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 |
|---|---|---|---|---|---|---|---|---|
3,018,372,613 | [logging] Clean up dynamo_timed usages in cudagraph_trees | masnesral | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152136
Summary: I'm investigating differences in total torch.compile overhead in our two main internal sources: dynamo_compile and pt2_compile_events. One source of discrepancy is due to cudagraphs overheads. Currently, we have a ... | true |
3,018,317,780 | Unaccaptable OOMs all the time. | Deathawaits4 | open | [
"needs reproduction",
"module: cuda",
"module: memory usage",
"triaged"
] | 3 | NONE | Hello,
i don't want to sound harsh, but pytorch has ruined me many training runs, and wasted many hours of training
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 250.00 MiB. GPU 0 has a total capacity of 79.26 GiB of which 104.75 MiB is free. Process 1007710 has 79.14 GiB memory in use. Of the alloca... | true |
3,018,241,032 | [RFC] Proposed Changes to Feature Tracking & Classification for PyTorch Releases starting Release 2.8 | atalman | open | [
"triaged"
] | 0 | CONTRIBUTOR | RFC Authors: @anitakat @atalman
Hello everyone,
Following feedback and discussion on existing gaps of the feature review process, below are proposed changes for which we are keen to have your input.
## Feature Tracking Process
Beginning with release 2.8, the PyTorch release will only track major features. At thi... | true |
3,018,235,081 | [ROCm] Fixes to enable VM-based MI300 CI runners | jithunnair-amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 3 | COLLABORATOR | New VM-based MI300 CI runners tested in https://github.com/pytorch/pytorch/pull/151708 exposed some issues in CI that this PR fixes:
* HSAKMT_DEBUG_LEVEL is a debug env var that was introduced to debug driver issues. However, in the new MI300 runners being tested, since they run inside a VM, the driver emits a debug... | true |
3,018,233,465 | Remove some instances of uninitialized memory use | pganssle-google | open | [
"open source",
"topic: not user facing"
] | 5 | CONTRIBUTOR | Two changes, one caught by MSAN, the other caught because it was blowing up tests.
The change in test_ir fixes a use-after-free by capturing the variable being closed over by value.
The change in debug_util initializes all values for the SourceLocation object. | true |
3,018,181,623 | [C10D] Autograd Support for Collectives | wconstab | open | [
"oncall: distributed",
"triaged"
] | 0 | CONTRIBUTOR | Building on #148690 and following from [this post](https://discuss.pytorch.org/t/supporting-autograd-for-collectives/219430) there are a few we should make to support autograd properly in our collective library.
**Problem:** Collectives today silently no-op during backwards
The first thing we should do since it's sim... | true |
3,018,174,869 | AOTI cannot move tensors between cuda devices | yushangdi | open | [
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
When we move tensors between cuda devices, AOTI just does a `AOTI_TORCH_ERROR_CODE_CHECK(aoti_torch_copy_(buf0, arg0_1, 0));`, which doesn't really change the device index. The resulting tensor is still in device 0.
Exported Program:
```
def forward(self, x):
x, = fx_pytree.tree_flatten_s... | true |
3,018,159,218 | [dynamic shapes] aten.constant_pad_nd meta impl | pianpwk | closed | [
"Merged",
"ciflow/trunk",
"release notes: export"
] | 5 | CONTRIBUTOR | We know the output shape, and we know this always produces a clone. Avoids data-dependent errors from the decomposition.
along with https://github.com/pytorch/pytorch/pull/150483, should fix https://github.com/pytorch/pytorch/issues/123855 | true |
3,018,156,403 | FlexAttention + Export / AOTI | drisspg | open | [
"triaged",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 0 | CONTRIBUTOR | # Summary
cc @chauhang @penguinwu @zou3519 @ydwu4 @bdhirsh @Chillee @yanboliang @BoyuanFeng | true |
3,018,149,226 | [C10D] Make collectives backwards throw an error | wconstab | open | [
"oncall: distributed",
"triaged"
] | 1 | CONTRIBUTOR | Today functional collectives and C10D collectives silently ignore backwards, which can surprise users and lead to missing gradients and incorrect training.
Many users of these collectives do not intend to use the backwards pass, so this limitation is not affecting them. They either call functional_collectives _during... | true |
3,018,070,853 | [CI] [anaconda] Utilities | atalman | closed | [
"module: ci",
"triaged",
"better-engineering"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Related to https://github.com/pytorch/pytorch/issues/138506
```
torch/utils/data/dataframes_pipes.ipynb
torch/utils/data/datapipes/utils/decoder.py
torch/utils/data/standard_pipes.ipynb
tools/setup_helpers/env.py
```
### Versions
2.8.0
cc @seemethere @malfet @pytorch/pytorch-dev-infra | true |
3,018,069,234 | Add runtime asserts to AOTI | yushangdi | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: export"
] | 22 | CONTRIBUTOR | Summary:
Solves https://github.com/pytorch/pytorch/issues/151925
Currently, AOTI only generate runtime asserts for unbacked symints. We should generate asserts for all `_assert_scalar` calls in the input graph.
Also factored out the run time assertion logic to a separate function.
We need to generate ... | true |
3,018,065,203 | [CI] [anaconda] Utility scripts and workflows | atalman | closed | [
"module: ci",
"triaged",
"better-engineering"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Related to https://github.com/pytorch/pytorch/issues/138506
```
.ci/pytorch/python_doc_push_script.sh#L76
.github/workflows/upload-test-stats-while-running.yml
.github/workflows/llm_td_retrieval.yml
.github/scripts/test_trymerge.py
tools/code_coverage/package/tool/print_report.py
```
### Vers... | true |
3,018,048,393 | [CI] [anaconda] Benchmarks anaconda removal | atalman | closed | [
"module: ci",
"triaged",
"better-engineering"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
Related to #138506
Benchmarks files
```
benchmarks/dynamo/Makefile
benchmarks/dynamo/runner.py
benchmarks/sparse/test_csr.sh
torch/utils/benchmark/examples/blas_compare_setup.py
torch/utils/benchmark/examples/prepare_e2e.sh
```
### Versions
2.8.0
cc @seemethere @malfet @pytorch/pytorch-de... | true |
3,018,043,192 | [NJT] `.bmm`'s BmmBackward0 fails compilation when second arg requires grad | imh | open | [
"module: autograd",
"triaged",
"module: nestedtensor",
"oncall: pt2"
] | 1 | NONE | ### 🐛 Describe the bug
When we try to compile `njt_tensor.bmm(default_tensor)` and `default_tensor` requires grad, compilation fails.
```python
import torch
def do_bmm(x, y):
return x.bmm(y.transpose(1,2))
d = 4
x = torch.nested.nested_tensor(
[
torch.randn((1,d)),
torch.randn((1,d)),
... | true |
3,018,024,782 | [poetry] 2.7.0+cpu includes cuda as a dependency | peter-axion | closed | [
"triage review",
"module: binaries",
"module: regression",
"topic: binaries"
] | 6 | NONE | ### 🐛 Describe the bug
I use torch `+cpu` variants in images I run on VMs without GPUs because the CUDA libraries are huge, so if I don't need them then I definitely don't want them.
When I use `poetry lock` on poetry 1 or 2 with torch `2.7.0+cpu` in my pyproject.toml, the cuda libraries and triton are added as depe... | true |
3,018,023,445 | [dynamo] Remove unnecessary guarding on callable user defined objects | anijain2305 | closed | [
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152120
* #151847
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,017,977,356 | [dynamo][ca] support dynamic annotations on tensors in ListVariables/TupleVariables | xmfan | open | [
"Merged",
"Reverted",
"ciflow/trunk",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo",
"ci-no-td"
] | 12 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151860
* __->__ #152119
* #151962
* #151731
Together with https://github.com/pytorch/pytorch/pull/151962, FIXES https://github.com/pytorch/pytorch/issues/133575
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSup... | true |
3,017,949,132 | Update torch/optim/optimizer.py | janeyx99 | closed | [
"release notes: optim"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152118
* #152117
* #152116
| true |
3,017,948,908 | Update torch/optim/optimizer.py | janeyx99 | closed | [
"release notes: optim"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152118
* __->__ #152117
* #152116
| true |
3,017,948,639 | Include other accelerators in capturable docstr for optimizers | janeyx99 | closed | [
"release notes: optim"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152118
* #152117
* __->__ #152116
| true |
3,017,910,917 | Unify how we create random inputs for auto-tuning | masnesral | closed | [
"module: rocm",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152115
Summary: We're creating autotune inputs slightly differently when autotuning in-process vs. in a subprocess: One implementation is in TensorMeta.to_tensor() and another in AlgorithmSelectorCache.benchmark_example_value. Move t... | true |
3,017,899,222 | [Torch Profiler] Only two streams captured in CUDA graph but multiple streams shown in Torch Profiler | ispobock | closed | [
"module: cuda",
"triaged"
] | 6 | NONE | ### 🐛 Describe the bug
As shown in the following demo code, I use two streams to overlap the `set_kv_buffer` operation, which will be captured in a CUDA graph. The `alt_stream` is created when the KVPool object initialized, so this stream should be reused all the runtime. There is no more stream created during the ru... | true |
3,017,898,839 | [CI] [anaconda] CI Build and Test scripts MacOS | atalman | closed | [
"module: ci",
"triaged",
"better-engineering"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
Related to https://github.com/pytorch/pytorch/issues/138506
CI Build and Test scripts to replace:
.ci/pytorch/macos-test.sh - used for torchbench
astunparse numpy scipy ninja pyyaml setuptools cmake typing-extensions requests protobuf numba cython scikit-learn librosa
.github/workflows/_mac-b... | true |
3,017,886,320 | Pin to SHA for actions outside of PyTorch | zxiiro | closed | [
"module: rocm",
"topic: not user facing"
] | 1 | COLLABORATOR | Pin actions from repos external to the PyTorch project to their shasums for security. This is a best practice as Git tags are not immutable.
https://openssf.org/blog/2024/08/12/mitigating-attack-vectors-in-github-workflows/
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @... | true |
3,017,864,752 | [ONNX] Implement sym_not | justinchuby | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: improvements"
] | 4 | COLLABORATOR | Implement onnx support for sym_not. Replaces https://github.com/pytorch/pytorch/pull/147472
Fix https://github.com/pytorch/pytorch/issues/136572 | true |
3,017,861,114 | Pin to SHA for actions outside of PyTorch | zxiiro | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | Pin actions from repos external to the PyTorch project to their shasums for security. This is a best practice as Git tags are not immutable.
https://openssf.org/blog/2024/08/12/mitigating-attack-vectors-in-github-workflows/
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @... | true |
3,017,786,422 | Python 3.11 and 3.13 support for Windows Arm64 | iremyux | closed | [
"module: windows",
"open source",
"module: arm",
"Merged",
"ciflow/binaries",
"topic: not user facing"
] | 3 | COLLABORATOR | This PR adds Python 3.11 and 3.13 support Windows Arm64 wheels and creates the necessary jobs
cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @Blackhex @malfet @snadampal @milpuz01 @aditew01 @nikhil-arm @fadara01 | true |
3,017,759,979 | [inductor][cpu] AMP static shape default wrapper AOTInductor performance regression in 2025_04_20 nightly release | zxd1997066 | open | [
"module: regression",
"topic: performance",
"oncall: pt2",
"oncall: cpu inductor"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
<p>AMP static shape default wrapper AOTInductor</p><table border="1" class="dataframe table">
<thead>
<tr style="text-align: right;">
<th>suite</th>
<th>name</th>
<th>thread</th>
<th>batch_size_new</th>
<th>speed_up_new</th>
<th>inductor_new</th>
... | true |
3,017,750,908 | Some Doc Issue about `torch.lobpcg()` | ILCSFNO | open | [
"module: docs",
"triaged",
"module: linear algebra"
] | 0 | CONTRIBUTOR | ### 📚 The doc issue
This issue is about func: `torch.lobpcg()`
### Discuss 1
Seen from #139563, some similar situation in `torch.lobpcg()`:
The doc of [torch.lobpcg()](https://pytorch.org/docs/stable/generated/torch.lobpcg.html#torch-lobpcg) shows its description as below:
https://github.com/pytorch/pytorch/blob/d... | true |
3,017,717,304 | Relax tolerance on test_aot_autograd_exhaustive_matmul_cpu_float32 without MKL | Flamefire | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | COLLABORATOR | When e.g. OpenBLAS is used instead of MKL the differences get to large:
> Greatest absolute difference: 5.91278076171875e-05 at index (7,) (up to 1e-05 allowed)
> Greatest relative difference: 3.468156592134619e-06 at index (7,) (up to 1.3e-06 allowed)
I traced some of the matmul operations and there are differenc... | true |
3,017,686,303 | [MTIA] Contribute OpExpanderPass to FX pass infra. | patrick-toulme | open | [
"fb-exported",
"release notes: fx",
"fx"
] | 4 | NONE | Summary:
MTIA has been using an OpExpanderPass in our compiler. This type of pass allows pass authors to write two functions
1. Pattern Matcher - returns a boolean and an optional metadata tuple
2. Expander - accepts a node and an optional metadata tuple
It cleanly organizes the components of a compiler pass, and all... | true |
3,017,591,462 | Update _torch_docs.py to Fix torch.bernoulli() | ILCSFNO | open | [
"triaged",
"open source",
"release notes: python_frontend"
] | 1 | CONTRIBUTOR | Fixes #152095
@malfet Wondering whether to fix signature that from:
```text
@overload
def bernoulli(input: Tensor, p: _float, *, generator: Optional[Generator] = None) -> Tensor:
```
to
```text
@overload
def bernoulli(input: Tensor, p: _float, *, generator: Optional[Generator] = None, out: Optional[Tensor] = ... | true |
3,017,586,122 | Change test/inductor/test_standalone_compile to test/inductor/test_compile | zou3519 | closed | [
"Merged",
"Reverted",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 11 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152103
These are the tests for torch._inductor.compile, so I renamed the file
test_compile. This is to avoid confusion with
torch._inductor.standalone_compile, which is now a lot more standalone
than torch._inductor.compile.
cc @voz... | true |
3,017,498,662 | Segmentation fault with # FIXME: copy.deepcopy() is not defined on nn.module | cattientk | open | [
"needs reproduction",
"module: crash",
"module: nn",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
I got error with this app always crash when I ran a model
```python
def _get_clones(module, N):
# FIXME: copy.deepcopy() is not defined on nn.module
return ModuleList([copy.deepcopy(module) for i in range(N)])
```
err:
```
Thread 0x00000002089f8c80 (most recent call first):
File ".v... | true |
3,017,246,853 | linear + relu don't fuse | nairbv | open | [
"triaged",
"oncall: pt2",
"module: inductor"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
I'm not entirely sure if this is expected behavior, but I think mm + relu are supposed to fuse when using torch.compile, and it looks like it's not happening.
example code:
```
import torch
import torch.nn as nn
model = nn.Sequential(nn.Linear(128, 128), nn.ReLU()).cuda()
x = torch.randn(32,... | true |
3,017,186,194 | What is the difference between normal_tensor.storage().use_count() and viewed_tensor's? | CLiqing | closed | [] | 1 | CONTRIBUTOR | In the test2() below, why is b.storage().use_count() still 2 even when I deleted the source tensor a?
```
import torch
def test1():
print("=============== test 1 ===============")
a = torch.empty(size=(17, 32, 128, 16), dtype=torch.float16)
b = a.view(-1)
# b.storage().use_count() is 2
def test2():
... | true |
3,017,033,307 | Migrate to new Windows Arm64 runners | iremyux | open | [
"triaged",
"open source",
"ciflow/binaries",
"topic: not user facing"
] | 1 | COLLABORATOR | This PR moves the Windows Arm64 nightly jobs to the new runner image, see [arm-windows-11-image](https://github.com/actions/partner-runner-images/blob/main/images/arm-windows-11-image.md )
Fixes #151671
| true |
3,016,777,788 | Switch to standard pep517 sdist generation | zklaus | open | [
"open source",
"release notes: releng"
] | 2 | COLLABORATOR | Generate source tarball with PEP 517 conform build tools instead of the custom routine in place right now.
Closes #150461.
The current procedure for generating the source tarball consists in creation of a source tree by manual copying and pruning of source files.
This PR replaces that with a call to the standa... | true |
3,016,700,597 | When using torch to convert to oxxn model, testing the inference results with actual images shows tensor mismatch | Zhengqinze05 | open | [
"module: onnx",
"triaged",
"onnx-needs-info"
] | 2 | NONE | ### 🐛 Describe the bug
Here is my test code :
```py
import os
import torch
import torch.nn as nn
import torch
import torchvision
from torchvision.models.detection import fasterrcnn_mobilenet_v3_large_320_fpn
from torchvision.models.detection.faster_rcnn import FastRCNNPredictor
from torch.utils.data import Dataset... | true |
3,016,669,515 | [Accelerator] Add `torch.acc.set_default_device()` and `torch.acc.device_module()` | shink | closed | [
"triaged",
"open source",
"topic: not user facing"
] | 15 | CONTRIBUTOR | ### Changes
Users may want to allocate tensors to the current accelerator, but `torch.set_default_device(torch.accelerator.current_accelerator())` is too long, so `torch.accelerator.set_default_device` (or `enable_default_device`?) may be a good choice.
### Test
```python
python test/test_accelerator.py
```
... | true |
3,016,589,024 | To fix inconsistency between signature and doc on `torch.bernoulli()` | ILCSFNO | open | [
"module: distributions",
"module: docs",
"triaged",
"actionable"
] | 3 | CONTRIBUTOR | ### 📚 The doc issue
The doc of [torch.bernoulli()](https://pytorch.org/docs/stable/generated/torch.bernoulli.html#torch-bernoulli) shows its description as below:
```text
torch.bernoulli(input: Tensor, *, generator: Optional[Generator], out: Optional[Tensor]) → Tensor
Draws binary random numbers (0 or 1) from a Bern... | true |
3,016,539,613 | Work around MPSGraph issue in backward pass of nn.ReplicationPad1d/2d | xwu-498 | open | [
"triaged",
"open source",
"release notes: mps"
] | 2 | NONE | Fixes https://github.com/pytorch/pytorch/issues/135447.
When the 3rd from last dimension is 2^16 or greater, MPSGraph returns 0 for padgradient.
To work around this, we break the problematic dimension into chunks with chunk size being
no greater than 2^16 - 1.
Test case for nn.ReplicationPad1d:
```
shape ... | true |
3,016,508,665 | Add optional device index to AOTIModelPackageLoader | juliusgh | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"module: inductor",
"release notes: inductor (aoti)",
"skip-url-lint"
] | 9 | CONTRIBUTOR | This is my suggestion for resolving #152087
This PR extends the constructor of `AOTIModelPackageLoader` with an (optional) device index. The device type is still determined by `metadata_["AOTI_DEVICE_KEY"]`, but the `device_index` argument can be used to move an AOTI model package to different devices like `cuda:0`,... | true |
3,016,491,867 | [AOTInductor] Inherit Buffer if not being updated | muchulee8 | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: inductor (aoti)"
] | 8 | CONTRIBUTOR | Summary: Inherit buffer from original constants buffer if it's not being updated.
Test Plan: TBD
Differential Revision: D73571260
| true |
3,016,486,952 | [Intel GPU] Support f32 intermediate dtype, headdim size <=576 and f32 causal mask for SDPA | LuFinch | open | [
"module: cpu",
"triaged",
"module: mkldnn",
"open source",
"release notes: xpu",
"module: xpu"
] | 3 | CONTRIBUTOR | In OneDNN v3.7, SDPA has below defects:
1. The dtype of intermediate value is the same as QKV, while Pytorch uses FP32 dtype for intermediate value to make sure better accuracy.
2. Only support headdim size <= 256.
3. Don't support implict causal mask when QKV is FP32. We need to build an attention mask explicitly... | true |
3,016,388,012 | [XPU] test_tensordot_out_kernel_errors_with_autograd_xpu_float32 UT failure | CuiYifeng | closed | [
"triaged",
"module: xpu"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
New UT `test_linalg_xpu.py::TestLinalgXPU::test_tensordot_out_kernel_errors_with_autograd_xpu_float32` failed with the following error:
```
AssertionError: "the 'out' tensor was specified and requires gradients" does not match "cannot resize variables that require grad"
```
### Versions
Colle... | true |
3,016,385,956 | dynamically set tags | jijiew | open | [] | 2 | CONTRIBUTOR | Fixes ##150972
This pull request allows for dynamically set tags | true |
3,016,379,634 | Incorrect Gradient Computation in `torch.log1p` | vwrewsge | closed | [
"triage review",
"module: autograd",
"module: NaNs and Infs"
] | 2 | NONE | ### 🐛 Describe the bug
# To Reproduce
```python
import torch
def test_bug():
a = torch.tensor([-1.0, 0.5, 1.0], requires_grad=True)
l = torch.log1p(a)[a > -1].sum() # This will include only a[1] and a[2]
l.backward()
print(a.grad)
if __name__ == "__main__":
test_bug()
```
# Output
```
tensor([ ... | true |
3,016,373,776 | AOTInductor package can only be loaded on the first GPU (cuda:0) in C++ via AOTIModelPackageLoader | juliusgh | closed | [
"triaged",
"oncall: r2p",
"oncall: pt2",
"oncall: export",
"module: aotinductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Thanks for implementing the very helpful AOTInductor features in C++! In my scenario I have to load a compiled `*.pt2` package on multiple GPUs (e.g. `cuda:{0..7}`) and then run inference on all of them. AFAIK `torch::inductor::AOTIModelPackageLoader` only supports loading the package on device... | true |
3,016,198,895 | Update CPU Inductor merge rules by adding more CPP Template | leslie-fang-intel | open | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152086
**Summary**
Add more CPP Template into the CPU Inductor merge rules.
| true |
3,016,193,153 | Aborted (core dumped) in torch.fliplr | cx104906 | closed | [
"needs reproduction",
"module: crash",
"triaged",
"security",
"topic: fuzzer"
] | 2 | NONE | ### 🐛 Describe the bug
### Summary
When using torch.fliplr with invalid data, the program crashes with Aborted (core dumped).
### Reproduce
curl -L -o 001-args.pkl "https://github.com/cx104906/poc/raw/main/pytorch/id%3A000001-args.pkl"
curl -L -o 001-kwargs.pkl "https://github.com/cx104906/poc/raw/main/pytorch/id%3A... | true |
3,015,903,788 | Revert "Add a warning when a tensor with requires_grad=True is converted to a scalar (#143261)" | PaulZhang12 | closed | [
"ci-no-td"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
This reverts commit 515b45e5693dbf9dd58d8472806cbe5f49e43074.
Reverted https://github.com/pytorch/pytorch/pull/143261 on behalf of https://github.com/clee2000 due to failing internal tests D72135661 ([comment](https://github.... | true |
3,015,860,789 | DISABLED test_captured_scale_float16_cuda_float16 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_captured_scale_float16_cuda_float16&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41048885024).
Over the pas... | true |
3,015,860,785 | DISABLED test_builtin_score_mods_float32_score_mod4_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_float32_score_mod4_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41051796108)... | true |
3,015,740,899 | Wrong formula for CosineAnnealingLR | bbbbbbbbba | open | [
"module: docs",
"module: optimizer",
"triaged",
"actionable"
] | 3 | NONE | ### 📚 The doc issue
https://github.com/pytorch/pytorch/blob/1eba9b3aa3c43f86f4a2c807ac8e12c4a7767340/torch/optim/lr_scheduler.py#L1054-L1056
This formula does not incorporate the learning rate of the last step, is the same as the "If the learning rate is set solely by this scheduler" formula below, and does not seem... | true |
3,015,732,432 | [BE] Replace `std::runtime_error` with `TORCH_CHECK` [2/N] | shink | open | [
"open source",
"release notes: quantization"
] | 2 | CONTRIBUTOR | Part of: #148114
Related commits:
- #151880
cc: @albanD | true |
3,015,711,694 | Adding fbgemm to allowlist | jimone1 | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx"
] | 8 | CONTRIBUTOR | Adding `torch.ops.fbgemm` to GraphPickler's allowlist. Otherwise, the fx graph module containing `fbgemm` node will return "Unable to pickle non-standard op" error.
The validation is done on the model and the difference appears only on the graph name not the node.
cc @aorenste @ezyang @SherlockNoMad @EikanWang @j... | true |
3,015,677,260 | Adding torch.ops.fbgemm to whitelist in GraphPickler | jimone1 | closed | [
"release notes: fx",
"fx"
] | 2 | CONTRIBUTOR | As title, this is tested by running on the model see D73553912 as an example. The only difference is the module name.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
3,015,657,302 | NCCL Error 1: unhandled CUDA error during DistributedDataParallel (DDP) training with NVIDIA GeForce RTX 5090 | kingchou007 | closed | [
"module: build"
] | 3 | NONE | ### 🐛 Describe the bug
I'm encountering an error while running a distributed training job using DistributedDataParallel (DDP) on a system with an NVIDIA GeForce RTX 5090 GPU. The job fails with the following error:
```
RuntimeError: NCCL Error 1: unhandled cuda error
The issue seems to be related to NCCL (NVIDIA Col... | true |
3,015,585,361 | [cuDNN][SDPA] Fix head-dim 256 condition for SM 10.0 | eqy | closed | [
"module: cudnn",
"module: cuda",
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"topic: not user facing",
"module: sdpa"
] | 9 | COLLABORATOR | turns out the backward is not supported yet, whoops
cc @csarofeen @ptrblck @xwang233 @msaroufim @jerryzh168 | true |
3,015,573,050 | [vec128] Fix fmsub NEON defintion | malfet | closed | [
"module: cpu",
"Merged",
"ciflow/trunk",
"topic: bug fixes",
"release notes: cpu (aarch64)"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152075
As reported in https://github.com/pytorch/pytorch/issues/149292, according to manual, `vfmsq_f32` implements `c - a * b` rather than `a * b - c`, so it's call must be prefixed with `vnegq_f32`
Also, adjust the tests to u... | true |
3,015,553,258 | Cause `ceil_div` to accept values of differing types an upcast to the larger type | r-barnes | open | [
"fb-exported"
] | 3 | CONTRIBUTOR | Test Plan: Sandcastle
Reviewed By: swolchok
Differential Revision: D73550062
| true |
3,015,545,729 | [export][function schema] support exporting hop with function schema argument | ydwu4 | closed | [
"Merged",
"fx",
"ciflow/inductor",
"release notes: export"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151067
* #152248
* #152247
* #152246
* #152245
* #152244
* __->__ #152073
* #152072
We need to make function schema proxyable to trace a the auto_functionalized hop that takes function schema as inputs. The implementation basically follow... | true |
3,015,545,632 | [export][be] better type annotation for lift_constants_pass | ydwu4 | closed | [
"Merged",
"ciflow/inductor",
"release notes: export"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #151067
* #152248
* #152247
* #152246
* #152245
* #152244
* #152073
* __->__ #152072
| true |
3,015,508,051 | [inductor][BE] Clean up use_mixed_mm and mixed_mm_choice usage inside pytorch | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152071
Differential Revision: [D73551912](https://our.internmc.facebook.com/intern/diff/D73551912/)
Decided to leave the mixed_mm tests alive.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuh... | true |
3,015,481,487 | failing to read rames even toughh the cam is connected | zouaoui21 | closed | [] | 3 | NONE | ### 🐛 Describe the bug
when i run the code , the url is correct , and it connects to the camera but never reads the frames
for this code :
import cv2
rtsp_url = "..................................."
video = cv2.VideoCapture(rtsp_url)
video.set(cv2.CAP_PROP_BUFFERSIZE, 3) # Increase buffer to prevent frame d... | true |
3,015,472,592 | [Proposal] Drop legacy CUDA support to slim down the wheels | NevermindNilas | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda",
"release notes: build"
] | 24 | CONTRIBUTOR | Proposal of dropping legacy CUDA support to slim down the Windows wheels.
With the latest release of 2.7.0 and the new Blackwell support we've seen yet another rise in size to the wheel, going from ~2.5GB with Pytorch 2.6.0 all the way to ~3.1GB with pytorch 2.7.0 CUDA 12.8 on Python 3.12 and ~3.3GB with Python 3.13... | true |
3,015,451,478 | Compiling attention (SDPA) with nested tensors fails when using DDP | mahyarkoy | open | [
"oncall: distributed",
"triaged",
"module: nestedtensor",
"oncall: pt2",
"module: sdpa"
] | 2 | NONE | ### 🐛 Describe the bug
When running the script below:
1. Compiling on single gpu no DDP works
2. No compiling using DDP works
3. But compiling using DDP breaks!
Using dense tensors as input (n) works fine in all cases.
To reproduce, run the script below with:
```
torchrun --standalone --nnodes=1 --nproc_per_node=2 ... | true |
3,015,447,159 | [AOTI] aoti_compile_and_package + use_runtime_constant_folding gives "Error: CUDA driver error: file not found" | henrylhtsang | closed | [
"oncall: pt2",
"oncall: export",
"module: aotinductor"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Hi, noticed a problem when using runtime constant folding with the aoti_compile_and_package API. Old API doesn't seem to have this problem, see the commented lines.
repro:
```
import torch
import torch._inductor.config
import torch.nn as nn
torch._inductor.config.aot_inductor.use_runtime_cons... | true |
3,015,442,422 | [Graph Partition] fix extra reference in runner.partitions to cudagraphify functions | BoyuanFeng | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | When CompiledFxGraph is deallocated, its cudagraphifed fn (i.e., `current_callable`) is expected to also be deallocated.
Without graph partition, this is true since the cudagraphified fn is only refered by compiled_fx_graph.current_callable.
However, with graph partition, runner.partitions hold cudagraphified fns w... | true |
3,015,427,295 | More logs to show why fx graph cache isn't hit / created? | henrylhtsang | closed | [
"triaged",
"oncall: pt2"
] | 2 | CONTRIBUTOR | Hi, when working on https://github.com/pytorch/pytorch/blob/main/torch/_inductor/compile_fx.py#L732-L990, it is very hard to tell why sometimes fx graph cache isn't hit, even with TORCH_LOGS="+inductor".
In my case, tlparse provides a bit more info, like
![Image](https://github.com/user-attachments/assets/cbac7402-7a... | true |
3,015,377,615 | [MPS] Adjust test_sum_dtypes so it can run on MPS. | dcci | closed | [
"Merged",
"Reverted",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor",
"ci-no-td"
] | 8 | MEMBER | cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,015,377,419 | [Bug] Memory leak in autograd with custom CUDA operations | khlaifiabilel | open | [
"needs reproduction",
"module: cpp-extensions",
"module: autograd",
"module: memory usage",
"triaged"
] | 1 | NONE | ### 🐛 Describe the bug
## 🐛 Bug
<!-- A clear and concise description of the bug -->
When using custom CUDA operations with PyTorch's autograd system, there appears to be a memory leak during backward passes in long training loops. The memory usage gradually increases even when no new tensors should be created or re... | true |
3,015,374,952 | [inductor][invoke_subgraph] Run joint graph passes for inference | anijain2305 | 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):
* #152357
* #152207
* __->__ #152062
* #151961
* #151957
* #151477
* #151633
* #151409
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchul... | true |
3,015,331,099 | Add graph inputs/outputs to comm overlap pass signature | wconstab | closed | [
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146558
* #146562
* __->__ #152061
* #152060
* #146561
To support peak-memory-aware passes, we can pass graph inputs/outputs
to these passes so they can compute a memory timeline.
This PR should be a functional no-op for existing passes
cc... | true |
3,015,330,984 | Add 'step' counter to visualize_overlap log | wconstab | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146558
* #146562
* #146561
* __->__ #152060
Example of log after the change:
```
[rank0]:V0227 15:07:20.704000 1594243 torch/_inductor/comms.py:621] [0/0] [__overlap] ==== Visualize overlap after reordering pass <function group_copy_collec... | true |
3,015,326,104 | DISABLED test_comprehensive_linalg_pinv_singular_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_linalg_pinv_singular_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41035465... | true |
3,015,326,018 | DISABLED test_comprehensive_floor_cuda_float16 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 29 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_floor_cuda_float16&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41036342325).
Over the pa... | true |
3,015,325,956 | DISABLED test_comprehensive_bitwise_right_shift_cuda_int32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 27 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_bitwise_right_shift_cuda_int32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41036342342).
... | true |
3,015,325,955 | DISABLED test_comprehensive_native_layer_norm_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_native_layer_norm_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41036342342).
... | true |
3,015,325,421 | Test | svekars | open | [
"topic: not user facing"
] | 2 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
| true |
3,015,324,600 | DISABLED test_comprehensive_sort_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 1 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_sort_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41036519831).
Over the past 3... | true |
3,015,324,527 | DISABLED test_comprehensive_nn_functional_max_pool3d_cuda_float32 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 3 | NONE | Platforms: linux, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_nn_functional_max_pool3d_cuda_float32&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/4103... | true |
3,015,324,465 | DISABLED test_index_multiple_cuda (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_index_multiple_cuda&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41035547301).
Over the past 3 hours, it ha... | true |
3,015,324,396 | DISABLED test_builtin_score_mods_float32_score_mod7_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_float32_score_mod7_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41032594592)... | true |
3,015,324,338 | DISABLED test_builtin_score_mods_float32_score_mod2_cuda_float32 (__main__.TestFlexAttentionCUDA) | pytorch-bot[bot] | closed | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_builtin_score_mods_float32_score_mod2_cuda_float32&suite=TestFlexAttentionCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41036274598)... | true |
3,015,323,533 | unbreak fb:operator_benchmark_test | sharpobject | open | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing"
] | 7 | NONE | Summary: unbreak fb:operator_benchmark_test
Test Plan: works on my machine
Differential Revision: D73540912
| true |
3,015,292,815 | [Graph Partition] Pass all cudagraph tree tests | BoyuanFeng | open | [
"oncall: distributed",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,015,258,285 | [Build] fix functorch install dir | stefantalpalaru | closed | [
"triaged",
"open source",
"topic: not user facing"
] | 4 | NONE | null | true |
3,015,253,927 | Pin theme to a branch | svekars | closed | [
"module: docs",
"Merged",
"ciflow/trunk",
"topic: docs",
"topic: not user facing"
] | 3 | CONTRIBUTOR | cc @sekyondaMeta @AlannaBurke | true |
3,015,240,302 | [DTensor] make test_dtensor_ops report dtensor_args | wconstab | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"merging"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #149764
* __->__ #152045
Before:
Does not report DTensor args, and you can't tell which combination of
sharding/replication is used for that particular iteration
```
RuntimeError: failed to run: torch.flatten, with (*[tensor([[[-6.107... | true |
3,015,240,169 | Move verbose warning to warning_once | wconstab | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
It was printing 1000s of lines for me..
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @d4l3k | true |
3,015,219,633 | [DO NOT LAND] Use cudaGetDevice in OSSProxyExecutor | yiming0416 | closed | [
"fb-exported",
"ciflow/inductor",
"release notes: inductor (aoti)"
] | 10 | CONTRIBUTOR | Summary: I am trying to use `cudaGetDevice()` in `oss_proxy_executor.cpp` and guard it under the macro `USE_CUDA`. However, seems like the code under `USE_CUDA` was never invoked even if I built PyTorch on a GPU machine. The `device_idx` remains -1, ideally it should change to `0` after `cudaGetDevice()` is called.
... | true |
3,015,211,547 | distrubuted: false positive Grad strides vs Bucket strides warning | nikitaved | open | [
"oncall: distributed"
] | 1 | COLLABORATOR | ### 🐛 Describe the bug
I am training a model on a single node with 4 GPUs using the HF [Accelerate](https://github.com/huggingface/accelerate) through SLURM. And this is the warning message I get:
```
/my_cluster_folder/site-packages/torch/autograd/graph.py:824: UserWarning: Grad strides do not match bucket view str... | true |
3,015,170,919 | [map] always turn on dynamo for map | ydwu4 | open | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Summary:
X-link: https://github.com/pytorch/executorch/pull/10409
Reland D72896450
Make map consistent with other control flow ops. After the change, map is able to support accessing closures in the map fn.
Test Plan: See existing tests.
Reviewed By: zou3519
Differential Revision: D73138427
cc @voznesenskym @p... | true |
3,015,145,214 | Improve stable library apis per Scott's feedback | janeyx99 | closed | [
"Merged",
"ciflow/trunk",
"ciflow/inductor",
"release notes: inductor (aoti)"
] | 6 | CONTRIBUTOR | Following 3 suggestions:
1. inline at::Tensor arg
2. use uniq ptr of array vs std::vector
3. document the `std::optional<S>()` case
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #152040
| true |
3,015,136,256 | Fix GuardOnDataDependentSymNode in the normalize operator | henryoier | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 17 | CONTRIBUTOR | Test Plan:
Dumped the local net torch.package to local
Ran
```
buck2 run scripts/shengqin:test_model_export -- /tmp/mtia_local_torch_package {\"local\":null}
```
succeeded
Reviewed By: hongyang-zhao
Differential Revision: D73405271
| true |
3,015,135,494 | [AOTInductor] Inherit Buffer if not being updated | 22quinn | closed | [
"fb-exported",
"ciflow/trunk",
"ciflow/inductor",
"release notes: inductor (aoti)"
] | 6 | CONTRIBUTOR | Summary: Inherit buffer from original constants buffer if it's not being updated.
Test Plan: TBD
@diff-train-skip-merge
| true |
3,015,131,954 | Re-enable FakeTensor caching for SymInts | aorenste | closed | [
"fb-exported",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Summary:
This backs out D60320595 which itself turned off FakeTensor caching when a SymInt was present.
Tests seem to pass so I'm assuming some dynamic shape work fixed what was breaking previously.
Test Plan: Reran the tests listed in T196779132 and they seem to pass.
Differential Revision: D73532965
cc @voznes... | true |
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