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 |
|---|---|---|---|---|---|---|---|---|
2,814,784,130 | [dynamo][builtin-skipfiles-cleanup] Remove re | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145559
* #145804
* #145828
* __->__ #145826
* #145753
* #145744
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,814,753,085 | [Inductor-CPU] Codegened flex attention kernels don't appear in profiler profiling results | sanchitintel | closed | [
"oncall: cpu inductor"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
### Problem statement
Codegened Inductor-CPU Flex attention kernels don't appear in profiling results because they're missing calls to `RECORD_FUNCTION`.
### Steps to reproduce
1. Clear Inductor cache (on Linux, it can be done via command line - with `rm -rf /tmp/torchinductor_$(whoami)/*`)... | true |
2,814,723,579 | Back out "Revert "pickler for GraphModule (#141659)"" | aorenste | closed | [
"oncall: distributed",
"release notes: distributed (fsdp)",
"fx",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145824
Original commit changeset: 2de53b3b6592
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @Xiaob... | true |
2,814,609,618 | Fix environment deployment spam | huydhn | closed | [
"module: rocm",
"Merged",
"topic: not user facing",
"test-config/default",
"ciflow/rocm"
] | 3 | CONTRIBUTOR | With https://github.com/pytorch-labs/pytorch-gha-infra/pull/598 in place, the environment can now be removed.
Fixes https://github.com/pytorch/pytorch/issues/145704
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
2,814,547,384 | Remove unneeded CUDA logic from _create_build_env | cyyever | closed | [
"triaged",
"open source",
"Merged",
"topic: not user facing"
] | 3 | COLLABORATOR | Because FindCUDAToolkit.cmake has that logic.
| true |
2,814,541,264 | add test for capture_dynamic_output_shape_ops=True changing expected output between eager and compiled versions | bobrenjc93 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 10 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145821
Followup from https://github.com/pytorch/pytorch/issues/130290
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,814,538,013 | Simplify handling of max jobs in CMake builds | cyyever | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,814,532,025 | Replace distutils.version with copied looseversion | cyyever | open | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 3 | COLLABORATOR | distutils was deprecated.
| true |
2,814,515,296 | Update cutlass pin from 3.6 to 3.7 | henrylhtsang | closed | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | ghstack-source-id: 1211a4456d2f5fe7871fef29a78f7e9f884a7bcf
Pull Request resolved: https://github.com/pytorch/pytorch/pull/145817
Testing right now
| true |
2,814,514,808 | Update cutlass pin from 3.6 to 3.7 | henrylhtsang | closed | [
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145817
| true |
2,814,512,759 | [DTensor] Add pointwise ops strategy for `aten.minimum` | wz337 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"module: dtensor"
] | 4 | CONTRIBUTOR | Need it for Shampoo optimizer.
https://github.com/facebookresearch/optimizers/blob/9c5700ad5ee81c28dc565c1a49c4b940da28eb8d/matrix_functions.py#L240-L242
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wconstab @d4l3k @c-p-i-o @tianyu-l @XilunWu | true |
2,814,484,553 | [AOTI] Cache treespec_loads calculation | henryhu6 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 8 | CONTRIBUTOR | Summary: Treespec can be reused instead of calculated from str every AOTI module call. Using cached result saves 0.2ms for each module call.
Test Plan:
Before:
{F1974751578}
After:
{F1974751667}
Differential Revision: D68749539
| true |
2,814,460,881 | [BE][Inductor] Simplify `custom_op` tests | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145814
Not sure what were the motivation behind repeating the same function over and over again for different backends
Change `test_custom_op_[123]` from acceptig separate (but identical) implementations for CPU, CUDA and XPU, to tak... | true |
2,814,457,290 | test oss ci whether will run cutlass backend test or not | henrylhtsang | closed | [
"fb-exported",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Differential Revision: D68748965
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov | true |
2,814,453,099 | [cutlass backend] check against arch >= 100 | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 10 | CONTRIBUTOR | Summary:
Want to add a guard against silent fallback to SM90.
GenerateSM100 was just added 3 days ago. https://github.com/NVIDIA/cutlass/blame/main/python/cutlass_library/generator.py#L8896
It should show up in CUTLASS 3.8 (not pinned yet).
Test Plan: ci
Differential Revision: D68748705
cc @voznesenskym @pengui... | true |
2,814,449,989 | [AsyncMM] re-enable and adapt to cutlass 3.6.0 (#144011) | yifuwang | open | [
"oncall: distributed",
"triaged",
"open source",
"fb-exported",
"release notes: distributed (c10d)"
] | 5 | COLLABORATOR | Summary:
cc H-Huang awgu kwen2501 wanchaol fegin fduwjj wz337 wconstab d4l3k c-p-i-o
imported-using-ghimport
Test Plan: Imported from OSS
Differential Revision: D68734003
Pulled By: yifuwang
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,814,408,650 | [export] Add tlparse to draft-export | angelayi | closed | [
"Merged",
"ciflow/trunk",
"release notes: export"
] | 4 | CONTRIBUTOR | Dependent on https://github.com/ezyang/tlparse/pull/87/files | true |
2,814,405,636 | [MPS] Extend `torch.mm`/`torch.bmm` to integral types | malfet | closed | [
"Merged",
"topic: improvements",
"release notes: mps",
"ciflow/mps"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145809
By using `naive_mm` kernel, but make sure that accumulation is done over int32 for smaller int types (and float for half and bfloat) as well as adding `navie_bmm` that follows the same pattern.
Remove stale restriction on ... | true |
2,814,405,562 | [MPS] Add `op_math_t` | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145809
* __->__ #145808
Similar to `at::opmath_t` to be used for reduction (and int mms) | true |
2,814,379,746 | DISABLED test_distributed_checkpoint_state_dict_type0_cuda (__main__.TestDistributedCheckpointCUDA) | pytorch-bot[bot] | open | [
"oncall: distributed",
"module: flaky-tests",
"skipped"
] | 7 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_distributed_checkpoint_state_dict_type0_cuda&suite=TestDistributedCheckpointCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/3624758944... | true |
2,814,379,707 | DISABLED test_distributed_checkpoint_state_dict_type0_cuda (__main__.TestDistributedCheckpointCUDA) | pytorch-bot[bot] | closed | [
"oncall: distributed",
"module: flaky-tests",
"skipped"
] | 1 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_distributed_checkpoint_state_dict_type0_cuda&suite=TestDistributedCheckpointCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/3625072505... | true |
2,814,379,657 | DISABLED test_return_advanced_contextmanager (__main__.ContextlibContextManagerTests) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 5 | NONE | Platforms: linux, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_return_advanced_contextmanager&suite=ContextlibContextManagerTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/36249687168).
O... | true |
2,814,372,438 | [dynamo][builtin-skipfiles-cleanup] Remove random | anijain2305 | closed | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145804
* #145876
* #145958
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,814,348,767 | Revert D68278174 | desertfire | closed | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Summary:
This diff reverts D68278174
New failures like T213574743 . Need more time to figure things out.
Test Plan: NA
Differential Revision: D68744749
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchule... | true |
2,814,339,003 | [export] allow bit shift builtin ops | ColinPeppler | closed | [
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145898
* __->__ #145802
| true |
2,814,337,482 | torch.linalg.eigh fails on CPU | atalman | closed | [
"triaged",
"module: regression",
"module: third_party",
"module: linear algebra"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
Based on this issue https://github.com/pytorch/pytorch/issues/94772 we see failure on CPU since PyTorch 2.4.0 Release.
Minumum test, requires [fc_layer_tensor.pt.zip](https://github.com/user-attachments/files/18566154/fc_layer_tensor.pt.zip) :
```python
import torch
t = torch.load('fc_layer_t... | true |
2,814,337,060 | config: Don't spam warnings about reference type configs | c00w | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 18 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145800
Summary:
https://github.com/pytorch/pytorch/issues/145755
The is_dynamic check for reference types was subtly broken, causing log spam
after it was accessed
Added an explicit type for is_default for reference types to make s... | true |
2,814,302,820 | inductor: Test for crash when nn.module has a bad getattr call. | c00w | closed | [
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145799
Note that I can't get this working, so I'd love some advice on how to write
this test.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng... | true |
2,814,298,140 | [will-not-merge] tuning | yifuwang | open | [
"oncall: distributed",
"open source",
"Stale",
"release notes: distributed (c10d)"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,814,298,074 | [Async-TP] improve algo selection | yifuwang | open | [
"oncall: distributed",
"open source",
"Stale"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145798
* __->__ #145797
* #145796
* #145795
* #145794
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,814,297,998 | [Async-TP] _pipelined_multi_all_gather_and_consume reduce overhead | yifuwang | open | [
"oncall: distributed",
"open source",
"Stale"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145798
* #145797
* __->__ #145796
* #145795
* #145794
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,814,297,639 | [AsyncMM] preliminary tuning | yifuwang | open | [
"oncall: distributed",
"open source",
"Stale",
"release notes: distributed (c10d)"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145798
* #145797
* #145796
* __->__ #145795
* #145794
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,814,297,550 | [Async-TP] Port _fused_all_gather_matmul_native to cpp to reduce launching overhead | yifuwang | open | [
"oncall: distributed",
"open source",
"Stale",
"release notes: distributed (c10d)"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145798
* #145797
* #145796
* #145795
* __->__ #145794
`_fused_all_gather_matmul_native` schedules multiple tasks (e.g., kernel, copy engine transfers, and stream_write_value32_) onto the GPU. Previously, `fused_all_gather_matmul_nati... | true |
2,814,287,859 | [CI][CUDA][cuSPARSELt] cusparselt 0.6.3 and cu121 related cleanups | nWEIdia | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | COLLABORATOR | Make ci cusparselt installation be consistent with nightly binary
Remove cu121 related docker build jobs and inductor runs Update test failures relating to cu121
cc @atalman @malfet @ptrblck @eqy @tinglvv @Skylion007 @huydhn
Retry of https://github.com/pytorch/pytorch/pull/145696 | true |
2,814,269,328 | Add CUDA 12.8 manywheel x86 Builds to Binaries Matrix | tinglvv | closed | [
"open source",
"Merged",
"ciflow/binaries",
"ciflow/trunk",
"topic: not user facing"
] | 18 | COLLABORATOR | https://github.com/pytorch/pytorch/issues/145570
Adding cuda 12.8.0 x86 builds first
TODO: resolve libtorch build failure and add build in https://github.com/pytorch/pytorch/pull/146084
cc @atalman @malfet @ptrblck @nWEIdia | true |
2,814,258,366 | cpp_wrapper: enable in aarch64 and x86 nightly dashboard performance runs | benjaminglass1 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145791
Adds `cpp_wrapper` mode to the nightly inductor benchmark runs, as well as optionally for manually triggered runs. This is justified by `aot_inductor` already being in those runs.
Additionally, re-enables `aot_inductor` ... | true |
2,814,233,818 | Move ROCm MI300 jobs to unstable to make CI green | ZainRizvi | closed | [
"module: rocm",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/unstable",
"ciflow/rocm"
] | 6 | CONTRIBUTOR | This is a temporary change to reduce intermittent tests failures. Jobs can be moved back once those machines get better runner isolation.
This also sneaks in a small fix to all the rocm job's build step to be run on Linux Foundation runners (the get-label-type dependency). The inductor-rocm-mi300 workflow already h... | true |
2,814,221,537 | Add CUDA 12.8 libtorch image | tinglvv | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | COLLABORATOR | https://github.com/pytorch/pytorch/issues/145570
Builds 12.8 libtorch docker/deprecate 12.1 meanwhile
cc @atalman @ptrblck @nWEIdia
| true |
2,814,210,855 | [MPS] masked_fill_ tiling for large tensors | Isalia20 | closed | [
"open source",
"release notes: mps"
] | 2 | COLLABORATOR | Fixes #143477 | true |
2,814,205,072 | Add ignorable commits on run_test.py to git blame ignore | janeyx99 | closed | [
"Merged",
"topic: not user facing"
] | 4 | CONTRIBUTOR | Chanced upon it while searching through cpp_extension related code. | true |
2,814,167,997 | [dynamo] Properly branch on an unspecialized NN module | StrongerXi | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145786
User defined NN module might have their own `__len__` or `__bool__`
methods which Dynamo needs to trace through, so that side effects and/or
reads to buffered writes are properly handled.
This patch removes the special `Unspe... | true |
2,814,163,331 | export serde turn hop's tuple arg into list | ydwu4 | open | [
"oncall: pt2",
"export-triage-review",
"oncall: export"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
See below repro:
```
import io
import torch
class Simple(torch.nn.Module):
def forward(self, ci, a, b):
def cond_fn(i, x, y):
return i > 0
def body_fn(i, x, y):
return i - 1, x + y, y - x
return torch._higher_order_ops.while_loop(cond_fn, b... | true |
2,814,153,916 | Run AOT custom extensions tests on Windows | janeyx99 | closed | [
"ciflow/trunk",
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145784
* #145764
| true |
2,814,132,243 | [BE]: Update typing of OrderedSet ancestor | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | Now that we are on python 3.9 minimum version we can properly use Generics in the superclass | true |
2,814,127,167 | Behavior Difference with Flex Attention + Sequence Packing | zaptrem | open | [
"triaged",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 1 | NONE | ### 🐛 Describe the bug
### Issue:
I'm observing odd attention map patterns in my flex attention sequence packing runs that aren't there on (what should be) identical F.SDPA runs:
F.SDPA maps at step 24k
Flex Attention maps a... | true |
2,814,124,686 | [dynamo] Properly prune dead input cell object | 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):
* __->__ #145781
This patch models input cell object as "newly created" rather than
"pre-existing" python object (see added documentation for why this
actually captures the semantics more accurately).
This enables the `SideEffects.prune_dead_... | true |
2,814,107,379 | Update CUDNN frontend submodule to 1.10.0 | Skylion007 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"release notes: cudnn"
] | 3 | COLLABORATOR | Update to CUDNN 1.10. Most of this is release is about supporting some new APIs needed for Blackwell integration and new features in the corresponding CUDNN version | true |
2,814,104,725 | [CUDNN][CUDNN V8 API] Allow user-specified CUDNN V8 API benchmarking technique | eqy | closed | [
"module: cudnn",
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 2 | COLLABORATOR | Useful for debugging apparent "regressions" when using cuDNN autotuning ("benchmarking")
cc @csarofeen @ptrblck @xwang233 | true |
2,814,095,969 | NJT support for cat() on the ragged dim | jbschlosser | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149892
* __->__ #145778
Requested [here](https://github.com/pytorch/pytorch/issues/118107#issuecomment-2615705795).
There's still a fair amount of work left. TODO:
* Fix the backwards pass (need NJT-specific derivative formula, possibl... | true |
2,814,076,536 | relax assertion to warning for unbacked binding names | avikchaudhuri | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: export"
] | 4 | CONTRIBUTOR | Summary:
Quick fix following up on https://github.com/pytorch/pytorch/pull/144894 to unblock internal tests.
Will keep investigating a more principled fix.
Test Plan: Failures in T213563826 now pass
Differential Revision: D68731710
| true |
2,814,076,483 | Update to NCCL 2.25.1 for 12.8 | tinglvv | closed | [
"triaged",
"open source",
"topic: not user facing"
] | 4 | COLLABORATOR | https://github.com/pytorch/pytorch/issues/145570
follow up for https://github.com/pytorch/pytorch/pull/145567/files | true |
2,814,052,976 | Error instead of silent specializing when an unbacked dimension has a value range cardinality of one | bobrenjc93 | closed | [
"triaged",
"oncall: pt2",
"module: dynamic shapes"
] | 0 | CONTRIBUTOR | ```
import torch
torch._dynamo.config.automatic_dynamic_local_pgo = False
@torch.compile()
def fn(x):
return torch.cat([x, torch.ones(5, 5)])
x = torch.ones(5, 5)
torch._dynamo.decorators.mark_unbacked(x, 0)
torch._dynamo.decorators.mark_unbacked(x, 1)
fn(x)
```
Results in
```
L_x_: "f32[u0, 5][5, 1]cpu"
```
... | true |
2,814,024,160 | [POC] flat_apply HOP | zou3519 | closed | [
"Stale",
"release notes: fx",
"fx"
] | 3 | CONTRIBUTOR | [no-ci]
Fixes #ISSUE_NUMBER
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,813,990,519 | Dynamo performance test benchmarks reuse model state between eager and compiled | xmfan | open | [
"triaged",
"module: benchmark",
"oncall: pt2",
"module: dynamo"
] | 0 | MEMBER | ### 🐛 Describe the bug
See `model`:
https://github.com/pytorch/pytorch/blob/64cd81712ddf867d1c4dc46ba4554d40d6d7d610/benchmarks/dynamo/common.py#L3431-L3470
Later, it is also used by the `speedup_experiment`. This can cause issues with stateful models like convit_base: https://github.com/huggingface/pytorch-image-mo... | true |
2,813,969,497 | Implement serializable getattr support for tensor subclasses | tugsbayasgalan | closed | [
"Merged",
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: export"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145772
builtins.getattr is not serializable, so we replace it with a custom op that has more refined schema.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx ... | true |
2,813,967,002 | Revert D68232274 | avikchaudhuri | closed | [
"fb-exported",
"ciflow/inductor",
"release notes: export"
] | 4 | CONTRIBUTOR | Summary:
This diff reverts D68232274
broken multiple tests - T213563826
Test Plan: NA
Differential Revision: D68725051
| true |
2,813,956,992 | [torch][distributed] re-merge NCCLComm::split impl | suo | closed | [
"oncall: distributed",
"fb-exported",
"Stale",
"release notes: distributed (c10d)"
] | 3 | MEMBER | Summary:
These were originally forked between fbcode and oss. This has led to some drift, as bugfixes related to ncclCommSplit + non-blocking never made it to internal. Now we're hitting these bugs in monarch so it would be nice to fix.
Just upstream the forked code and delete the fb-only version.
Test Plan: Unit tes... | true |
2,813,952,858 | Revert D68232274 | avikchaudhuri | closed | [
"fb-exported",
"ciflow/inductor",
"release notes: export"
] | 3 | CONTRIBUTOR | Summary:
This diff reverts D68232274
broken multiple tests - T213563826
Test Plan: NA
Differential Revision: D68725051
| true |
2,813,950,210 | Log info for AOTAutogradCache bypasses instead of warning | jamesjwu | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145768
Fixes #145767
FxGraphCache also logs to info instead of warning so lets do that
| true |
2,813,935,628 | Spammy Aot autograd cache warning | eellison | closed | [] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```with-proxy python benchmarks/dynamo/torchbench.py --backend inductor --device cuda --only
basic_gnn_edgecnn --amp --cold-start-latency --print-compilation-time --training --performance 2>&1
```
Gives
```
loading model: 0it [00:02, ?it/s]
cuda train basic_gnn_edgecnn
[WAR... | true |
2,813,917,063 | [cond] remove warning for unsupported tuple returns | pianpwk | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 4 | CONTRIBUTOR | I guess this is supported now | true |
2,813,916,554 | Add magma cuda build 12.8 | tinglvv | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | COLLABORATOR | https://github.com/pytorch/pytorch/issues/145570
cc @atalman @malfet @ptrblck @nWEIdia | true |
2,813,914,356 | Set -DPy_LIMITED_API flag for py_limited_api=True extensions | janeyx99 | closed | [
"Merged",
"ciflow/trunk",
"release notes: python_frontend"
] | 3 | CONTRIBUTOR | This could be BC breaking, because there was a period of time when we use py_limited_api=True but don't enforce the flag, and now that we will start enforcing the flag, people's custom extensions may fail to build.
This is strictly still better behavior, as it is sketchy to claim CPython agnosticism without the flag... | true |
2,813,912,780 | Run inductor perf benchmark on ROCm | huydhn | closed | [
"module: rocm",
"Merged",
"release notes: releng",
"test-config/default",
"ciflow/rocm"
] | 3 | CONTRIBUTOR | This requires https://github.com/pytorch/pytorch/pull/144594. The test run on PT2 dashboard is at https://hud.pytorch.org/benchmark/compilers?dashboard=torchinductor&startTime=Mon%2C%2020%20Jan%202025%2019%3A46%3A14%20GMT&stopTime=Mon%2C%2027%20Jan%202025%2019%3A46%3A14%20GMT&granularity=hour&mode=inference&dtype=bflo... | true |
2,813,903,406 | [export] fix non-strict pre_dispatch exporting while_loop | ydwu4 | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"keep-going"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145762
fix https://github.com/pytorch/pytorch/issues/145737.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,813,888,696 | dynamo cannot trace global op_set .__contains__ | ydwu4 | open | [
"high priority",
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 7 | CONTRIBUTOR | ### 🐛 Describe the bug
This gives a graph break:
```python
import torch
op_set = {
torch._C._set_grad_enabled,
torch.amp._enter_autocast,
torch.amp._exit_autocast,
}
def f(x):
if torch.ops.aten.add in op_set:
return x.sin()
return x.cos()
torch.compile(f, fullgraph=True, backend="eager")... | true |
2,813,877,447 | Performance degradation in scaled_dot_product_attention with attn_mask and sequence length multiples of 16 | alexanderb14 | closed | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | ### 🐛 Describe the bug
There's a performance degradation when using `scaled_dot_product_attention` with the `attn_mask` argument, when the sequence length is a multiple of 16. This issue can be reproduced using the following code snippet.
**Reproducer Code**
```
import torch
from torch._inductor.runtime.benchmarking... | true |
2,813,873,581 | [chore][ez] change alloc buffer size from 4000 to 4096 | c-p-i-o | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145759
* #145757
* #145756
Summary:
Allocations typically happen as a power of 2 anyway.
Change the default alloc size to 4096 so eek out a bit more perf.
Test:
unit tests
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337... | true |
2,813,873,445 | [bug] fix memory leaks for failed queries | c-p-i-o | closed | [
"oncall: distributed",
"release notes: distributed (c10d)"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
Summary:
Correctly handle freeing allocated buffers if query does not parse.
This would only happen in atypical scenarios.
1. Call stream.commit() for failure cases. This will free up the buffer
that's allocated in the `rea... | true |
2,813,873,322 | [bug] handle case when remote peer closes connection | c-p-i-o | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145759
* __->__ #145757
* #145756
Summary:
In the case where remote peer closes the connection, nread returns 0. In
this case, we still want to free up the allocated buffer.
Also, reorder the if so that the likely success cases (nread > 0) ... | true |
2,813,873,136 | [chore] fix new linter | c-p-i-o | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145759
* #145757
* __->__ #145756
Summary:
Fix new linter that's complaining when I made changes to this file:
class 'LibUVStoreDaemon' defines a non-default destructor but does not
define a copy constructor, a copy assignment operator, a m... | true |
2,813,838,969 | Spam: UserWarning: Skipping serialization of skipfiles_inline_module_allowlist value | ezyang | open | [
"module: logging",
"triaged",
"oncall: pt2"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
When I run
```
import torch
@torch.compile(dynamic=True)
def rmsnorm_without_weight(hidden_states, eps=1e-6, dtype=torch.bfloat16):
variance = hidden_states.to(torch.float32).pow(2).mean(-1, keepdim=True)
hidden_states = hidden_states * torch.rsqrt(variance + eps)
hidden_states = ... | true |
2,813,829,222 | [OSS] Add no dist as an argument to DCP top level apis | ankitageorge | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary: No-dist, for a non-distributed checkpoint, was a top level param in the past, but was removed. This was requested back in https://github.com/pytorch/pytorch/issues/125777 and will be needed for our torchtune changes to use DCP
Test Plan: existing tests pass
Differential Revision: D68714246
cc @H-Huang @a... | true |
2,813,821,316 | [dynamo][builtin-skipfile-cleanup] Remove signal | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"keep-going"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #145559
* #145804
* #145828
* #145826
* __->__ #145753
* #145744
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,813,819,640 | initialize device when pinning memory on this device, short circuit i… | ngimel | closed | [
"Merged",
"ciflow/trunk",
"release notes: cuda"
] | 8 | COLLABORATOR | …s_pinned if device is not initialized
Do not land
RFC
potential fix for #144687
Now `.is_pinned(device="cuda")` does not initialize device and thus doesn't poison the fork (but it complains about `device` arg being deprecated). To not need `device=` arg we'd need to fix get_accelerator to not initialize device. ... | true |
2,813,816,802 | [OSS] Update FileSystem methods to properly handle a string argument | ankitageorge | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Summary: When testing, I tried to pass in a string argument to the FileSystem class' methods, which is a valid input, but the cast() that casted the string to a path wasn't working as was likely expected and was leading all the methods to fail with a string arg. Instead of a cast, a proper constructor should be used.
... | true |
2,813,812,422 | [dynamo] save/restore system random state more carefully | williamwen42 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor",
"ci-no-td"
] | 16 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145750
Reattempt of https://github.com/pytorch/pytorch/pull/145435 since the state of the linked internal diff appears to be messed up.
Note: I have verified that the previously failing internal tests now pass internally.
cc @... | true |
2,813,806,978 | [checkpointing] Add support for HuggingFace filesystem to read and write DCP checkpoints | ankitageorge | closed | [
"oncall: distributed",
"fb-exported",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary: This diff adds a new filesystem _HfFileSystem, built on top of the existing HfFileSystem. We can't use the existing class that HF has, because we need a few more methods so that it works with our existing save and load APIs. We also had fs as an argument to the FileSystemWriter and FileSystemReader so that it ... | true |
2,813,796,905 | Set USE_CUFILE=1 by default and add pypi package to binary build matrix | mikaylagawarecki | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 8 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145748
| true |
2,813,795,919 | [Torch] Extract arange_out resizing logic into a helper function that can be used by other devices | PatriceVignola | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Summary: We want to use the resizing implementation for arange_out in other devices (in this case MTIA), to make sure that the computations match and to avoid off-by-one-errors.
Test Plan: Existing CI tests pass.
Differential Revision: D68694489
| true |
2,813,782,830 | [ATen][CUDA] Implement 128 bit vectorization v2 | Aidyn-A | closed | [
"module: cuda",
"open source",
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"ci-no-td",
"module: core aten"
] | 20 | COLLABORATOR | This is a re-base PR to my previous one #141959.
Description from the original PR:
This PR implements 128-bit vectorization. It improves the performance of contiguous elementwise ops by 4-10% on Hopper H100.
<details>
<summary>The benchmark code used </summary>
```Python
import time
import torch
f... | true |
2,813,758,428 | Add nitpick warning that aoti_torch/c/shim.h is ABI stable | ezyang | closed | [
"Merged",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145745
Signed-off-by: Edward Z. Yang <ezyang@meta.com> | true |
2,813,740,994 | [dynamo][builtin-skiplist-cleanup] Remove weakref | 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):
* #145559
* #145804
* #145828
* #145826
* #145753
* __->__ #145744
WeakKeyDictionary already works very nicely with the UserDefinedObject Variable Tracker.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe... | true |
2,813,737,711 | TorchScript run_method fails from 2.5.0 onward on Ubuntu | blace-ai-transfer | open | [
"oncall: jit",
"module: deadlock"
] | 4 | NONE | ### 🐛 Describe the bug
Using https://download.pytorch.org/libtorch/cu118/libtorch-shared-with-deps-2.5.1%2Bcu118.zip or https://download.pytorch.org/libtorch/cu118/libtorch-shared-with-deps-2.5.0%2Bcu118.zip the following code does not return. Console prints the "run..." but never seems to finish execution of the `ru... | true |
2,813,704,938 | [aarch64] Rebuild everything with ArmPL | psaab | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 12 | CONTRIBUTOR | Summary: Rebuild everything that used OpenBLAS with ArmPL
Test Plan: CI, prod test
Reviewed By: Nicoshev
Differential Revision: D68219559
| true |
2,813,650,365 | [BE]: Update Cutlass submodule to 3.8 candidate for SM100+ support | Skylion007 | closed | [
"open source",
"better-engineering",
"ciflow/trunk",
"release notes: cuda",
"topic: not user facing"
] | 17 | COLLABORATOR | Update CUTLASS submodule to 3.8 candidate for preliminary Blackwell support, without this PyTorch will not compile various CUTLASS kernels properly for Blackwell. | true |
2,813,638,034 | [MPS] Fix `c0::metal::log_gamma` correctness on M4 | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #145740
To workaround a bug where `abs` method call seems to be ignored before calling log, which could be reproduced by running the following code (submitted as FB16415011 )
```swift
import Metal
func run_shader<T: BinaryFloati... | true |
2,813,499,812 | No broadcasting by default. | YagaoDirac | open | [
"triaged",
"needs research",
"module: python frontend"
] | 5 | NONE | ### 🚀 The feature, motivation and pitch
I actually ran into shape bug but pytorch guessed it would be some broadcasting intentionally, and wasted a bit time( like hours, but still acceptable).
Then I decide to print the shape and denote it in the variable name, like g_reshaped__batch_1_output.
I prefer the no-broadc... | true |
2,813,484,099 | [Docs] Make comm handle wait & is_completed docs more clear for multi-stream | Edenzzzz | open | [
"triaged",
"open source",
"Stale",
"release notes: distributed (c10d)"
] | 5 | NONE | Fixes #145713
Looks like a earlier fix on `wait()` (https://github.com/pytorch/pytorch/pull/143305) has been pushed but not reflected in the main branch, so feel free to revert my change on that part.
Made coressponding clarifications on `is_completed`
cc @awgu @wconstab | true |
2,813,470,095 | while_loop fails to export when strict=False | desertfire | closed | [
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 1 | CONTRIBUTOR | Repro:
Apply the following patch, then run `python test/export/test_export.py -k test_while_loop_simple` and the test fails when `strict=False`
```
diff --git a/test/export/test_export.py b/test/export/test_export.py
index 9b070141ac3..22096a68a1b 100755
--- a/test/export/test_export.py
+++ b/test/export/test_export.p... | true |
2,813,435,813 | [MPS][BE] Use conveinence methods to set args | malfet | closed | [
"Merged",
"topic: not user facing",
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | It's better to call `mtl_setArgs` rather than set arguments one by one with the risk of making a typo
Also, all interactions with MTLCommandBuffer must be serialized, which is commonly done using dispatch queues
| true |
2,813,403,617 | [MPSInductor] Compiled lgamma produces different results on M2 vs M4 for float16 | malfet | closed | [
"triaged",
"module: mps",
"oncall: pt2"
] | 3 | CONTRIBUTOR | ### 🐛 Describe the bug
Running this on my M4
```
% python -c "import torch; print(torch.compile(torch.ops.aten.lgamma)(torch.arange(128, device='mps', dtype=torch.half).sin()))"
```
results in tensor full of NaNs
```
tensor([ inf, 1.1414e-01, 5.9540e-02, 1.8916e+00, nan, nan,
... | true |
2,813,365,866 | Workaround for unsupported return of multiple tensors for `torch.cond` in a model intended for torch.onnx.export(dynamo=true,...) | ionymikler | closed | [
"module: onnx",
"triaged",
"oncall: pt2",
"module: higher order operators",
"oncall: export"
] | 14 | NONE | ### 🐛 Describe the bug
Trying to `onnx.export` a `nn.Module` with a conditional in its computational graph. In essence similar to this example:
```py
import torch
class Wrapper(torch.nn.Module):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.cond_model = CondModel()
... | true |
2,813,335,428 | "AssertionError: Guard check failed" on PyTorch nightlies after 2025-01-22 when running torchao tests | vkuzo | closed | [
"high priority",
"triaged",
"oncall: pt2",
"module: dynamo"
] | 10 | CONTRIBUTOR | ### 🐛 Describe the bug
Running the following command introduces an assertion error on recent versions of PyTorch nightlies:
```
// run a test in torchao repo
// test source code: https://github.com/pytorch/ao/blob/main/test/prototype/test_smoothquant.py
> pytest test/prototype/test_smoothquant.py -s -x
...
... | true |
2,813,279,758 | add pt2 callbacks for backward pass and prevent duplicate callbacks | burak-turk | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Summary: This change adds callbacks for lazy backwards compilation while preventing duplicate callbacks to be fired.
Differential Revision: D68577593
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 ... | true |
2,813,256,319 | [Performance] `tensordot` has substantial overhead | randolf-scholz | open | [
"module: performance",
"triaged",
"module: linear algebra"
] | 11 | CONTRIBUTOR | ### 🐛 Describe the bug
`torch.tensordot(A, B)` is ~50% slower than `torch.dot(A.flatten(), B.flatten())` for matrices of size≤512 on GPU, and on CPU it is even slower than `torch.trace(A.T @ B)` until n=1024.
![Image](https://... | true |
2,813,142,448 | [export] Fail fast on pytorch with `aoti_load_package` | bhack | open | [
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
When we use
`aoti_compile_and_package` for GPU and then on another instance we use `aoti_load_package` without GPU it is failing internally at:
https://github.com/triton-lang/triton/blob/main/python/triton/runtime/driver.py#L8
As the message is a bit ambiguous
`raise RuntimeError(f"{len(acti... | true |
2,813,139,536 | KL div between t-distribution | moghadas76 | open | [
"module: distributions",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
KL between T-distribution did not implemented:
```python
target_distribution = StudentT(
df=df,
loc=target,
scale=torch.ones_like(target) * scale.mean() # Using mean scale for target
)
# Compute KL divergence
kl_div = torch.... | true |
2,812,788,078 | [ATen][Native][CUDA][SCALED_MM] limit f8f8bf16 rowwise scaled matmul to sm_90 | Aidyn-A | closed | [
"module: cuda",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"matrix multiplication",
"module: float8",
"module: core aten"
] | 6 | COLLABORATOR | The CUTLASS-based kernel for f8f8bf16 rowwise scaled matmul is specific to Hopper devices only. It is not re-usable on newer devices without modifications. This PR adds a guard for this matmul to be sm_90 specific. Once the kernel is there, the guard may be removed.
cc @ptrblck @msaroufim @eqy @yanbing-j @vkuzo @alb... | true |
2,812,586,788 | [NT] torch.cat for nested tensors | FloCF | closed | [] | 1 | NONE | ### 🚀 The feature, motivation and pitch
Nested tensors are a great way to handle a batch of sequences with different lengths, which is often the case in NLP or ViTs for images of very different resolutions.
Often, you add a `cls_token` to the input tensor as the first token, which currently (awaik) is not straightfor... | true |
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