameter `k` to calculate hits@k. I would like to collect hits for different `k`s, e.g. I would like to collect hits@1, hits@10 and hits@100 without having to re-run the model.
In the solution I envision `KGEModel.test` w... | true |
2,783,401,918 | Apply clang-format for ATen/core/boxing cpp files | zeshengzong | closed | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Code change via add path config in .lintrunner.toml file and running
```bash
lintrunner -a --take CLANGFORMAT --all-files
``` | true |
2,783,322,243 | [inductor][cpu] fused attention Inductor tests fails with an error " name 'getitem' is not defined " | kareemshaik80 | closed | [
"oncall: pt2",
"oncall: cpu inductor"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
I have regrenrated all the patterens with the flag PYTORCH_GEN_PATTERNS=1 by setting config flag "fallback_random" is set to true. By default this falg is false.
After setting this flag to True. I ran existing fused attention tests but the test failed with the following error.
**CMD to r... | true |
2,783,291,020 | Thread-safe approach on temporarily changing the `set_default_type` | baluyotraf | open | [
"triaged",
"enhancement",
"module: python frontend"
] | 5 | NONE | ### 🚀 The feature, motivation and pitch
There are cases in our code in which we rely on torch to infer the type of the data. There are code sections in which we would like to use higher precision for floating points and it would be nice to only set the default types in these code blocks.
### Alternatives
We are cur... | true |
2,783,246,761 | [FlexAttention] Allow to pass mod_type info to `create_mask` via arg or keyword. | oraluben | closed | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 5 | CONTRIBUTOR | `_get_mod_type` does not always work, e.g. `def some_score(score, *args)` in https://github.com/pytorch-labs/attention-gym/pull/103/commits/29f43391be8c952e86307c6cb1682022abf7de00. This PR allows user to specific the type (mask/score) via `create_mask(mod_fn, mod_type=_ModificationType.SCORE, ...)` or `create_mask(sco... | true |
2,783,246,531 | torch.stack for sequences | yueyinqiu | open | [
"module: typing",
"triaged",
"enhancement",
"module: python frontend"
] | 6 | NONE | ### 🚀 The feature, motivation and pitch
I'm trying to let my tensors to have a static dimension count for type checking, like:
```python
import torch
import typing
Tensor2d = typing.NewType("Tensor2d", torch.Tensor)
def matmul(x: Tensor2d, y: Tensor2d) -> Tensor2d:
return Tensor2d(x.matmul(y))
# So t... | true |
2,783,237,681 | Update slow tests | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/slow",
"ci-no-td"
] | 3 | COLLABORATOR | This PR is auto-generated weekly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/weekly.yml).
Update the list of slow tests. | true |
2,783,226,964 | Fix Throughputbenchmark issue | shiyang-weng | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: dynamo"
] | 5 | CONTRIBUTOR | Fixes [144461](https://github.com/pytorch/pytorch/issues/144461)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,783,187,401 | [Update torch-xpu-ops] Update torch-xpu-ops to resolve XPU build error introduced by #144364 | etaf | closed | [
"open source",
"topic: not user facing",
"ciflow/xpu"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144668
* #144667
As title. | true |
2,783,159,480 | [XPU build] Fix XPU build error caused by wrong code change introduced by #142213 | etaf | closed | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 6 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144668
* __->__ #144667
The PR #142213 changed the function parameter name from `inputs` to `input_handles` but still use `inputs` in function, and caused XPU build failure. Since XPU CI did not gate the PR, we need to fix it here to unblo... | true |
2,783,135,743 | [mps/inductor] Add support for truncdiv(). | dcci | closed | [
"Merged",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | MEMBER | Two other inductor tests pass after this change.
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakh... | true |
2,783,106,932 | [MPSInductor] Fix maximum/minimum for int types | malfet | closed | [
"Merged",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | `metal::isnan` is only defined for floats, so provide a generic wrapper
that is false for integral types
TODO: Figure out why type propagantion is not working (or should it?)
Fixes #ISSUE_NUMBER
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @i... | true |
2,783,084,636 | Generalize poison fork logic for each device backend | guangyey | closed | [
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: improvements",
"topic: not user facing",
"ciflow/periodic",
"ciflow/mps",
"ciflow/rocm",
"ciflow/xpu",
"ci-no-td",
"module: accelerator"
] | 39 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144664
# Motivation
Generalize the posion_fork code to make it reusable across different devices.
cc @albanD @EikanWang | true |
2,783,078,906 | Support loading and executing a ExportedProgram from torch.export in C++ environment | supercharleszhu | open | [
"oncall: pt2",
"oncall: export"
] | 11 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Hi all, we are currently working on an online ML platform in the company which require us to
1. similar to torchscript, export a pytorch model graph and variable into an IR which can be executed in c++ environment
2. Update the model parameters when executing inference.
... | true |
2,782,916,424 | [MPSInductor] Add support for sizevars | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Just pass them as kernel arguments
After this change `pytest test/inductor/test_torchinduct.py -v -k _mps` reports 330 failed, 429 passed after and 335 failed, 424 passed before
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 ... | true |
2,782,872,702 | Fix torch.logsumexp dim description | zeshengzong | closed | [
"triaged",
"open source",
"Stale",
"release notes: python_frontend"
] | 3 | CONTRIBUTOR | Fixes #144339
Remove `dim` optional description in `torch.logsumexp` doc.
**Test Result**
**Before**
**After**
| true |
2,782,807,117 | Implement the `mode` property for transformed distributions | hukz18 | open | [
"module: distributions",
"triaged"
] | 0 | NONE | ### 🚀 The feature, motivation and pitch
Currently, the `TransformedDistribution` class of `torch.distributions.transformed_distribution` doesn't have a `mode` property. Calling `mode` on such an instance will raise a `NotImplementedError` that falls back to the `Distributions` base class.
Though I understand th... | true |
2,782,762,476 | Incorrect formula in docstring for torch.nn.modules.normalization.RMSNorm | enedil | closed | [] | 3 | NONE | ### 📚 The doc issue
Issue is at this line:
https://github.com/pytorch/pytorch/blob/9ae35b8bb13f3c35803355ce26fb9ee9954f1bdf/torch/nn/modules/normalization.py#L328
Assume for simplicity, that len(x.shape) == 1.
Formula is
```
y = x / sqrt(RMS[x] + epsilon) * gamma
```
RMS, as indicated from the linked ... | true |
2,782,740,342 | Update CONTRIBUTING.md | kaykenho | closed | [
"open source",
"topic: not user facing"
] | 3 | NONE | Update documentation for the contributing process
- Clarified the steps
- Minor fixes to grammar and formatting for clarity.
Fixes #ISSUE_NUMBER
| true |
2,782,732,952 | Async distributed checkpointing works incorrectly with tensors on CPU | dimdi-y | closed | [
"oncall: distributed",
"triaged",
"oncall: distributed checkpointing"
] | 5 | NONE | ### 🐛 Describe the bug
If an update to model CPU parameters happens before an async distributed checkpoint (via `torch.distributed.checkpoint.async_save`) is finished, the new value is written instead of the original one.
Moving the model to GPU or waiting on the returned future helps with the issue, but doing an ... | true |
2,782,728,512 | remove allow-untyped-defs from torch/ao/nn/quantized/reference/modules/linear.py | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"release notes: AO frontend"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144656
| true |
2,782,728,489 | remove allow-untyped-defs from torch/_C/_dynamo/eval_frame.pyi | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144655
| true |
2,782,728,470 | remove allow-untyped-defs from torch/nn/parameter.pyi | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144656
* #144655
* __->__ #144654
| true |
2,782,728,455 | remove allow-untyped-defs from torch/distributed/checkpoint/api.py | bobrenjc93 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144656
* #144655
* #144654
* __->__ #144653
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @LucasLLC @MeetVadakkanchery @mhorowitz @pradeepfn @ekr0 | true |
2,782,728,434 | remove allow-untyped-defs from torch/ao/nn/intrinsic/__init__.py | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"release notes: AO frontend"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144652
| true |
2,782,698,709 | [MPS] lu factor ex implementation | Isalia20 | closed | [
"triaged",
"open source",
"Merged",
"topic: improvements",
"release notes: mps",
"ciflow/mps"
] | 7 | COLLABORATOR | Implements `torch.linalg.lu_factor_ex` | true |
2,782,604,784 | [BE]: Update literal typing for torch/fx/graph nodelist | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx"
] | 3 | COLLABORATOR | Mentioned in discussion for #144631
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,782,592,023 | [MPSInductor] Better error when kernel fails to compile | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: improvements",
"release notes: mps",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144649
* #144648
* #144647
Now error message looks as follows:
```
% python ../test/inductor/test_torchinductor.py -v -k test_cat_unbacked_2d_mps
test_cat_unbacked_2d_mps (__main__.GPUTests) ... inline_call []
stats [('calls_c... | true |
2,782,585,380 | [MPS][BE] Surface syntax errors shader compilation | malfet | closed | [
"better-engineering",
"Merged",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144649
* __->__ #144648
* #144647
Before this change
```python
>>> import torch
>>> torch.mps._compile_shader('What')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/malfet/miniconda3/envs/py31... | true |
2,782,585,353 | [BE] Introduce `c10::SyntaxError` | malfet | closed | [
"better-engineering",
"Merged",
"release notes: python_frontend",
"topic: improvements"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #144649
* #144648
* __->__ #144647
Which will be translated into Python's SyntaxError | true |
2,782,545,207 | [Inductor] Unifiy Low Precision FP Legalization for to_dtype_bitcast & constant | DDEle | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 10 | CONTRIBUTOR | The upcast in `to_dtype_bitcast()` breaks following operations that only works with the target type (I uses `bitwise_and` in the updated UT).
This PR fixes this problem. Let's check the CI results to make sure it doesn't bring... | true |
2,782,541,376 | [RFC] Improve performance for softmax op for cuda in some specific size | ywq880611 | closed | [
"module: performance",
"module: cuda",
"triaged"
] | 4 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
In the triton [tutorial](https://triton-lang.org/main/getting-started/tutorials/02-fused-softmax.html) for softmax, we could compare the performance of pytorch op and triton, here is the result on my local (RTX3080):
### Compare between triton and torch
![softmax-perf](http... | true |
2,782,524,234 | remove Windows XPU build workaround. | xuhancn | closed | [
"module: windows",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel",
"intel",
"ciflow/xpu",
"module: xpu"
] | 34 | COLLABORATOR | From the RFC: https://github.com/pytorch/pytorch/issues/141946
Fixes https://github.com/pytorch/pytorch/issues/134989
After we land these fixing PRs:
1. https://github.com/pytorch/pytorch/pull/142245
2. https://github.com/pytorch/pytorch/pull/141943
We can remove the Windows XPU workaround.
cc @peterjc123 @... | true |
2,782,469,720 | nn.functional.interpolate doesn't work correctly with NCW tensors when output W exceeds 2^23 | alexlyulkov | open | [
"module: nn",
"triaged",
"module: edge cases"
] | 0 | NONE | ### 🐛 Describe the bug
nn.functional.interpolate returns strange results for NCW tensors when output W exceeds 2^23.
**Reproduction:**
```
import torch
n = (1 << 22) + 4
x = []
for i in range(n // 2):
x.append(0.0)
x.append(1.0)
x = torch.tensor(x, device="cuda:0", dtype=torch.float)
x = x.vie... | true |
2,782,424,962 | [Not4Land] test `optree` version compatibility | XuehaiPan | closed | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"not4land",
"ciflow/inductor"
] | 1 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,782,409,175 | FSDP OOM error | blurmemo | closed | [] | 1 | NONE | I use two 40G A100 GPUs and one 80G GPUs to fine-tune my model through lora and FSDP which ShardingStrategy is FULL SHARD. When I use command(CUDA_VISIBLE_DEVICES=5,3,4 torchrun --standalone --nnodes=1 --nproc-per-node=3 finetuning.py) to begin my work. I still get problems which are OOM on two 40G A100 GPUs. I watch ... | true |
2,782,406,282 | [FX] Refactor immutable collections implementation | XuehaiPan | closed | [
"open source",
"Merged",
"release notes: fx",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #147691
* __->__ #144640
* #147699
Get rid of dynamic class creation via `type(name, bases, ...)`. Convert it to classic static class definition for better readability and static analysis support.
cc @ezyang @SherlockNoMad @EikanWang @jg... | true |
2,782,317,400 | torch.vmap + autograd.Function + current_level bug | yanboliang | open | [
"module: autograd",
"triaged",
"module: vmap",
"module: functorch"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
It we call ```torch._C._functorch.current_level()``` inside of an autograd function's ```setup_context``` method, and then apply ```torch.vmap``` on top of it, it errors out.
Repro:
* Checkout and apply https://github.com/pytorch/pytorch/pull/143811
* Replace ```key = id(Generated)``` with `... | true |
2,782,298,517 | [MPSInductor] Implement bitcasts | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | That will be used to compile something like `torch.rand(32, device='mps').view(dtype=torch.int32)`
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhund... | true |
2,782,277,604 | CheckpointError with `torch.distributed.algorithms._checkpoint.checkpoint_wrapper` and `torch.compile` | eliphatfs | open | [
"module: activation checkpointing",
"triaged",
"oncall: pt2",
"module: inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import functools
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributed.algorithms._checkpoint.checkpoint_wrapper import apply_activation_checkpointing, checkpoint_wrapper, CheckpointImpl
@torch.compile(mode='reduce-overhead')
class SelfAt... | true |
2,782,277,352 | Error loading "pytorch\torch\lib\shm.dll" or one of its dependencies when building from source (Windows 11) | Panchovix | closed | [] | 0 | NONE | ### 🐛 Describe the bug
I have built torch from source, on https://github.com/pytorch/pytorch/commit/63569d9745b0530f8d66721e2a462c9f042e6b16 commit, using:
Magma for CUDA 12.6 (2.5.4)
MKL 2025.0 and 2020.2
cudNN 9.6
cuSPARSELt 0.6
cuDSS 0.4
On VS 2022 with MSVC v143
Using
```
cmake .. -GNinja ^
... | true |
2,782,232,134 | [MPSInductor] Implement `check_bounds` | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Although at the moment it returns rather than rasises assert due to https://github.com/pytorch/pytorch/pull/144632
`pytest test/inductor/test_torchinductor.py -v -k _mps` score is `368
failed, 391 passed, 32 skipped`
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng ... | true |
2,782,226,572 | [MPS] `torch.mps.synchronize` hangs on error | malfet | open | [
"triaged",
"module: deadlock",
"module: mps"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Consider following code
```python
import torch
lib=torch.mps._compile_shader("kernel void foo(device float* x) {__builtin_trap();}")
lib.foo(torch.rand(3, device="mps"))
torch.mps.synchronize()
```
It will hang the process, and few attempt to reproduce the same resulted in system hang
... | true |
2,782,217,891 | 144x less efficient CPU usage when training NN past a certain width | dustinboswell | open | [
"module: performance",
"triaged",
"module: arm"
] | 2 | NONE | ### 🐛 Describe the bug
The code below is a minimal NN training loop with a fully connected NN of shape (10->width->width->10).
When width is 45, everything is fine, the code takes about 1 second, and only uses 1 CPU.
When width is 46, the code takes 9 seconds, and uses all 16 cpus.
So it's 144x less efficient (w... | true |
2,782,208,242 | [MPSInductor] Properly generate index expressions | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Now test_slice_scatter4_mps passes
Before this change test_torchinductor.py reported 422 failed and 337 passed, after this change 412 failed 347 passed.
Fixes https://github.com/pytorch/pytorch/issues/144630
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenz... | true |
2,782,173,571 | Micro-optimization in Graph.nodes.__iter__ | jansel | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144631
This generates slightly better code (removing a generator frame) and
drops a redundant assert.
```py
>>> import timeit
>>> def a():
... yield from range(3)
...
>>> def b():
... return range(3)
...
>>> time... | true |
2,782,090,892 | [mps/inductor] Adjust lowering to not emit comments | dcci | closed | [
"module: mps",
"oncall: pt2"
] | 7 | MEMBER | ### 🐛 Describe the bug
**Edit**
The problem weren't VLAs, rather, the fact that `//` is a comment in metal and an operation in python.
** Original report **
There are currently a fair amount of inductor tests that are failing because the lowering emits VLAs, which aren't supported by the Metal shading language (acco... | true |
2,782,086,391 | [mps/inductor] Add support for trunc(). | dcci | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 6 | MEMBER | inductor/test_div1 passes after this change.
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundo... | true |
2,782,074,987 | Patch Weibull.mode | j-wilson | closed | [
"module: distributions",
"triaged",
"open source",
"Stale"
] | 4 | CONTRIBUTOR | This PR fixes the Weibull distribution's `mode` property, which is currently incorrect for `concentration < 1`.
Before:
```
dist = Weibull(scale=torch.ones(4), concentration=torch.tensor([0.5, 0.75, 1.0, 1.25]))
dist.mode
> tensor([1.0000, nan, 0.0000, 0.2759])
```
After:
```
dist = Weibull(scale=torch.... | true |
2,782,054,624 | remove allow-untyped-defs from torch/distributed/_checkpointable.py | bobrenjc93 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #144627
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
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