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 |
|---|---|---|---|---|---|---|---|---|
2,836,267,931 | [inductor][idea] Defer realize/inline decisions | jansel | open | [
"triaged",
"enhancement",
"oncall: pt2",
"module: inductor"
] | 0 | CONTRIBUTOR | ## Background
Currently, inductor lowering has the concept of a realized versus unrealized tensor. Suppose you have:
```py
def example(a, b):
x = a + b
y = torch.sin(x)
```
`x` will get mapped to:
```py
def inner_fn_x(index):
tmp0 = ops.load("a", index[0])
tmp1 = ops.load("b", index[0])
tmp2 = ops.add(tmp... | true |
2,836,257,174 | Dynamo should consider tensor mutation when reconstructing generator | guilhermeleobas | open | [
"triaged",
"oncall: pt2",
"module: dynamo",
"dynamo-side-effects"
] | 0 | COLLABORATOR | In PR #145223, we added support for reconstructing a generator only when no side effects are present. However, we do not currently account for tensor mutations. This issue tracks the missing support for detecting tensor mutations.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @... | true |
2,836,236,891 | [BE]: Inline special functions for MPS | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | These header functions should be inlined for consistency and to avoid translation unit / symbol issues. | true |
2,836,225,749 | [inductor] Improve type annotations in _inductor/pattern_matcher.py | rec | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: fx",
"topic: not user facing",
"fx",
"module: inductor",
"ciflow/inductor",
"suppress-api-compatibility-check",
"suppress-bc-linter"
] | 5 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146626
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv @voznesenskym @penguinwu @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @desertfire @chauhang @aakh... | true |
2,836,213,182 | Move capture_provenance to make_node_impl | angelayi | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 15 | CONTRIBUTOR | Previously we were only logging `make_user_impl` implementations, which only gets triggered for operations done on python SymInts, not cpp SymInts. Instead `make_node_impl` will get triggered for both python and cpp SymInt operations.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,836,167,700 | [Flex Attention] Cannot determine truth value of Relational | alexdremov | closed | [
"triaged",
"oncall: pt2",
"module: pt2-dispatcher",
"module: flex attention"
] | 2 | CONTRIBUTOR | ### 🐛 Describe the bug
Flex attention autotune causes `Cannot determine truth value of Relational`
To reproduce, run this benchmark: https://gist.github.com/alexdremov/0f143fd30168588b13ed07a2363c7cb4
### Versions
PyTorch version: 2.7.0.dev20250206+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROC... | true |
2,836,139,920 | bug fix: ensure 4d input in _scaled_dot_product_attention_math_mps | hellopahe | closed | [
"triaged",
"open source",
"Merged",
"topic: bug fixes",
"release notes: mps",
"ciflow/mps"
] | 7 | CONTRIBUTOR | This pr addresses the issue in the MPS backend for `_scaled_dot_product_attention_math_mps` where a 3d input like (num_heads, seq_len, query_dim) cannot be automatically treated as (1, num_heads, seq_len, query_dim), which can be inferred on cpu or cuda, which can be circumvented by adding a util function to ensure a 4... | true |
2,836,128,108 | Fix inductor non-stable argsort/sort test | nicholasw-gc | open | [
"triaged",
"open source",
"ciflow/trunk",
"topic: not user facing",
"module: inductor"
] | 15 | CONTRIBUTOR | - Prevent the inductor test for argsort/sort from wrongly failing when the argsort/sort output with stable=False differs from pytorch but is still a valid argsort output.
- Add functionality to allow alternative assert_equal functions in inductor tests for future cases.
cc @voznesenskym @penguinwu @EikanWang @jgong... | true |
2,836,119,518 | aten op full_like has kwarg that prepare_pt2e does not expect | Erik-Lundell | closed | [
"oncall: quantization"
] | 1 | NONE | ### 🐛 Describe the bug
When quantizing a torch.full_like() op, it gets stuck when calling prepare_pt2e in ```_maybe_insert_input_observers_for_node```. There is an assert that checks aten ops (except a few) don't have kwargs, but aten.full_like does. I therefore get the following error message:
```
# Clone h... | true |
2,836,087,855 | Enable qint8 and quint8 add for AArch64 using ACL directly | davsva01 | closed | [
"module: cpu",
"triaged",
"open source",
"release notes: quantization",
"release notes: releng",
"arm priority"
] | 5 | NONE | This enables qint8 and quint8 add for AArch64 through Arm Compute Library (ACL) directly.
It’s based on changes in PR #145942 which enables the use of ACL directly in ATen.
Relative performance improvement using OMP_NUM_THREADS=1 is ~15x, using OMP_NUM_THREADS=32 it’s ~5.4x.
Script to benchmark quantised add perfo... | true |
2,836,067,606 | [mps] Remove a stale comment. | dcci | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: mps",
"ciflow/mps",
"module: inductor"
] | 6 | MEMBER | The implementation of the function was moved to a shader, but the comment was left there.
cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amja... | true |
2,836,035,338 | Fix for special.zeta nan handling - follow-up PR #138653 | vladimirrotariu | open | [
"triaged",
"module: special"
] | 0 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Continuing [PR #138653](https://github.com/pytorch/pytorch/pull/138653).
I hereby attach the suggestion of Albert Steppi (@steppi):
Now that we have this background out of the way. I think my preference in SciPy would be to change zeta(x, q) to be nan and to codify this as a ... | true |
2,835,967,169 | Generate test reports for pytest when option is given | Flamefire | closed | [
"triaged",
"open source",
"topic: not user facing"
] | 2 | COLLABORATOR | The argument needs to be appended when test reports should be generated. `IS_CI` is not necessarily set, so rather check `TEST_SAVE_XML` instead as in other places where test reports are conditionally enabled.
See also https://github.com/pytorch/pytorch/issues/126523 | true |
2,835,945,976 | [don't merge] test baseline | xuhancn | closed | [
"open source",
"topic: not user facing",
"ciflow/binaries_wheel",
"ciflow/xpu"
] | 7 | COLLABORATOR | Fixes #ISSUE_NUMBER
| true |
2,835,945,905 | [BE][Ez]: Enable ruff rule banning print in assert | Skylion007 | closed | [
"triaged",
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 3 | COLLABORATOR | Enables a few ruff rules
* Ban print statements within asserts (likely bugs)
* ~Use string for Decimal literal to prevent loss of precision~
* ~Do not use default args for __post__init__ in dataclasses, they likely were meant to go into the factory method, the __init__, or somewhere else. The default values are use... | true |
2,835,921,583 | [CD] Add python 3.13t build for xpu | chuanqi129 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel"
] | 9 | COLLABORATOR | Fixes #146451
| true |
2,835,899,790 | Description of `input` in `torch.addbmm()` should be a `Parameter` | ILCSFNO | closed | [
"module: docs",
"triaged",
"actionable",
"topic: docs",
"module: python frontend"
] | 1 | CONTRIBUTOR | ### 📚 The doc issue
The doc of [`torch.addbmm()`](https://pytorch.org/docs/stable/generated/torch.addbmm.html#torch-addbmm) shows its `Parameters` and `Kw Arguments` as below:
https://github.com/pytorch/pytorch/blob/8a4dd763b87478d01ae327ec439632212b8a3357/torch/_torch_docs.py#L409-L417
But for `input`, which is no... | true |
2,835,860,360 | [WIP] BaseSubclass | IvanKobzarev | open | [
"Stale"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146612
| true |
2,835,854,469 | Fix ignore description in `torch.addbmm()`, `torch.addmm()`, `torch.addmv()` and `torch.baddbmm()` | ILCSFNO | closed | [
"module: docs",
"triaged",
"actionable",
"module: python frontend"
] | 0 | CONTRIBUTOR | ### 📚 The doc issue
Seen from #146399, I notice some similar situations in [`torch.addbmm()`](https://pytorch.org/docs/stable/generated/torch.addbmm.html#torch-addbmm), [`torch.addmm()`](https://pytorch.org/docs/stable/generated/torch.addmm.html#torch-addmm), [`torch.addmv()`](https://pytorch.org/docs/stable/generate... | true |
2,835,853,813 | Remove some NOLINT | cyyever | closed | [
"oncall: distributed",
"open source",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | COLLABORATOR | Fixes #ISSUE_NUMBER
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,835,852,006 | [BE][Ez]: Enable some additional pylint ruff warnings | Skylion007 | closed | [
"open source",
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 6 | COLLABORATOR | Some additional code hardening with some pylint warnings in ruff that usually indicate bugs. All code currently conforms nicely to them, but this will ensure these errors can be detected statically before running / creating tests.
The follow rules:
* Ban walrus operators where they would have no effect over regula... | true |
2,835,728,588 | Gh/lucasllc/1/head | LucasLLC | closed | [
"oncall: distributed"
] | 1 | CONTRIBUTOR | Seeing how many errors I get when I delete this function
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,835,629,358 | [ROCm][Windows] Remove external linkage from an anonymous namespace | m-gallus | closed | [
"oncall: jit",
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"release notes: jit",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Fixes a clang-cl compiler error related to attempt to export a symbol that doesn't have any external linkage, since its declared within a local anonymous namespace.
cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naro... | true |
2,835,612,881 | [ROCm][Windows] Fix unrecognized _BitScanReverse intrinsic | m-gallus | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Since PyTorch with ROCm on Windows is built with clang-cl and not MSVC, the intrinsics used are different and hence an attempt to compile with `_BitScanReverse` fails. However, a call to `__builtin_clz` which follows in the subsequent preprocessor branch is correctly recognized by the clang-cl compiler.
cc @jeffdaily ... | true |
2,835,594,615 | [ROCm][Windows] Fix isnan integer overload errors on MS STL | m-gallus | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Microsoft's STL has a problem with integer overloads of std::fpclassify used by std::isnan and std::isinf. These functions need a cast to double to function correctly. Otherwise, the call fails with "ambiguous call to overloaded function" error.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @... | true |
2,835,576,394 | [Profiler] Enable CUPTI teardown to reduce profiler overhead | mgmtea | open | [
"triaged",
"open source",
"oncall: profiler",
"topic: not user facing"
] | 11 | NONE | The problem is that the profiler slowed down
training by roughly 10-20% even after completion
because cuptiFinalize was not called in Kineto due to TEARDOWN_CUPTI=0. Disabling CUPTI teardown was a workaround for crashes which occured when CUDA graphs were used. This issue was fixed in CUDA 12.6. Also there is no poin... | true |
2,835,570,712 | Regression: Multiple OpenMP runtimes linked to libtorch_cpu.so | vinithakv | closed | [
"module: performance",
"module: build",
"triaged",
"module: POWER"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
Hi,
Running the granite model on ppc64le Linux machine with latest PyTorch built from sources, shows a regression in performance.
Testing with OpenBLAS 3.29.
The libtorch_cpu.so seems to have picked up libomp.so and libgomp.so as dependencies, when compared to PyTorch-2.5.
With PyTorch 2.6 mai... | true |
2,835,448,596 | DISABLED test_tmp_not_defined_issue3_dynamic_shapes_cpu (__main__.DynamicShapesCpuTests) | pytorch-bot[bot] | closed | [
"module: rocm",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_tmp_not_defined_issue3_dynamic_shapes_cpu&suite=DynamicShapesCpuTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/36770936980).
Over th... | true |
2,835,251,733 | Enabling efficient model-level redistribution between FSPD-TP | SalmanMohammadi | open | [
"oncall: distributed"
] | 9 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
The age of RL-based LLM finetuning is upon is. For many RL training paradigms, there exists a step where a (large) model is used for inference (i.e. autoregressive sampling under `no_grad`), followed by a training step with the same model. After this training step, the updated ... | true |
2,835,243,849 | Fixed a typo in dataset.py | Zhou32 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: dataloader",
"topic: not user facing"
] | 7 | CONTRIBUTOR | Changed word 'Mult' to 'Multi'. | true |
2,835,243,688 | [Windows][ROCm] Fix c10 hip tests | m-gallus | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | CONTRIBUTOR | - Solves a problem related to .hip source files being ignored by the build system when HIP language is not enabled in CMake.
- Also ensures that the test executables link to an appropriate CRT Runtime Library and hence have access to all the necessary symbols. Previously, there were many problems related to linkage er... | true |
2,835,230,255 | [t.compile][Functools] Cache decorator support for dynamo | mieshkiwrk | open | [
"high priority",
"triaged",
"actionable",
"module: correctness (silent)",
"oncall: pt2",
"module: dynamo",
"dynamo-triage-jan2025"
] | 2 | NONE | ### 🐛 Describe the bug
Given below example, `eager` handles cached function as expected, `t.compile` treats it normally, set guards for z and recompiles with each new call.
I haven't found any information about supporting cache in case of dynamo, with [this commit ](https://github.com/pytorch/pytorch/commit/53fc921ce... | true |
2,835,220,077 | [ARM] Fix bug in _ref_test_helper in test_ops and fix failing test on Aarch64 | robert-hardwick | closed | [
"triaged",
"open source",
"module: arm",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"arm priority"
] | 7 | COLLABORATOR | We have a failing unit test on Aarch64
```
Exception: Caused by reference input at index 34: SampleInput(input=Tensor[size=(5, 5, 4), device="cpu", dtype=torch.complex64, contiguous=False], args=(), kwargs={}, broadcasts_input=False, name='')
To execute this test, run the following from the base repo dir:
P... | true |
2,835,200,186 | separate f16 vectorized class from bf16 | Ryo-not-rio | closed | [
"module: cpu",
"triaged",
"open source",
"module: arm",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"arm priority"
] | 16 | COLLABORATOR | Separating the f16 vectorized class into a different file from the bf16 vectorized class in order to be able to add a new bf16 SVE vectorized class in https://github.com/pytorch/pytorch/pull/143666. This is required as we would need to exclude the current bf16 class in order to use the sve bf16 class but still include ... | true |
2,835,174,041 | skip test_torch_dynamo_codegen_pow if CPU backend is not cpp | GeorgeWigley | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 12 | CONTRIBUTOR | The test asserts that `aten.pow` is not present in the generated kernel code. When using a CPU backend other than cpp, the kernel contains comments referencing the aten ops that produced the kernel in this case `aten.pow`.
This PR skips that test case if the CPU backend is not cpp.
cc @voznesenskym @penguinwu @E... | true |
2,835,134,343 | torch.library.infer_schema should support list[...] in addition to typing.List[...] | lw | closed | [] | 2 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
Since Python 3.9, using `typing.List` (and all other types of that kind) is deprecated and the built-in `list` type should just be used instead. See https://docs.python.org/3/library/stdtypes.html#types-genericalias and https://peps.python.org/pep-0585/.
When using Python 3.11... | true |
2,835,127,166 | [NOT FOR LANDING] experimental NVSHMEM integration | yifuwang | open | [
"oncall: distributed",
"open source",
"release notes: distributed (c10d)",
"no-stale"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146593
* #146592
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,835,127,000 | clang-format CUDASymmetricMemory.cu | yifuwang | open | [
"oncall: distributed",
"open source",
"Stale",
"release notes: distributed (c10d)"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146593
* __->__ #146592
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,835,097,224 | Unable to export a large model to ONNX (exceeds 2GB limit) with custom attention layer | david-666-maker | closed | [
"module: onnx",
"triaged"
] | 5 | NONE | ### 🐛 Describe the bug
I’m encountering an issue while exporting a large text-encoder model to ONNX. The model is fairly large (over 2 GiB when serialized) and triggers the following error:
`RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file mus... | true |
2,834,991,057 | Signature should be extended for `torch.hamming_window()` | ILCSFNO | open | [
"triaged",
"module: python frontend"
] | 4 | CONTRIBUTOR | ### 🐛 Describe the bug
Seen from #145371, I notice some similar situations in [`torch.hamming_window()`](https://pytorch.org/docs/stable/generated/torch.hamming_window.html):
https://github.com/pytorch/pytorch/blob/4a545eb85d6ba06079787a83f8ab1a8c8f67c76f/torch/_torch_docs.py#L12380-L12381
### Minified Repro
```pyt... | true |
2,834,937,123 | [DDP] Use NCCL allocated memory for gradient bucket | kwen2501 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)",
"release notes: distributed (ddp)"
] | 20 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146589
So that NVLink SHARP comes with zero-copy on H100+ platforms, for DDP applications.
Less SM usage, less memory contention between NCCL kernel and compute kernels.
Added env `DDP_DISABLE_COMM_MEM` as a back-out option:
``... | true |
2,834,926,688 | [METAL] inline bfloat min/max | Isalia20 | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 7 | COLLABORATOR | After a recent commit 36c6e09528a7e071edecde083254da70cba26c95 , building from source with `python setup.py develop` leads to an error due to multiple symbols for min/max:
```
FAILED: caffe2/aten/src/ATen/kernels_bfloat.metallib /Users/Irakli_Salia/Desktop/pytorch/build/caffe2/aten/src/ATen/kernels_bfloat.metallib
... | true |
2,834,906,851 | [Dynamo] Allow dynamo to handle `str.xxx()` | shink | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo"
] | 19 | CONTRIBUTOR |
Fixes #146350
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,834,850,314 | CI related issues | swgu98 | closed | [
"module: ci",
"triaged"
] | 2 | NONE | I would like to ask if PyTorch's CI has a rerun mechanism, for example, if a workflow fails to run unexpectedly, the developer needs to rerun it manually.
Is there an exemption mechanism, for example, if a workflow fails, but there is no time to wait or it fails unexpectedly, can it be merged directly?
cc @seemethere... | true |
2,834,821,629 | Create aa | swgu98 | closed | [
"open source",
"topic: not user facing"
] | 12 | NONE | Fixes #ISSUE_NUMBER
| true |
2,834,805,789 | Create aa.yml | swgu98 | closed | [
"open source",
"topic: not user facing"
] | 1 | NONE | Fixes #ISSUE_NUMBER
| true |
2,834,790,185 | [symbolic shapes] Log symnode id | angelayi | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | We want to log the symnode id which will help us with provenance tracking between expressions created.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,834,773,750 | [Partitioner] Reduce time consuming of partitions merger | lingzhiz1998 | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: fx",
"topic: not user facing",
"fx"
] | 19 | CONTRIBUTOR | This patch optimize maybe_merge_partition func through 3-ways:
Remove unnecessary copy https://github.com/pytorch/pytorch/blob/main/torch/fx/passes/infra/partitioner.py#L99. The number of copied nodes is large if we can merge all of the nodes of graph into one partition.
Record users of each partition to avoid dupl... | true |
2,834,771,925 | Clarify that compile(module) only affects the forward method | zeshengzong | open | [
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 6 | CONTRIBUTOR | Fixes #141616
## Changes
- Add `Note` to Clarify how compile works with `nn.Module`
- Optimize plain url address with clickable description
## Test Result
### Before
![image](https://github.com/user-attachments/as... | true |
2,834,767,288 | [Partitioner] Remove unnecessary upstream nodes in dependency viewer | lingzhiz1998 | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: fx",
"topic: not user facing",
"fx",
"keep-going"
] | 16 | CONTRIBUTOR | We iterate upstream nodes to update partition map. But actually did nothing due to we iterate nodes with reversed topological order https://github.com/pytorch/pytorch/pull/136608/files#diff-f2f9dd3903fd99955732eb694941fea0cb7301a58d59554787f3311d417e5615L193 so that there exists no upstream nodes in assignment. Remove ... | true |
2,834,751,082 | Pytorch model (.pth format) not loading in KServe environment | VidhyaPandi | open | [
"needs reproduction",
"module: serialization",
"triaged"
] | 2 | NONE | ### 🐛 Describe the bug
I am performing binary classification on the Titanic dataset using a deep neural network. Here is the model-preprocessing and training code.
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from collections import Counter
from sklearn.utils import sh... | true |
2,834,727,889 | add `torch.float4_e2m1fn_x2` to PyTorch | vkuzo | closed | [
"release notes: quantization"
] | 4 | CONTRIBUTOR | Summary:
Adds the `torch.float4_e2m1fn_x2` dtype to PyTorch, as detailed in
https://github.com/pytorch/pytorch/issues/146414 . Please see the issue for a detailed definition of the format.
Note that I decided to keep the casts out of this to significantly simplify the code, as defining casting between packed a... | true |
2,834,691,963 | Clean up op BC check list | houseroad | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 12 | MEMBER | Summary: Remove the expired ones
Test Plan: ci
Differential Revision: D69226556
| true |
2,834,690,487 | Torch Dynamo Export Failed on RetinaNet from Torchvison | YixuanSeanZhou | open | [
"oncall: pt2",
"export-triaged",
"oncall: export"
] | 1 | NONE | ### 🐛 Describe the bug
Torch Dynamo Export Failed.
```python
import torch
import torchvision
from torch._export import capture_pre_autograd_graph
m = torchvision.models.detection.retinanet_resnet50_fpn(weights=torchvision.models.detection.RetinaNet_ResNet50_FPN_Weights.DEFAULT).eval()
capture_pre_autograd_grap... | true |
2,834,635,373 | How to pip3 torch==2.1.0.dev20230822+cu118 | minhphi1712 | closed | [
"module: binaries",
"triaged"
] | 1 | NONE |
> I’ve tried installing this specific version multiple times, but the issue keeps occurring.
pip3 install torch==2.1.0.dev20230822+cu118
```
ERROR: Could not find a version that satisfies the requirement torch==2.1.0.dev20230822+cu118 (from versions: 1.13.0, 1.13.1, 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2... | true |
2,834,630,334 | [ROCm][TunableOp] Close offline tuning results file when offline tuning is disabled. | naromero77amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 9 | COLLABORATOR | This PR is to fix UT breakage that has been reported internally and is considered high priority. When `tunable.record_untuned_enable(False)` is invoked, we flush the results of the untuned gemm file.
Offline tuning I/O currently doesn't have a set untuned results filename member function or untuned results write to ... | true |
2,834,622,398 | add python root bin to windows load path. | xuhancn | closed | [
"module: windows",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel",
"intel"
] | 28 | COLLABORATOR | This PR is extend python root bin path to dll load list.
It makes PyTorch robust and compatible to more dependency libraries, such as `intel-pti`.
cc @peterjc123 @mszhanyi @skyline75489 @nbcsm @iremyux @Blackhex @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
2,834,615,137 | RuntimeError: PyTorch is not linked with support for new_one devices | xiangxinhello | closed | [
"triaged",
"module: PrivateUse1"
] | 8 | NONE | ### 🐛 Describe the bug
```python
import torch
import pdb
class _OpenRegNewOne:
pass
torch.utils.rename_privateuse1_backend("new_one")
torch._register_device_module('new_one', _OpenRegNewOne())
unsupported_dtype = [torch.quint8, torch.quint4x2, torch.quint2x4, torch.qint32, torch.qint8]
torch.utils.generate_meth... | true |
2,834,554,283 | [Dynamo][autograd.Function] Relax backward speculation strict mode a bit | yanboliang | closed | [
"Merged",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146742
* #146741
* __->__ #146571
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,834,547,926 | inconsistency in geometric_ on CPU and GPU | alionapi | open | [
"triaged",
"module: edge cases"
] | 0 | NONE | ### 🐛 Describe the bug
Inconsistency in `geometric_` on CPU and GPU
```
import torch
self = torch.tensor([[[[float('inf')]]]], dtype=torch.float16)
generator = None
self_cuda = self.cuda()
p = 1e-8
result_cpu = self.geometric_(p)
result_gpu = self_cuda.geometric_(p)
print("CPU result:\n", result_cpu)
print("GPU ... | true |
2,834,520,879 | torch.compile with fullgraph=True causes overwritten variable error in versions later than torch==2.5.1 | FurtherAI | open | [
"high priority",
"triaged",
"module: regression",
"oncall: pt2",
"module: inductor"
] | 5 | NONE | ### 🐛 Describe the bug
## Minimal Error
Basically, a single forward backward pass through this simple module with `fullgraph=True` will run fine, but on the second pass, it will throw an error for overwriting a variable.
Here is the minimal reproducer:
```python
import torch
from torch import nn
class MLP(nn.Module... | true |
2,834,447,145 | Matmul Triton Template with epilogue fusion can not speed up on XPU. | etaf | open | [
"triaged",
"module: xpu"
] | 2 | COLLABORATOR | ### 🐛 Describe the bug
The matmul triton template is designed and tuned for CUDA, and we found that with epilogue fusion , eg MM + ReLU, the generated fused triton kernel can never speed up on XPU. The root cause is register spill.
This is not reasonable, we're investigating the solution.
### Versions
PyTorch vers... | true |
2,834,405,704 | [copy-for-import][inductor] Refactor op handlers part 2 | jansel | closed | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Copy of #146252 for import into fbcode testing
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @desertfire @chauhang @aakhundov | true |
2,834,401,401 | [DCP] Allow for rank-specific tensors with duplicate keys | cassanof | open | [
"triaged",
"oncall: distributed checkpointing"
] | 3 | CONTRIBUTOR | ### 🚀 The feature, motivation and pitch
My understanding of DCP is that it assumes either DTensor, or fully replicated tensors in the state dict. I have some custom sharding implementation that doesn't use DTensor, and I needed to write a custom SavePlanner class that gathers the shard before saving.
The logic for lo... | true |
2,834,394,751 | use register_full_backward_hook with c10d in torch.compile and raise error | yangxiaorun | open | [
"oncall: distributed"
] | 0 | NONE | ### 🐛 Describe the bug
The following script will trigger "torch._dynamo.exc.TorchRuntimeError: Failed running call_method copy_(*(FakeTensor(..., size=(1, 2), grad_fn=<AsStridedBackward0>), FakeTensor(..., size=(1, 2), grad_fn=<WarnNotImplemented>)), **{}):", I don't understand how AsStridedBackward0 is generated in ... | true |
2,834,352,508 | [inductor] Fix test error test_force_cutlass_backend_aoti_cexpr_codegen | jansel | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Test Plan:
```
buck2 test 'fbcode//mode/opt' fbcode//caffe2/test/inductor:cutlass_backend -- --exact 'caffe2/test/inductor:cutlass_backend - test_force_cutlass_backend_aoti_cexpr_codegen (caffe2.test.inductor.test_cutlass_backend.TestCutlassBackend)'
```
Differential Revision: D69219873
cc @voznesenskym @penguinwu... | true |
2,834,317,008 | Fix broken meta function for flex-attention backwards | drisspg | closed | [
"Merged",
"ciflow/trunk",
"release notes: nn",
"topic: bug fixes",
"module: inductor",
"ciflow/inductor",
"module: flex attention"
] | 14 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146563
# Summary
Fixes https://github.com/pytorch/pytorch/issues/146377
So what was the original problem: we were codegening a really weird epilogue:
```Python
# first compute broadcasted dk of shape [Bq, Hkv, KV... | true |
2,834,312,859 | [pt2d] Add reorder_comms_preserving_peak_memory pass | wconstab | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146562
* #146561
* #152060
This is a new pass to replace the pre-existing passes. It has the same
basic goal, to achieve communication overlap (latency hiding), but also
constrains the solution to not increase peak memory.
The... | true |
2,834,312,455 | Include CollectiveKernel in inductor debug visualization | wconstab | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146558
* #146562
* __->__ #146561
* #152060
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhun... | true |
2,834,312,351 | enable reorder | wconstab | closed | [
"module: inductor",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146562
* #146561
* __->__ #146560
* #146559
* #146558
| true |
2,834,312,235 | Apply changes from https://github.com/pytorch/pytorch/commit/211847de3c1c3d6cbd299e14a001b794eabf2a2d | wconstab | closed | [
"oncall: distributed",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146562
* #146561
* #146560
* __->__ #146559
* #146558
| true |
2,834,312,010 | [not for land] temp changes to enable 'simple_fsdp' | wconstab | open | [
"oncall: distributed",
"ciflow/inductor"
] | 5 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146558
* #146562
* #146561
* #152060
Cherry-picked several unlanded changes from the simple-fsdp workstream
- [dtensor] support mixed precision for redistribute (#20)
- also Apply changes from https://github.com/pytorch/pytorch/commi... | true |
2,834,276,608 | Add fqn_modifier at loading_state_dict and unit test | mori360 | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 9 | CONTRIBUTOR | In Fusion model, users might change the state_dict keys by state_dict_hook
The load_state_dict APIs here won't call model.state_dict() so that the hooks won't be called to change the keys, causing the mismatch between fqn and state_dict keys.
The PR here suggests users to add how they would change the state_dict ke... | true |
2,834,259,984 | Add fqn_modifier at loading_state_dict and unit test | mori360 | closed | [
"oncall: distributed",
"topic: not user facing"
] | 1 | CONTRIBUTOR | In Fusion model, users might change the state_dict keys by state_dict_hook
The load_state_dict APIs here won't call model.state_dict() so that the hooks won't be called to change the keys, causing the mismatch between fqn and state_dict keys.
The PR here suggests users to add how they would change the state_dict ke... | true |
2,834,252,590 | distributed/serialization: add experimental streaming torch.save/load methods | d4l3k | closed | [
"oncall: distributed",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 13 | MEMBER | Summary:
This is intended for use with torchft when we need to do a streaming state dict transfer. This is strictly superior to the prior streaming method in torchft as this supports all tensor subclasses such as DTensor.
This supports 100% of the inputs to torch.save/load but is not wire compatible nor intended ... | true |
2,834,251,670 | [cutlass backend] Set no fallback to aten, disabled a few broken tests, default to test on H100 | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | This PR does a few things:
* set fall back to aten to False for most tests. Without this, a lot of tests would fail silently since they just use aten
* Disable two subprocess related broken tests. They would crash in subprocess. More investigation needed.
* remove/disable the tests on A100. Let me elaborate a bit m... | true |
2,834,233,373 | [dynamo] Remove the suggestion to use suppress_errors on compiler error | 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):
* #146550
* __->__ #146553
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,834,225,496 | [MPSInductor] Fix min/max for bfloat16 | malfet | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146552
By introducing a full specialization that upcasts everything to float, as bfloat does not have a native min/max
Test by runing `test_min_max_reduction`
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSu... | true |
2,834,223,149 | libtorch_cuda_linalg.so: undefined symbol: mkl_lapack_dsbrdbn on a source built PyTorch 2.6.0 with USE_STATIC_MKL=1 on CUDA platform | filbranden | open | [
"module: build",
"triaged",
"module: mkl",
"module: regression",
"actionable"
] | 4 | NONE | ### 🐛 Describe the bug
I'm seeing this error on a source built PyTorch 2.6.0 with USE_STATIC_MKL=1 on a CUDA platform
Using the following code snippet to reproduce the issue:
```python
import torch
A = torch.randn(2, 2, dtype=torch.complex128)
A = A + A.T.conj()
torch.cuda.init()
torch.linalg.eigh(A.to("cuda"))
```... | true |
2,834,217,824 | [dynamo] Actionable message on recompilations for fullgraph=True | anijain2305 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 9 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146550
* #146553
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
2,834,211,288 | [BE][Metal] Fix signed unsigned comparison warning | malfet | closed | [
"Merged",
"topic: not user facing",
"ciflow/mps"
] | 3 | CONTRIBUTOR | I wish I knew how to extract Metal warnings during JIT compilation but https://developer.apple.com/documentation/metal/mtldevice/makelibrary(source:options:)?changes=_7&language=objc is a lie as `error:` stays `nil` unless shader compilation fails. But when it does following warnings are thrown
```
program_source:666... | true |
2,834,209,809 | [ROCm][TunableOp] Future proof TunableOp unit test. | naromero77amd | closed | [
"module: rocm",
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"ciflow/rocm"
] | 3 | COLLABORATOR | TunableOp UT will fail because the regular expression in the test will not work for future versions of ROCm.
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang | true |
2,834,205,687 | [BE][MPS]Reduce number BitwiseOps parameters to 1 | malfet | closed | [
"release notes: mps",
"ciflow/mps"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146547
* #146522
To mimic the behavior of CPU and CUDA
TODO: Add TensorIterator to cast to the same dtype if needed (but want to see if we have tests for it already) | true |
2,834,184,814 | [export] Fix tensor variants to scalar variants. | zhxchen17 | closed | [
"fb-exported",
"ciflow/trunk",
"release notes: quantization",
"release notes: export"
] | 3 | CONTRIBUTOR | Summary:
Ensure that when we construct an ExportedProgram, instead of having patterns like
```
torch.ops.aten.add.Tensor(tensor, scalar)
```
we will always fix it to become
```
torch.ops.aten.add.Scalar(tensor, scalar)
```
Test Plan: CI
Differential Revision: D69212362
| true |
2,834,181,942 | Update test.sh to run a greater set of unit tests on aarch64 | christinaburge | open | [
"module: ci",
"triaged",
"open source",
"Stale",
"topic: not user facing"
] | 4 | NONE | expanded set of unit tests that run on aarch64 to be the entire set of tests that can be run by run_test.py
cc @seemethere @malfet @pytorch/pytorch-dev-infra | true |
2,834,172,628 | [dynamo] fix dynamo_compile logging on RecompileLimitExceeded | xmfan | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 6 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146544
Logging branches based on RecompileLimitExceeded or not. If we exceed the limit, we fallback to eager before even trying to analyze the frame. We handle RecompileLimitExceeded outside of the try/catch/finally that edits the m... | true |
2,834,172,282 | Update local_timer.py to improve queue handling | christinaburge | open | [
"oncall: distributed",
"triaged",
"open source",
"Stale",
"release notes: distributed (torchelastic)"
] | 3 | NONE | - Switched from `multiprocessing.Queue` to `torch.multiprocessing.Queue`
- Wrapped `qsize()` in `try-except` to prevent `NotImplementedError`
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o | true |
2,834,172,227 | DeepSeek: mixed precision optimizers (BF16AdamW) | ngimel | open | [
"module: optimizer",
"triaged"
] | 6 | COLLABORATOR | DeepSeek mentions that they keep optimizer states in bf16, this is something that afaik our optimizers don't support.
Similarly, one could imagine computing/accumulating gradients in less than fp32 accuracy and adding them to fp32 params, something that's also not supported today, when `param` and `param.grad` are mand... | true |
2,834,171,573 | onnx.export: When a quantized model is exported using onnx.export, the convolution result has discrepency with the original quantized model. | ZiyaoAtAiZip | open | [
"module: onnx",
"triaged"
] | 6 | NONE | ### 🐛 Describe the bug
As the title, when using onnx to export a quantized convolution layer, the outcome will have plus or minus one difference in some positions with the quantized convolution layer.
The sample code below can stably re-generate this problem
```python
import torch
import torch.nn as nn
import torch.q... | true |
2,834,162,827 | [export] Draft export custom streamer | angelayi | closed | [
"release notes: export"
] | 1 | CONTRIBUTOR | * Instead of using tlparse's StreamHandler, draft-export will use its own, which will capture the logs, filter them, and only output the relevant ones to the log file.
* To do this, the CaptureStructuredTrace logger will use a `LogRecord` which is basically a dictionary with a custom hash function based on what is be... | true |
2,834,162,723 | [mps] Implement support for sinc() operator (inductor and eager). | dcci | closed | [
"Merged",
"module: mps",
"release notes: mps",
"ciflow/mps",
"module: inductor",
"ciflow/inductor"
] | 4 | MEMBER | cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @desertfire @chauhang @aakhundov | true |
2,834,142,080 | Dynamo unsupported call_function BuiltinVariable(or_) [ConstDictVariable(), ConstDictVariable()] {} | zou3519 | closed | [
"triaged",
"oncall: pt2",
"module: dynamo",
"module: graph breaks",
"dynamo-dicts"
] | 0 | CONTRIBUTOR | ```py
import torch
# works
@torch.compile(fullgraph=True)
def f():
a = {"one": torch.ones(5)}
a.update({"two": torch.ones(4)})
return a
f()
# doesn't work, raises
# Unsupported: call_function BuiltinVariable(or_) [ConstDictVariable(), ConstDictVariable()] {}
@torch.compile(fullgraph=True)
def f():
re... | true |
2,834,139,950 | Log graph breaks | Raymo111 | closed | [
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"module: dynamo",
"ciflow/inductor",
"dynamo-logging"
] | 7 | MEMBER | Graph breaks currently aren't logged to dynamo_compile and pt2_compile_events. We want to log them.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
2,834,135,934 | vmap x compile silently incorrect | zou3519 | closed | [
"high priority",
"triaged",
"actionable",
"module: correctness (silent)",
"oncall: pt2",
"module: functorch",
"dynamo-triage-jan2025"
] | 6 | CONTRIBUTOR | ```py
import torch
from torch import Tensor
lib = torch.library.Library('mylib', 'FRAGMENT')
@torch.library.custom_op('mylib::vquantile', mutates_args=())
def vquantile(x: Tensor, q: Tensor, dim: int = -1) -> Tensor:
return torch.quantile(x, q, dim)
@torch.library.register_fake('mylib::vquantile')
def _(x, q, di... | true |
2,834,120,240 | [wip] disable decorator for ca | xmfan | closed | [
"Stale",
"module: dynamo",
"ciflow/inductor",
"module: compiled autograd"
] | 3 | MEMBER | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #146535
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames @yf225 | true |
2,834,114,798 | [export] Add additional tlparse logging | angelayi | closed | [
"Merged",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146939
* #146955
* #146859
* #146858
* __->__ #146534
* #146533
* #146532
Added some additional logging so we can also run tlparse on generic export errors
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv | true |
2,834,114,714 | [export] Use custom stream logger in draft-export | angelayi | closed | [
"Merged",
"ciflow/inductor",
"release notes: export"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146939
* #146955
* #146859
* #146858
* #146534
* __->__ #146533
* #146532
Using a custom logger so that we can store our own buffer to dedup logs that look the same. The schema for deduping is as follows:
```python
if key == "m... | true |
2,834,114,628 | [symbolic shapes] Log SymNode id for provenance | angelayi | closed | [
"Merged",
"ciflow/trunk",
"release notes: fx",
"fx",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #146939
* #146955
* #146859
* #146858
* #146534
* #146533
* __->__ #146532
We can use the SymNode id to point us back to how previous expressions were created, and construct this nice tree in tlparse:
<img width="761" alt="image" src="ht... | true |
2,834,094,578 | [MPS] linalg solve implementation | Isalia20 | closed | [
"open source",
"Merged",
"topic: improvements",
"release notes: mps",
"ciflow/mps"
] | 4 | COLLABORATOR | Fixes #98222
| true |
2,834,087,624 | [aoti] Add a Tracing Context with FakeTensorMode to AOT Inductor Lowering | yushangdi | open | [
"fb-exported",
"Stale",
"ciflow/trunk",
"module: inductor",
"ciflow/inductor",
"release notes: export",
"module: aotinductor"
] | 12 | CONTRIBUTOR | Summary:
Fixes https://github.com/pytorch/pytorch/issues/118304
In the issue, we have problem with unbacked symints because the fake tensor mode is not detected by AOTI when there's no input.
In the current implementation, AOTI can only detect fake mode from node.meta["val"] for placeholder nodes, which is pr... | true |
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