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 |
|---|---|---|---|---|---|---|---|---|
2,932,626,915 | Lintunner running on newly added files despite being explicitly excluded in .lintrunner.toml | TovlyFB | closed | [
"module: ci",
"module: lint",
"triaged",
"module: devx"
] | 1 | CONTRIBUTOR | In my [PR 148936](https://github.com/pytorch/pytorch/pull/148936), lintrunner is [failing with CLANGTIDY](https://github.com/pytorch/pytorch/actions/runs/13927137669/job/38974556917?pr=148936) despite me adding the newly added files to the `exclude_patterns` of the CLANGTIDY rule in `.lintrunner.toml`. Per @malfet, the... | true |
2,932,603,851 | [inductor] Add a helper for convert index_dtype to torch dtype | isuruf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149531
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,932,595,881 | [CI][docker] Remove vulkan and swiftshader from docker builds | clee2000 | closed | [
"Merged",
"module: vulkan",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Probably should have been removed with https://github.com/pytorch/pytorch/pull/139354/files?
Should I also remove mentions of them from build.sh and test.sh? | true |
2,932,553,924 | Fakify torchbind objects in compile_fx and add tests for SigridTransformsInstanceTorchBind | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Summary:
We need to properly fakify torchbind objects, including the ones in graph module attributes, so the resgitered fake implementation works properly.
- _fakify_script_objects in `compile_fx`
- Allow fake torchbind objects in `torchbind_constants`
Remove `node.meta["unbacked_bindings"]` for `aot_compile` in `co... | true |
2,932,458,473 | Fix dynamic shapes repordering bug | tugsbayasgalan | closed | [
"Merged",
"ciflow/trunk",
"release notes: export"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149528
WHen we create constraints, we look at the ordering of kwargs according to model signature. But when we trace, we use the ordering that is created based on how user passes in their kwargs. As a result, constraints and dynam... | true |
2,932,455,816 | GHA request labels should represent independent fleet of runners | jeanschmidt | open | [
"module: ci",
"triaged",
"enhancement",
"needs design"
] | 3 | CONTRIBUTOR | Currently we identified that a few runners are provided by multiple vendors/organizations and use the same label.
* linux.s390x
* linux.idc.xpu
* linux.rocm.gpu.2
* macos-m2-15 (and mac label standards)
We need to identify the labels that are reused across fleets and define a new standard that better reflect where th... | true |
2,932,444,267 | Add release branch push triggers to rocm-mi300.yml | pytorchbot | closed | [
"module: rocm",
"open source",
"topic: not user facing",
"ciflow/rocm",
"ciflow/rocm-mi300"
] | 1 | COLLABORATOR | When we added the rocm-mi300.yml earlier this year, we had lower capacity and we were just pipecleaning the workflow, so we set the trigger to only respond to pushes to main branch. But now we have more stability as well as capacity, and we would really like to ensure that the release branch is being tested on MI300s a... | true |
2,932,374,513 | Pin auditwheel to 6.2.0 | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | Observing aarch64 failure in nightly:
https://github.com/pytorch/pytorch/actions/runs/13917778961/job/38943911228
Similar to: https://github.com/pytorch/vision/pull/8982
```
2025-03-18T08:44:58.4128744Z Repairing Wheel with AuditWheel
2025-03-18T08:44:58.5440988Z INFO:auditwheel.main_repair:Repairing torch-2.8... | true |
2,932,293,420 | [codemod] Fix clang-tidy command line doc comments | scramsby | closed | [
"oncall: jit",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Summary:
Fixes the comments to match the latest updates to the checked-in tools.
Search/replace applied in this order:
* `# /fbsource/tools/lint/clangtidy/clang-tidy-platform010 -list-checks` -> `# ~/fbsource/tools/lint/clangtidy/clang-tidy-platform010-clang-17 -list-checks`
* `# ~/fbsource/tools/lint/clangtidy/clang-... | true |
2,932,279,253 | DISABLED test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_float64 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 5 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_float64&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorc... | true |
2,932,279,096 | DISABLED test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_float16 (__main__.TestForeachCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"module: mta"
] | 5 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_binary_op_with_scalar_self_support__foreach_pow_is_fastpath_True_cuda_float16&suite=TestForeachCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorc... | true |
2,932,278,773 | DISABLED test_lazy_module4 (__main__.NNModuleTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 2 | NONE | Platforms: linux, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_lazy_module4&suite=NNModuleTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/39028613778).
Over the past 3 hours, it has been de... | true |
2,932,278,665 | DISABLED test_lazy_module2 (__main__.NNModuleTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: linux, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_lazy_module2&suite=NNModuleTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/39036676376).
Over the past 3 hours, it has been de... | true |
2,932,278,467 | DISABLED test_lazy_module3_cuda (__main__.NNModuleTestsDeviceCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: linux, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_lazy_module3_cuda&suite=NNModuleTestsDeviceCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/39036676376).
Over the past 3 hours,... | true |
2,932,201,749 | Try to enforce signature ordering | tugsbayasgalan | open | [
"ciflow/inductor",
"release notes: export"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149518
| true |
2,932,112,603 | Add release branch push triggers to rocm-mi300.yml | jithunnair-amd | closed | [
"module: rocm",
"open source",
"Merged",
"topic: not user facing",
"ciflow/rocm"
] | 8 | COLLABORATOR | When we added the rocm-mi300.yml earlier this year, we had lower capacity and we were just pipecleaning the workflow, so we set the trigger to only respond to pushes to main branch. But now we have more stability as well as capacity, and we would really like to ensure that the release branch is being tested on MI300s a... | true |
2,932,103,964 | ```StateDictOptions``` in combination with ```cpu_offload=True``` and ```strict=False``` not working | psinger | open | [
"oncall: distributed",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
When running the following for distributed weight loading:
```
options = StateDictOptions(
full_state_dict=True,
broadcast_from_rank0=True,
strict=False,
cpu_offload=True,
)
set_model_state_dict(model=model, model_state_dict=weights, options=options)
```
I am getting `KeyErr... | true |
2,932,099,772 | [Inductor Cutlass backend] Fix imports and compilation of Cutlass SM100 Kernels | kadeng | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Summary: Fixes the import and compilation of Cutlass SM100 Kernels.
Test Plan: Cutlass backend unit tests, running benchmarks/inductor_backends/cutlass.py
Differential Revision: D71196747
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisun... | true |
2,932,088,373 | DTensor: more generically support CompositeImplicitAutograd ops under inference mode | bdhirsh | closed | [
"oncall: distributed",
"Merged",
"ciflow/inductor",
"release notes: distributed (dtensor)"
] | 3 | CONTRIBUTOR | Today, if you run DTensor (or any tensor subclass) under __torch_dispatch__, you will start seeing `CompositeImplicitAutograd` ops show up in the torch_dispatch.
"handling" these ops is trivial: you can just tell them to decompose into their constituent ops. Normally this decomposing happens in autograd, above DTens... | true |
2,932,052,552 | [ROCm] Enable more inductor UTs | jataylo | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"ciflow/rocm",
"ciflow/inductor-rocm",
"ciflow/inductor-periodic",
"ciflow/rocm-mi300"
] | 7 | COLLABORATOR | Primarily enable inductor fp8 tests, also enable other inductor tests
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @hongxiayang @naromero77amd @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @... | true |
2,932,034,355 | Added _fused_sdp_choice_stub dispatcher support for HPU device | pralay-das | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: sdpa"
] | 9 | CONTRIBUTOR | Currently for HPU device we don't have any support for _fused_sdp_choice_stub dispatcher function, so for `scaled_dot_product_attention` function by default selecting the `MATH Backend` using `_fused_sdp_choice_stub` for HPU device. With this PR we have enabled support for `_fused_sdp_choice_stub` dispatcher function, ... | true |
2,932,016,919 | [XPU] Update triton commit to fix to fix level_zero not found by env var LEVEL_ZERO_V1_SDK_PATH. | etaf | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"ciflow/xpu"
] | 5 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149511
| true |
2,932,015,883 | Fix with effect lowering for list return type | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Summary: - For `torch.ops.higher_order.with_effects`'s lowering, we should not extract the items out of an list (i.e. `*result` vs `result`). The `get_attr` nodes consider the result to be in the list format.
Test Plan:
```
buck run fbcode//mode/dev-nosan //caffe2/test/inductor:torchbind -- -r test_torchbind_aot_compi... | true |
2,931,738,760 | `torch.compile` has a graph break when one of the `out_dims` of `torch.vmap` is set to `None` | sses7757 | closed | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 2 | NONE | ### 🐛 Describe the bug
I want to `torch.compile` a vmapped function (`torch.vmap(..., in_dims=(None, 0), out_dims=(None, 0))`) with the default "inductor" backend and `fullgraph=True`; however, it failed due to a graph break caused by the `torch._C._functorch.is_batchedtensor` function, which was invoked by `torch.vm... | true |
2,931,635,300 | Adam optimizer ValueError: beta1 as a Tensor | Vetti420 | open | [
"needs reproduction",
"module: optimizer",
"triaged"
] | 9 | NONE | ### 🐛 Describe the bug
I got this error, if I set capturable=True
ValueError: beta1 as a Tensor is not supported for capturable=False and foreach=True
But worked for this,
config.optimizer =
{
"foreach": False,
"capturable": False
}
### Versions
v2.7.0
cc @vincentqb @jbsch... | true |
2,931,624,315 | Switch s390x tests to blocklist | AlekseiNikiforovIBM | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/s390"
] | 6 | COLLABORATOR | Switch s390x tests to blocklist | true |
2,931,596,711 | [ROCm] [Perf Testing] Remove num_warps restrictions on ROCm for perf | jataylo | open | [
"module: rocm",
"open source",
"module: inductor",
"ciflow/inductor",
"ciflow/rocm",
"ciflow/inductor-perf-test-nightly-rocm"
] | 2 | COLLABORATOR | Perf testing
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @hongxiayang @naromero77amd @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,931,573,933 | Parallelize sort | annop-w | closed | [
"module: cpu",
"open source",
"Merged",
"Reverted",
"topic: not user facing",
"ciflow/inductor",
"ci-no-td"
] | 16 | CONTRIBUTOR | PR #142391 erroneously used `USE_OMP` instead of `USE_OPENMP`.
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,931,489,127 | [Inductor] Adjust boundary checking of dimensions using YBLOCK | kundaMwiza | open | [
"triaged",
"open source",
"topic: not user facing",
"module: inductor"
] | 5 | CONTRIBUTOR | Apply the same logic introduced in https://github.com/pytorch/pytorch/pull/139751 to triton kernels using block ptrs. Here, if ynumel / YBLOCK > max_y_grids, dimensions dependent on YBLOCK need to be boundary checked, even if the block shape in such dimensions is a multiple of an expression in YBLOCK. This is because y... | true |
2,931,482,682 | fix ValueError issue | FlintWangacc | open | [
"triaged",
"open source",
"release notes: fx",
"fx"
] | 2 | NONE | fix following issue:
ValueError: code: co_varnames is too small
Fixes #149497
In `symbolic_trace`, It will crash with following stack.
```shell
Traceback (most recent call last):
File "/home/hmsjwzb/work/models/QWEN/./qwen5.py", line 55, in <module>
traced_model = torch.fx.symbolic_trace(model)
... | true |
2,931,401,399 | [dynamo] register_module_forward_pre_hook lead to compiled model produce wrong inference results | Cookiee235 | closed | [
"high priority",
"triaged",
"actionable",
"module: correctness (silent)",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025",
"ubn"
] | 5 | CONTRIBUTOR | ### 🐛 Describe the bug
Given the same inputs, the inference results for the compiled models were not equivalent to the original model before/after the execution of `register_module_forward_pre_hook(pre_hook)` ,
Such results are bizarre!
```python
import torch
model = torch.nn.Sequential(
torch.nn.Linear(10, ... | true |
2,931,304,833 | Inductor produce significantly different inference results with the originl original model | Cookiee235 | open | [
"oncall: pt2",
"oncall: cpu inductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class Model(torch.nn.Module):
def __init__(self):
super(Model, self).__init__()
self.linear = torch.nn.Linear(3, 3)
self.linear.weight = torch.nn.Parameter(torch.eye(3))
self.linear.bias = torch.nn.Parameter(torch.zeros(3))
def fo... | true |
2,931,250,561 | [RFC] : Dynamically Quantized 8-bit Matrix Multiplication support | nikhil-arm | open | [
"oncall: quantization",
"enhancement"
] | 6 | COLLABORATOR | # Dynamically Quantized 8-bit Matrix Multiplication support
## Background
PyTorch currently supports 4-bit dynamic quantized matrix multiplication via two operations:
- **`torch.ops.aten._dyn_quant_pack_4bit_weight`**
Packs the quantized weights, scales, and (optional) bias for a Linear layer into a single tensor... | true |
2,931,228,436 | Adapt test_misc.py for HPUs | amathewc | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 12 | CONTRIBUTOR | This PR is related to https://github.com/pytorch/pytorch/pull/145476 . That PR had two files (test_functions.py and test_misc.py) . test_functions was causing CI/rebase/merge issues and hence removed for now. This PR contains only test_misc.py.
This is a continuation of https://github.com/pytorch/pytorch/pull/144387... | true |
2,931,200,518 | Fix ValueError issue | FlintWangacc | closed | [
"module: cpu",
"open source",
"module: amp (automated mixed precision)",
"release notes: quantization",
"module: dynamo"
] | 4 | NONE | Fixes #149497
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @mcarilli @ptrblck @leslie-fang-intel @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,931,196,232 | symbolic_trace failed on deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | FlintWangacc | open | [
"module: fx",
"oncall: fx"
] | 1 | NONE | ### 🐛 Describe the bug
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from torch_mlir import fx
model_name = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
prompt = "What ... | true |
2,931,165,260 | possible output mismatch with torch.compile | vpandya-quic | closed | [
"high priority",
"triage review",
"module: embedding",
"oncall: pt2"
] | 3 | NONE | ### 🐛 Describe the bug
I have following test
```python
def test_large_random_embedding():
# Define a simple embedding model
class SimpleEmbeddingModel(torch.nn.Module):
def __init__(self, num_embeddings=10_000, embedding_dim=512):
super(SimpleEmbeddingModel, self).__init__()
s... | true |
2,931,118,257 | DISABLED AotInductorTest.FreeInactiveConstantBufferCuda (build.bin.test_aoti_inference) | pytorch-bot[bot] | open | [
"module: flaky-tests",
"skipped",
"oncall: pt2",
"export-triaged",
"oncall: export",
"module: aotinductor"
] | 95 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=AotInductorTest.FreeInactiveConstantBufferCuda&suite=build.bin.test_aoti_inference&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/3901216756... | true |
2,930,915,425 | Skip test if torchvision is not available | Flamefire | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | COLLABORATOR | The test unconditionally imports torchvision and fails if the isn't installed.
Skip it in this case.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,930,775,781 | DISABLED [WORKFLOW_NAME] / [PLATFORM_NAME] / [JOB_NAME] | Owner-DSH | closed | [
"module: ci"
] | 1 | NONE | > For example, DISABLED pull / win-vs2022-cpu-py3 / test (default). Once
> created, the job will be disabled within 15 minutes. You can check the
> list of disabled jobs at https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json
> If you need to get this out ASAP instead of waiting for 15 minutes,
> you can manually... | true |
2,930,775,739 | Android sys | Owner-DSH | closed | [
"module: ci"
] | 0 | NONE | > For example, DISABLED pull / win-vs2022-cpu-py3 / test (default). Once
> created, the job will be disabled within 15 minutes. You can check the
> list of disabled jobs at https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json
> If you need to get this out ASAP instead of waiting for 15 minutes,
> you can manually... | true |
2,930,739,741 | [Dynamo] Support the torch._C.DisableTorchFunction ctx manager | mlazos | closed | [
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149491
* #149490
* #149489
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,930,739,626 | [Dynamo] add support for torch._C._is_torch_function_all_disabled | mlazos | closed | [
"Merged",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149491
* __->__ #149490
* #149489
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,930,739,528 | [Dynamo] Refactor DisableTorchFunction ctx manager | mlazos | closed | [
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 5 | CONTRIBUTOR | Refactors the DisableTorchFunction ctx manager to properly model the eager code (no args to the context manager).
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149491
* #149490
* __->__ #149489
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe... | true |
2,930,706,167 | [distributed] fix: use group rank instead of global rank when possible | zhc7 | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 11 | CONTRIBUTOR | Fixes #149200
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,930,598,356 | add privateuse1 device type to pre forward hook of fsdp | garfield1997 | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (fsdp)"
] | 17 | CONTRIBUTOR | add privateuse1 device type to pre forward hook of fsdp
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,930,562,122 | Fix index error for reorder_and_filter in gemm template | CaoE | open | [
"open source",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | COLLABORATOR | Fixes #149475
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,930,553,604 | fix et trace collection of all_to_all | sanshang-nv | closed | [
"oncall: distributed",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 25 | CONTRIBUTOR |
fix ET trace collection to all_to_all.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,930,517,349 | [dynamo] Support tensor subclass with overriden tensor methods and properties | StrongerXi | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"ci-no-td"
] | 11 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149792
* __->__ #149484
* #149483
* #149482
This fixes most of the "torch.compile X tensor-subclass" issues
encountered in https://github.com/city96/ComfyUI-GGUF/issues/118. The
relevant tensor subclass definition is here:
https://github.co... | true |
2,930,517,238 | [dynamo] Support `torch.Tensor._make_subclass` and tracing through tensor subclass `__new__` | StrongerXi | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"ci-no-td"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149792
* #149484
* __->__ #149483
* #149482
This builds off the previous patch in the stack, and fully fixes
https://github.com/huggingface/diffusers/issues/10795.
Essentially, tensor subclass in the issue uses
`torch.Tensor._make_subclass... | true |
2,930,517,130 | [dynamo] Support Tensor subclass that has dynamic attributes or calls `Parameter.__torch_function__` | StrongerXi | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"ci-no-td"
] | 17 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149792
* #149484
* #149483
* __->__ #149482
This fixes most of https://github.com/huggingface/diffusers/issues/10795,
except for `torch.Tensor._make_subclass`, which will be fixed in a
subsequent patch.
The relevant tensor subclass from th... | true |
2,930,517,013 | [dynamo] fix calling torch function on newly constructed tensor subclass | StrongerXi | 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):
* #149792
* #149484
* #149483
* #149482
* #149791
* __->__ #149481
This patch updates existing `test_return_..._subclass` tests in
`test/dynamo/test_subclasses.py`, so that they end up invoking the
`__torch_function__` method of the newly cons... | true |
2,930,484,446 | load_inline no_implicit_headers mode | msaroufim | closed | [
"module: cpp-extensions",
"Merged",
"ciflow/trunk",
"release notes: cpp"
] | 19 | MEMBER | In the kernelBot leaderboard we support people competing with custom cuda extensions via `load_inline()`, however even on toy kernels this can result in cold starts of up to 90s - this problem is primarily responsible for us having to double our timeout values
I performed an investigation here https://github.com/msa... | true |
2,930,365,618 | Remove Ubuntu 18.04 scripts | cyyever | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"release notes: releng"
] | 6 | COLLABORATOR | Ubuntu 18.04 end of life reached on May 31, 2023. These code isn't used now.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,930,325,306 | [Distributed] Add `repr` methods for `ParallelStyle`s | shink | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (dtensor)"
] | 9 | CONTRIBUTOR | Fixes #149470
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,930,273,966 | changing linear layer initialization formula in docs | karanjakhar | closed | [
"open source"
] | 4 | NONE | Fixes #149474
| true |
2,930,270,273 | There is some discrepancy between the document explain and code implement of optim.SGD() when use maximize=True | l1351868270 | closed | [
"module: docs",
"module: optimizer",
"triaged",
"actionable"
] | 2 | NONE | ### 🐛 Describe the bug
In the document (https://pytorch.org/docs/stable/generated/torch.optim.SGD.html) .The loop is
It means:
1.get the original grad, $g_{t} = og_{t}$
2.weight_decay != 0, update the grad, $g_{t} = og_{t} ... | true |
2,930,269,577 | IndexError in linear_binary when X and Y are the same with max-autotune enabled | CaoE | open | [
"oncall: pt2",
"oncall: cpu inductor"
] | 0 | COLLABORATOR | ### 🐛 Describe the bug
When the x and y are the same in the inputs with max-autotune enabled, an index error occurs.
Simple reproducer:
```
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
self.linear = torch.nn.Linear(1024, 1024)
def forward(self, input):
out = se... | true |
2,930,265,708 | nn.Linear layer initialization formula wrong in docs | karanjakhar | closed | [
"module: docs",
"module: nn",
"triaged",
"actionable"
] | 2 | NONE | ### 📚 The doc issue
But in implementation it's:
### Suggest a potential alternative/fix
It should be:
![Image](https://github.com/u... | true |
2,930,265,257 | [Intel GPU][PT2E] bugfix: use zero-point to decide conv src zp mask | ZhiweiYan-96 | closed | [
"module: cpu",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/xpu"
] | 8 | COLLABORATOR | # Motivation
The PR fix a bug that wrongly decides the zero-point mask setting. Specifically, it deems zero-point is always not zeros due to scale is used for judgement. Fortunately, the bug only affects the performance. The accuracy is not affected.
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest a... | true |
2,930,258,252 | torch.compile(mode="max-autotune") produces different outputs from eager mode | tinywisdom | closed | [
"triaged",
"oncall: pt2",
"module: inductor",
"topic: fuzzer"
] | 4 | NONE | ### 🐛 Describe the bug
I'm encountering a result mismatch between eager mode and `torch.compile(mode="max-autotune")`.
The outputs differ beyond acceptable tolerances (e.g., `torch.allclose` fails), and this behavior persists in both stable and nightly builds.
### Related Discussion
I initially posted this issue o... | true |
2,930,251,005 | Pin auditwheel to 6.2.0 | atalman | closed | [
"Merged",
"ciflow/binaries",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Observing aarch64 failure in nightly:
https://github.com/pytorch/pytorch/actions/runs/13917778961/job/38943911228
Similar to: https://github.com/pytorch/vision/pull/8982
```
2025-03-18T08:44:58.4128744Z Repairing Wheel with AuditWheel
2025-03-18T08:44:58.5440988Z INFO:auditwheel.main_repair:Repairing torch-2.8... | true |
2,930,229,896 | `ParallelStyle`s (ColwiseParallel, etc) do not have a `__repr__()` | apaz-cli | closed | [
"oncall: distributed"
] | 2 | NONE | ### 🚀 The feature, motivation and pitch
I'm writing a TP plan for a new model, and it's not possible to print the dict to copy/paste it. It's making debugging the parallelism strategies from torchtitan much harder. `Placement` objects already have a `__repr__`, so this should be easy to support.
### Alternatives
_N... | true |
2,930,209,865 | Refactor `test/test_torch.py` by moving testcase to `test_indexing.py` | zeshengzong | open | [
"triaged",
"open source",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Following #148875
Fix `FIXME` in `test_torch.py` by moving test-cases to `test_indexing.py`
```python
# FIXME: move to test indexing
# FIXME: move to indexing test suite
```
- Move tests in `test/test_torch.py` to `test_indexing.py`
- Remove `FIXME` comments
## TestResult
```bash
pytest test/test_to... | true |
2,930,194,738 | torch.library.opcheck doesn't check strides for CPU Tensors | zou3519 | open | [
"high priority",
"module: cpp-extensions",
"triaged",
"module: custom-operators",
"module: library",
"module: pt2-dispatcher"
] | 3 | CONTRIBUTOR | Repro:
```py
import torch
from torchvision.transforms.functional import to_pil_image, pil_to_tensor
import PIL
def crop(pic, box):
img = to_pil_image(pic.cpu())
cropped_img = img.crop(box)
return pil_to_tensor(cropped_img).to(pic.device) / 255.
img = torch.ones(3, 64, 64)
img *= torch.linspace(0, 1, steps... | true |
2,930,114,308 | [audio hash update] update the pinned audio hash | pytorchupdatebot | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | COLLABORATOR | This PR is auto-generated nightly by [this action](https://github.com/pytorch/pytorch/blob/main/.github/workflows/nightly.yml).
Update the pinned audio hash. | true |
2,930,102,826 | [ROCm] support experimental CU carveout | jeffdaily | open | [
"module: rocm",
"triaged",
"open source",
"release notes: rocm",
"ciflow/rocm"
] | 1 | COLLABORATOR | Fixes #149280. Follow up to #147966, but now available for ROCm.
Since hipblaslt does not support HIPBLASLT_MATMUL_DESC_CU_COUNT_TARGET, we instead create a hipStream that has a CU mask applied. We pass this masked stream to hipblaslt instead of pytorch's current stream. We ensure stream ordering between streams ... | true |
2,930,102,458 | [export] Beef up guard_added logs | angelayi | closed | [
"Merged",
"ciflow/trunk",
"fx",
"ciflow/inductor",
"release notes: export"
] | 3 | CONTRIBUTOR | cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,930,094,489 | Catch OSError in general when writing files | HollowMan6 | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 9 | CONTRIBUTOR | Redundant exception types in `except (PermissionError, OSError):`. Write `except OSError:`, which catches exactly the same exceptions.
https://github.com/pytorch/pytorch/actions/runs/13935844871/job/39141062991
When hipify files, or writing cprofile files, PermissionError is not enough when the file is locat... | true |
2,930,072,971 | support multinomial for dynamic num_samples | avikchaudhuri | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: export"
] | 7 | CONTRIBUTOR | Test Plan: added test
Fixes #149048
Differential Revision: D71434914
| true |
2,930,063,823 | Avoid recompilation caused by is_mm_compute_bound | laithsakka | open | [
"triaged",
"oncall: pt2",
"module: dynamic shapes"
] | 0 | CONTRIBUTOR | From @Elias Ellison
is_mm_compute_bound is just to avoid benchmarking cases where it is reliably unprofitable.
so in the case of dynamic we probably should just return keep it on and not guard.
Here is my proposal to address this
The benchmarking is on by default, we disable it iff some conditions are statically know... | true |
2,930,052,153 | Use enum to select floating point format in FbgemmEmbedding APIs | MatzeB | closed | [
"fb-exported"
] | 3 | CONTRIBUTOR | Summary:
X-link: https://github.com/pytorch/FBGEMM/pull/3847
Most FBGemmEmbedding APIs currently feature a `bool is_bf16_out` parameter to differentiate between the float16 and bfloat16 format when the output array has type `uint16_t`.
I am in the process of adding E5M2 and E4M3FN formats for output arrays with type ... | true |
2,930,037,985 | Remove test_get_model_state_dict_del_memory | mori360 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"release notes: distributed (checkpoint)"
] | 7 | CONTRIBUTOR | test_get_model_state_dict_del_memory get unexpected memory, leading to the test failures.
Remove tests right now to avoid blocking the others.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,930,021,565 | [xpu] set aot device flags in cpp_extension | jingxu10 | closed | [
"open source",
"Merged",
"topic: not user facing",
"ciflow/xpu"
] | 31 | COLLABORATOR | If PyTorch is compiled with only AOT text strings starting with "dg2", the `_get_sycl_arch_list()` function will pass an empty string to `-device` argument of `ocloc` and then cause a compilation crash. | true |
2,930,005,954 | [Graph Partition] Support symbol inputs | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 3 | CONTRIBUTOR | This PR supports symbol inputs to graph partition functions. Before this PR, we rely on `node.read_writes` to get partition inputs. However, this does not cover symbol inputs.
In this PR, for each graph partition, we collect all symbol inputs which are required to be in scope to successfully perform codegen,... | true |
2,929,981,311 | Error when tracing torch.func.functional_call inside of a HOP | angelayi | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"module: higher order operators",
"module: pt2-dispatcher"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
I'm trying to add support for scanning over mulitple layers, and have verified it works with _fake_scan, so now I'm trying to replace that call with real `scan`. However I am running into an error in torch.compile when it's trying to trace the call to torch.func.functional_call with in my scan ... | true |
2,929,966,235 | Base version committed | jamesjwu | closed | [
"triaged"
] | 0 | CONTRIBUTOR | null | true |
2,929,965,999 | Support num_ctas > 1? | jamesjwu | open | [
"triaged",
"oncall: pt2"
] | 1 | CONTRIBUTOR | cc @chauhang @penguinwu | true |
2,929,965,947 | Support user defined triton kernels | jamesjwu | open | [
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | cc @chauhang @penguinwu | true |
2,929,965,883 | Support launch_enter and launch_exit hooks | jamesjwu | open | [
"low priority",
"triaged",
"oncall: pt2"
] | 4 | CONTRIBUTOR | cc @chauhang @penguinwu | true |
2,929,965,833 | Support save_cubin (and therefore, support cpp_wrapper use cases) | jamesjwu | open | [
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | cc @chauhang @penguinwu | true |
2,929,965,779 | Support sharedMem > 48 KB | jamesjwu | closed | [
"triaged",
"oncall: pt2"
] | 2 | CONTRIBUTOR | See parent issue: support StaticCudaLauncher when triton kernels require more than 48 KB of shared memory
cc @chauhang @penguinwu | true |
2,929,965,501 | Support any number of kernel arguments (fallback to heap allocation beyond N max arguments) | jamesjwu | closed | [
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | cc @chauhang @penguinwu | true |
2,929,965,192 | Hook up statically compiled triton kernels to FXGraphCache's warm start | jamesjwu | closed | [
"triaged",
"oncall: pt2"
] | 0 | CONTRIBUTOR | cc @chauhang @penguinwu | true |
2,929,965,044 | Hook up StaticCudaLauncher to torch.compile | jamesjwu | closed | [
"triaged"
] | 0 | CONTRIBUTOR | null | true |
2,929,963,551 | DTensor slicing on sharded dimension leads to replication | garrett361 | open | [
"oncall: distributed",
"triaged",
"module: dtensor"
] | 5 | NONE | Slicing of sharded `DTensor`s currently results in differing placements depending on the axis over which the `DTensor` is sharded:
* Slicing a sharded dimension leads to replication over that dimension.
* Slicing a replicated dimension preserves all placements of the `DTensor`
**Expectation**: slicing will preserve th... | true |
2,929,952,885 | [ROCm] skip test_RNN_dropout_state | dnikolaev-amd | closed | [
"module: rocm",
"open source",
"Merged",
"topic: not user facing",
"ciflow/rocm"
] | 3 | CONTRIBUTOR | PR to skip test_nn.py::TestNN::test_RNN_dropout_state
Currently ROCm doesn't support dropout value for RNN
PR to enable RNN dropout on ROCm still in review and blocked pytorch/pytorch#144572
Fixes: https://github.com/pytorch/pytorch/issues/68849
cc: @jithunnair-amd @pruthvistony
cc @jeffdaily @sunway5... | true |
2,929,950,466 | [skip ci] benchmark stack vs heap libtorch_agnostic.my_ones_like | janeyx99 | closed | [
"topic: not user facing"
] | 2 | CONTRIBUTOR | This PR was for benchmarking purposes. For the stack_my_ones_like op in this PR to work, libtorch's shim_common.cpp's to_ivalue() cannot delete sivp (as sivp is now on the stack and not the heap).
original my_ones_like:
<img width="538" alt="image" src="https://github.com/user-attachments/assets/aebf2b3b-b4c9-464d-... | true |
2,929,948,025 | [export] Support python assertion with symints. | zhxchen17 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"fx",
"module: dynamo",
"ciflow/inductor",
"release notes: export"
] | 10 | CONTRIBUTOR | Summary: This diff ports some technique from torch.fx symbolic trace to trace through Python asserts when we run into data dependent symbolic shape assertions, so that we can achieve the same effect as torch dynamo to automatically turn assert into torch.check()s.
Test Plan: buck test mode/opt caffe2/test:test_expor... | true |
2,929,944,334 | ci: Remove mentions and usages of DESIRED_DEVTOOLSET and cxx11 | seemethere | closed | [
"Merged",
"Reverted",
"ciflow/binaries",
"release notes: releng",
"skip-pr-sanity-checks",
"ci-no-td"
] | 17 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149443
This is a remnant of our migration to manylinux2_28 we should remove
these since all of our binary builds are now built with cxx11_abi
Signed-off-by: Eli Uriegas <eliuriegas@meta.com>
cc @albanD | true |
2,929,943,157 | [StaticCudaLauncher] Support any number of kernel arguments | jamesjwu | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149629
* #149657
* #149054
* __->__ #149442
Fixes #149450
This PR adds fallback support on StaticCudaLauncher for any number of kernel arguments. Above MAX_ARGS, we can do a heap allocation/malloc instead.
For 0 arguments, triton t... | true |
2,929,933,237 | Batch Sampler Speedup | GalAvineri | open | [
"triaged",
"open source",
"release notes: dataloader"
] | 5 | NONE | # Motivation
https://github.com/pytorch/pytorch/pull/147706 attempts to accelerate `BatchSampler` over `RandomSampler` by utilizing the fact that `RandomSampler` can construct all the epoch's indices before yielding them.
This PR generalizes this approach for all samplers that share this feature (e.g `SequentialSampl... | true |
2,929,927,619 | [pt2] Support statically launching triton compiled cuda kernels | jamesjwu | open | [
"triaged",
"actionable",
"oncall: pt2",
"module: inductor",
"module: user triton"
] | 1 | CONTRIBUTOR | This is a master issue describing progress for StaticCudaLauncher.
Overall, the goal here is to be able to statically launch cuda kernels generated by Triton from just the cubin file and various metadata, without having to ever call CompiledKernel.init_handles(). To do so, we need to:
- Implement the launcher itsel... | true |
2,929,925,787 | [dynamo] recursive-only dont_skip_tracing with traceback approach | williamwen42 | open | [
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"keep-going",
"module: compile ux"
] | 1 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #149439
Attempt #2 at https://github.com/pytorch/pytorch/pull/148736 using a traceback approach rather than a global variable approach.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzh... | true |
2,929,914,230 | Fix format string in ck_gemm_template.h for int64_t variables | izaitsevfb | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Summary:
Change %d to %ld in printf format specifier to correctly handle int64_t variables n, m, k.
This fixes compilation errors in HIP builds where the format string didn't match the argument type.
forward fix for D71412006
```
In file included from fbcode/caffe2/aten/src/ATen/native/hip/ck_gemm_bfloat16.hip:4:
fbc... | true |
2,929,880,500 | [MPSInductor] Move threadfence at the right location | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps"
] | 7 | CONTRIBUTOR | Not sure how it worked in the past, but fence should be before first read from the shared memory, not after it.
This bug was exposed by https://github.com/pytorch/pytorch/pull/148969 which removed unnecessary barrier before calling `threadgroup_reduce` functions
Test plan:
```
% python3 generate.py --checkpoint_pat... | true |
2,929,863,013 | [MTIA] Add _mtia_getCurrentRawStream to MTIA module | PatriceVignola | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary: The FlexAttention path generates code that uses this function. Although streams are not used yet in Triton-MTIA, adding this now allows us to not branch out just for MTIA and generate different code.
Test Plan: CI
Reviewed By: chaos5958
Differential Revision: D70072057
| true |
2,929,853,311 | Enable fast path for qlinear (static/dynamic) and qadd for AArch64 though ACL directly. | fadara01 | closed | [
"module: cpu",
"open source",
"module: arm",
"release notes: quantization",
"ciflow/linux-aarch64",
"arm priority"
] | 10 | COLLABORATOR | This is a backport for the PRs enabling a fast path for eager mode static/dynamic quantized matmuls and quantized add for AArch64 through Arm Compute Library (ACL) directly - https://github.com/pytorch/pytorch/pull/148585, https://github.com/pytorch/pytorch/pull/148653.
PR https://github.com/pytorch/pytorch/pull/148... | true |
2,929,823,041 | Supporting non-tensor-data write_size in planner write items. | pradeepfn | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"Reverted",
"ciflow/trunk",
"release notes: distributed (checkpoint)",
"ci-no-td",
"oncall: distributed checkpointing"
] | 9 | CONTRIBUTOR | Summary:
1\ The current write item structure does not contain the amount of data that needs to be written.
2\ the planner.item already has a size primitive 'tensor_storage_size'. https://fburl.com/code/7a0gsmw7 But only for tensors.
3\ Right now, the only way the writer layer get hold of this property (fro non tenso... | true |
2,929,812,139 | [MTIA] Ensure correct stream behavior for input_buffer add autograd on MTIA | jvandebon | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Test Plan: CI
Differential Revision: D71414498
| true |
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