Datasets:
id int64 2.74B 3.05B | title stringlengths 1 255 | user stringlengths 2 26 | state stringclasses 2
values | labels sequencelengths 0 24 | comments int64 0 206 | author_association stringclasses 4
values | body stringlengths 7 62.5k ⌀ | is_title bool 1
class |
|---|---|---|---|---|---|---|---|---|
3,048,328,783 | Floating Point exception in Convolution with disabled SMT | Flamefire | open | [] | 0 | COLLABORATOR | ### 🐛 Describe the bug
Using NNPACK for convolution on a system with disabled SMT causes a `Floating Point exception" caused by a divide-by-zero, terminating the program.
This can be easily reproduced with `python nn/test_convolution.py TestConvolutionNN.test_conv2d_discontiguous_weight`
This can be traced to a cal... | true |
3,048,208,603 | miss doc for torch.segment_reduce | shadow150519 | open | [] | 0 | NONE | ### 📚 The doc issue
I have noticed there is a function called segment_reduce, but I can't find its doc, will it have a better performance than torch.scatter_reduce since torch.scatter_reduce is more general?
### Suggest a potential alternative/fix
_No response_ | true |
3,048,164,781 | `torch.batch_norm` shows inconsistent error behavior between CPU and GPU | SilentTester73 | open | [] | 1 | NONE | ### 🐛 Describe the bug
## Description
When `torch.batch_norm` is called with one of `running_mean` or `running_var` as a tensor and the other as `None`, an internal assertion `Expected has_running_mean == has_running_var to be true, but got false` is triggered on CUDA-enabled GPUs. However, this error is *not* trigg... | true |
3,048,015,448 | The parameters of in_proj_bias in MultiheadAttention are zeros | Neronjust2017 | open | [] | 0 | NONE | ### 🐛 Describe the bug
I use nn.MultiheadAttention in my model
```
self.multihead_attn = nn.MultiheadAttention(d_model,
nhead,
dropout=dropout,
batch_... | true |
3,047,984,875 | Avoid using system_clock | cyyever | open | [
"oncall: distributed",
"module: cpu",
"open source",
"release notes: quantization"
] | 1 | COLLABORATOR | This PR replaces most `std::chrono::system_clock` with `std::chrono::steady_clock` if the duration is used in condition variables. Ideally system clocks should be used only to log wall-clock times.
Some `high_resolution_clock` are also changed to `steady_clock` because its resolution is not required in the context.
... | true |
3,047,982,027 | [ROCm][CI] Update build-environment for mi300 workflows | jithunnair-amd | open | [
"module: rocm",
"open source",
"topic: not user facing",
"ciflow/rocm"
] | 1 | COLLABORATOR | so their test times are tracked separately in https://raw.githubusercontent.com/pytorch/test-infra/generated-stats/stats/test-times.json. Currently, both MI200 and MI300 test times get combined into the same key `linux-focal-rocm-py3.10`
cc @jeffdaily @sunway513 @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hong... | true |
3,047,909,723 | Inconsistent behavior between CPU and GPU implementations of `torch.arange` | SilentTester73 | open | [] | 1 | NONE | ### 🐛 Describe the bug
## Description
When using `torch.arange()` with a start value greater than the end value and a positive step, the behavior differs between CPU and GPU implementations:
- GPU silently returns an empty tensor
- CPU correctly raises an exception about inconsistent bounds with step sign
## Reprod... | true |
3,047,900,019 | Inconsistent behavior and misleading error message for `torch.nanmean()` with complex dtypes | SilentTester73 | open | [
"topic: bug fixes"
] | 2 | NONE | ### 🐛 Describe the bug
## Description:
When using nanmean() with complex tensors, there's an inconsistent behavior between CPU and GPU implementations:
- On GPU: The function works correctly with complex dtypes (complex128)
- On CPU: The function fails, but with a misleading error message: "nansum does not support c... | true |
3,047,833,331 | fix slice w/ dynamic shapes | cgufb | open | [
"fb-exported",
"ciflow/inductor"
] | 4 | CONTRIBUTOR | Summary: guard_size_oblivious has side effects that'll result in invalid strides when slice nodes take negative index on dynamic input shapes.
Test Plan: CIs should pass.
Differential Revision: D74354663
| true |
3,047,778,668 | [Minimizer] Fix the path naming | jimone1 | open | [
"fb-exported",
"release notes: fx",
"fx"
] | 5 | CONTRIBUTOR | Summary:
Added some logging and captured the indexing. See below image.
{F1977773416}
This is why the saved module path is called `/tmp/jimwan/minimizer_a_acc.pt`
Now the updated module paths are `/tmp/jimwan/minimizer_addmm_default_103_acc.pt`.
Test Plan:
```
MTIAC_USE_DIST_REF_KERNELS=all buck2 run @//mode/opt mt... | true |
3,047,722,761 | DISABLED test_intermediary_hooks_same_on_inductor (__main__.HooksTests) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 1 | NONE | Platforms: asan, linux, mac, macos, rocm
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_intermediary_hooks_same_on_inductor&suite=HooksTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41835113407).
... | true |
3,047,721,817 | Inconsistent Complex torch.Tensor.asin() Results Between CPU and GPU | SilentTester73 | open | [] | 1 | NONE | ### 🐛 Describe the bug
## Bug Description
When computing the asin of a complex tensor with very small real part, large imaginary part using PyTorch, there is a discrepancy between the results computed on CPU versus GPU. The CPU computation often returns complex infinity, while the GPU returns finite numerical values... | true |
3,047,693,561 | Operations on a tensor and a scalar will cause the error on dtype of the result | Redempt1onzzZZ | closed | [] | 2 | NONE | ### 🐛 Describe the bug
It's a derived finding based on #153014. As the normal logic of pytorch, when an API dealing with two tensor of different dtype (data precision), the result will follow the higher precision, like the below example.
```
import torch
tensor1 = torch.tensor([0.01], dtype=torch.float16, device='cud... | true |
3,047,638,306 | Add tests to check pretty print when padding is a string in C++ API | Alvaro-Kothe | open | [
"open source",
"topic: not user facing"
] | 1 | CONTRIBUTOR | Currently there are no tests to verify the behaviour of pretty print when padding is `torch::kSame` or `torch::kValid`. This PR just adds this tests to check for future regressions.
| true |
3,047,624,613 | Add logging for guard miss failure | jamesjwu | open | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 6 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153125
Differential Revision: [D74371381](https://our.internmc.facebook.com/intern/diff/D74371381/)
This PR adds some logging for guard misses to tlparse, so that we know when AOTAutogradCache and FxGraphCache miss due to guard... | true |
3,047,624,527 | Turn on static cuda launcher test | jamesjwu | closed | [
"fb-exported",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* (to be filled)
Differential Revision: [D74339692](https://our.internmc.facebook.com/intern/diff/D74339692/)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chen... | true |
3,047,608,665 | DISABLED test_input_codegen_with_sympy_expr_xpu (__main__.AOTInductorTestABICompatibleGpu) | etaf | open | [
"triaged",
"skipped",
"module: xpu"
] | 1 | COLLABORATOR | Platforms: <fill this in or delete. Valid labels are: asan, linux, mac, macos, rocm, win, windows.>
This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22inductor%2Ftest_aot_inductor.py%3A%3AAOTInductorTestABICompatibleGpu%3A%3Atest_input_code... | true |
3,047,534,169 | [CUDA] test_c10d_nccl test_extra_cuda_context failure due to _helper_test_extra_cuda_context_by_memory | nWEIdia | open | [] | 1 | COLLABORATOR | While trying to replace cuda11.8 distributed jobs by cuda 12.6 ([PR](https://github.com/pytorch/pytorch/pull/151594/files#diff-9f639571a250cffbe9cded7d2fbb5ad6311e4be9c0c7610e5ba85930806e7f38)), test_extra_cuda_context failed and I had to increase the 1.5x heuristic to 1.7 to temporarily workaround the failure.
When... | true |
3,047,526,737 | Revert "[CI] docker images use tags instead of image name (#152209)" | huydhn | open | [
"module: rocm",
"topic: not user facing",
"ciflow/inductor",
"ci-no-td"
] | 1 | CONTRIBUTOR | This reverts commit 0145f9e29e37beb2fb03bf2538f675060ab7b4f5.
DEBUG PR, no need to review
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd | true |
3,047,515,089 | DISABLED test_nn_module (__main__.TestGuardSerialization) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 2 | NONE | Platforms: asan, linux, mac, macos, rocm, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_nn_module&suite=TestGuardSerialization&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41828599132).
Over ... | true |
3,047,510,959 | devmate factor our test_torch tests | bobrenjc93 | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153119
* #153118
* #152924
prompt "ok great now can you split test\_torch.py into more smaller
pieces just like you did with test\_basic\_vital\_signs.py?" | true |
3,047,498,747 | devmate test_basic_vital_signs | bobrenjc93 | open | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #153119
* __->__ #153118
* #152924
| true |
3,047,468,182 | [TESTING] Triton pin (May 7) 81f93f2c8ec7d20a1f8184def767edeaebeb6812 | davidberard98 | open | [
"ciflow/trunk",
"topic: not user facing",
"ciflow/inductor",
"ciflow/rocm",
"ci-no-td"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153117
| true |
3,047,467,718 | [c10d] Reduce test verbosity | kwen2501 | open | [
"module: c10d",
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153116
Has been seeing a lot of `Starting event listener thread for rank` recently in test print-out. Moving them to `logger.debug`. | true |
3,047,453,154 | [ONNX] Implement sym_float? | justinchuby | open | [
"module: onnx",
"triaged"
] | 2 | COLLABORATOR | Do we need sym_float in https://github.com/pytorch/pytorch/blob/main/torch/onnx/_internal/exporter/_torchlib/ops/symops.py ?
@titaiwangms @xadupre | true |
3,047,451,491 | [BE][lint] fix PYFMT for PT-D code under torch.testing._internal, add them to the lint list | XilunWu | open | [
"oncall: distributed",
"module: lint",
"better-engineering",
"ciflow/trunk",
"topic: not user facing"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153114
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @EikanWang @jgong5 @wenzhe-nrv @sanchitintel | true |
3,047,447,913 | [C10D] Move getNcclDataType into NCCLUtils | GD06 | closed | [
"oncall: distributed",
"fb-exported",
"Merged",
"ciflow/trunk",
"release notes: distributed (c10d)"
] | 6 | CONTRIBUTOR | Differential Revision: D74365214
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,047,425,123 | Support using SymInt shapes for torch.baddbmm no-broadcast case | yf225 | open | [
"ciflow/trunk",
"topic: not user facing"
] | 2 | CONTRIBUTOR | A typical `bmm` kernel in Helion needs to pass in symint shapes to `torch.baddbmm`. Currently `self.expand((dim1, dim2, dim3))` in baddbmm runs unconditionally and it doesn't work with symint shapes (it raises the following error):
```
Traceback (most recent call last):
File "/home/willfeng/local/helion_yf225/heli... | true |
3,047,422,533 | [Graph Partition] Maintain relative order within partition during reordering | BoyuanFeng | open | [
"oncall: distributed",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | PR #151968 adds `reorder_for_minimizing_partition` for the minimal number of partitions. If reordering two nodes cannot reduce the number of partitions, `reorder_for_minimizing_partition` should maintain the relative order of these two nodes and rely on other reorder passes for some nice features, such as shorter liven... | true |
3,047,414,644 | [c10d] Remove unordered PG destroy test | kwen2501 | open | [
"oncall: distributed",
"ciflow/trunk",
"topic: not user facing"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153110
torch.distributed does not support unordered ProcessGroup destroy. Removing the test.
Resolves #137507
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k | true |
3,047,396,841 | Inconsistent size passed to custom CUDA alloc/free in torch::unique_consecutive | darrin-willis | open | [] | 0 | NONE | ### 🐛 Describe the bug
When using `CUDAPluggableAllocator`, there is a different size passed to `malloc` vs `free` for some tensor inside `torch::unique_consecutive` on the third invocation. This can impact & corrupt alternative allocators like RMM. This may be related to https://github.com/pytorch/pytorch/pull/13047... | true |
3,047,361,033 | Introduce unbacked friendly is_known_contiguous and use it instead of is_contiguous in all locations where there is a general path for not know_contiguous | laithsakka | open | [
"oncall: pt2",
"module: dynamic shapes",
"data dependent error"
] | 0 | CONTRIBUTOR | title.
cc @chauhang @penguinwu @ezyang @bobrenjc93 | true |
3,047,306,800 | do not reinplace diagonal_scatter | BoyuanFeng | open | [
"ciflow/trunk",
"topic: not user facing",
"module: functionalization",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | In the following code, `copy_` changes values of `mul` which is later read by `torch.mm`. So `torch.mm` has to happen after `copy_`. This info is captured in aot graph. We can see `mm` reads `diagonal_scatter`, which reads `copy`. So we know torch.ops.aten.mm must happen after torch.ops.aten.copy.
However, in post_g... | true |
3,047,291,352 | [cutlass backend] Fix EVT test for fbcode post cutlass 3.9.2 upgrade | henrylhtsang | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153106
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,047,287,497 | [dynamo] Fix super and classmethod binding of cls object | anijain2305 | open | [
"ciflow/trunk",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153105
* #152883
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,047,281,502 | [FlexAttention] Remove Old Constraint on lastdim strides | drisspg | open | [
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | https://github.com/pytorch/pytorch/pull/151959
Cherry pick
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,047,264,749 | [Inductor] Investigate computing global amaxes via atomics (instead of a reduction based approach) in triton codgen | danielvegamyhre | open | [
"oncall: pt2",
"module: inductor"
] | 0 | CONTRIBUTOR | ## Summary
Tensorwise or rowwise amax values are used to compute scaling factors in float8 quantization. Computing these values in a performant way is critical for float8 training with dynamic quantization, where we are dynamically scaling the tensors at runtime in forward/backward.
Currently inductor codegen uses a... | true |
3,047,243,750 | `bernoulli_()` produces inconsistent results between CPU and GPU | SilentTester73 | closed | [] | 1 | NONE | ### 🐛 Describe the bug
## Description
The in-place `torch.Tensor.bernoulli_()` function generates significantly different results when run on CPU versus GPU.
## Minimal Reproduction Code
Available on Colab: [https://colab.research.google.com/drive/1CC3VIj0FocMUu1ebozzF7IHsdBiQDPE_?usp=sharing](https://colab.researc... | true |
3,047,232,042 | [CUDA][CUDNN] Dispatch to cuDNN for non-batch-splittable 64-bit NCHW convolutions | eqy | open | [
"module: cuda",
"module: cpu",
"module: convolution",
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | For #152816
cc @ptrblck @msaroufim @jerryzh168 @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 | true |
3,047,230,094 | DISABLED test_intermediary_hooks_same_on_aot_eager (__main__.HooksTests) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: asan, linux, mac, macos, rocm, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_intermediary_hooks_same_on_aot_eager&suite=HooksTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/4181877... | true |
3,047,223,137 | [mm sampling] extract more triton information | coconutruben | closed | [
"fb-exported",
"Merged",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 8 | CONTRIBUTOR | Summary:
# Why
capture more triton config information that was not being captured
# What
capture and extract
- group_m
- allow_tf32
- acc_type
- matrix_instr_nonkdim
- waves_per_eu
- kpack
to achieve this, add
- matrix_instr_nonkdim
- waves_per_eu
- kpack
to the info_dict of the TritonTemplateCaller
Test Plan:
... | true |
3,047,189,264 | [Cherry-pick] Fix copysign + scalar correctness issue | malfet | open | [
"release notes: mps",
"ciflow/mps"
] | 1 | CONTRIBUTOR | Which consists of two cherry-picks:
- https://github.com/pytorch/pytorch/pull/152997
- https://github.com/pytorch/pytorch/pull/152510 (only partially, as code path are quite divergent between 2.7 and trunk)
| true |
3,047,165,801 | Use std::fma for CUDA Adam kernel's lerps. | MeetThePatel | open | [
"open source",
"release notes: cuda"
] | 1 | CONTRIBUTOR | Switch the calculation of lerps in Adam's fused CUDA kernel to use std::fma, as proposed by @crcrpar . | true |
3,047,162,885 | [WIP][XPU] Update Triton commit | anmyachev | open | [
"triaged",
"open source",
"topic: not user facing",
"ciflow/inductor",
"ciflow/xpu"
] | 2 | COLLABORATOR | To view the current pass rate on a full test suite and detect problems earlier. | true |
3,047,161,717 | [CUDA][cuBLASLt] Respect `allow[FP16/BF16]ReductionCuBLAS` in `cuBLASLt` | eqy | open | [
"module: cublas",
"open source",
"module: bfloat16",
"module: half",
"topic: not user facing",
"matrix multiplication"
] | 1 | COLLABORATOR | cuBLASLt matmuls have been silently allowing all reduction types, which meant that e.g., `allow_fp16_reduced_precision_reduction = False` had no effect.
In practice split-K with reduced precision reductions were unlikely to happen as the default `CUBLASLT_WORKSPACE_SIZE` of 1MiB tends to prevent this.
However thi... | true |
3,047,146,820 | Add missing in-place on view check to custom autograd.Function | soulitzer | open | [
"release notes: autograd"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153094
* #153005
Fixes https://github.com/pytorch/pytorch/issues/152773 | true |
3,047,052,936 | [vec128] Fix fmsub NEON defintion | pytorchbot | closed | [
"module: cpu",
"open source"
] | 1 | COLLABORATOR | 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 |
3,047,034,816 | [MKLDNN] Check that strides are positive | pytorchbot | closed | [
"module: cpu",
"module: mkldnn",
"open source",
"ciflow/linux-aarch64"
] | 1 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #151848
For pooling ops. Prevents division-by-zero when argument is wrong
Fixes https://github.com/pytorch/pytorch/issues/149274
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 @gujinghui @PenghuiCh... | true |
3,047,030,686 | Fix tensorpipe compilation with clang-17 | pytorchbot | closed | [
"open source"
] | 1 | COLLABORATOR | By suppressing `missing-template-arg-list-after-template-kw` warning, which seems to be required to compile Google's libnop, which is in a semi-abandoned state now
```
In file included from /Users/malfet/git/pytorch/pytorch/third_party/tensorpipe/third_party/libnop/include/nop/base/variant.h:21:
/Users/malfet/git/py... | true |
3,046,998,970 | Clean up right nav | svekars | open | [
"module: docs",
"topic: docs",
"topic: not user facing"
] | 2 | CONTRIBUTOR | - Move community and language binding links to the horizontal bar
- Add an intro to the community page.
- Fix the link in the ogp_image
- Fix the link in the version switcher
- Clean up unneeded links
- Test noindex as a meta tag in fsdp doc
cc @sekyondaMeta @AlannaBurke | true |
3,046,977,866 | [Cherry Pick] Remove cuda dependencies from non cuda buids #152333 | atalman | closed | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | Cherry Pick of https://github.com/pytorch/pytorch/pull/152333
Related to: https://github.com/pytorch/pytorch/issues/152121
| true |
3,046,976,974 | [nativert] move recordfunction | dolpm | open | [
"fb-exported",
"topic: not user facing"
] | 8 | CONTRIBUTOR | Summary:
nativert RFC: https://github.com/zhxchen17/rfcs/blob/master/RFC-0043-torch-native-runtime.md
To land the runtime into PyTorch core, we will gradually land logical parts of the code into the Github issue and get each piece properly reviewed.
This diff moves the our function-recording raii wrapper into record_... | true |
3,046,969,761 | [nativert] move executor config to torch | dolpm | open | [
"fb-exported",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Summary:
nativert RFC: https://github.com/zhxchen17/rfcs/blob/master/RFC-0043-torch-native-runtime.md
To land the runtime into PyTorch core, we will gradually land logical parts of the code into the Github issue and get each piece properly reviewed.
This diff moves the executor config to torch. since it's header-only... | true |
3,046,947,509 | Export doesn't work with patched forward | tugsbayasgalan | open | [
"oncall: pt2",
"oncall: export"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```
class Foo(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
return x + 2
import functools
def fancy_forward(x, y):
return x + 2 + y
Foo.forward = functools.partial(fancy_forward, y=torch.randn(4, 4))
torch.export.export(Foo(), (to... | true |
3,046,947,193 | Allow workflows to opt-out of experiments | zxiiro | open | [
"open source",
"topic: not user facing",
"ciflow/inductor-periodic"
] | 1 | COLLABORATOR | This change adds support to allow workflows to opt-out of experiments.
| true |
3,046,940,041 | Refactor nested benchmarking functions in select_algorithm.py | masnesral | open | [
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153084
Summary: I'll need some of the benchmark-related functions surfaced so I can use them for remote autotuning. This PR just lifts the main in-process benchmarking helpers to classmethods. It wasn't strictly necessary to also mov... | true |
3,046,920,180 | [CUDA][cuBLASLt] Fix scale setting for `allowFP16AccumulationCuBLAS` `true` case | eqy | open | [
"module: cuda",
"triaged",
"module: cublas",
"open source",
"module: half",
"release notes: cuda"
] | 1 | COLLABORATOR | Also add some missing `@onlyCUDA` / support check decorators in `test_matmul_cuda.py`
Should help resolve #151890
cc @ptrblck @msaroufim @jerryzh168 @csarofeen @xwang233 | true |
3,046,896,343 | [dynamo] Harden torch function dispatchability check for attributes and methods access | StrongerXi | open | [
"ciflow/trunk",
"module: dynamo",
"ciflow/inductor",
"release notes: dynamo"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153082
See more details in
https://github.com/pytorch/pytorch/issues/151771#issuecomment-2836372110.
Fixes #151771.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayis... | true |
3,046,889,949 | [cutlass-3] Add cutlass key for fbcode and OSS | henrylhtsang | open | [
"fb-exported",
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 7 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153081
Differential Revision: [D74337959](https://our.internmc.facebook.com/intern/diff/D74337959/)
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chen... | true |
3,046,852,748 | [BE] Move all lint runner to 24.04 | malfet | closed | [
"topic: not user facing"
] | 1 | CONTRIBUTOR | As Ubuntu-20 reached EOL on Apr 1st, see https://github.com/actions/runner-images/issues/11101
This forces older python version to be 3.8
Delete all linux-20.04 runners from the lintrunner.yml
Cherry-pick of https://github.com/pytorch/pytorch/pull/150427 into release/2.7 branch
(cherry picked from commit 48af2cd... | true |
3,046,834,020 | [FSDP2][Doc] add pointer to torchtitan | weifengpy | open | [
"release notes: distributed (fsdp)"
] | 1 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153079
Summary:
Test Plan:
Reviewers:
Subscribers:
Tasks:
Tags: | true |
3,046,761,919 | Add TensorLR variant for fused Adagrad on CPU | MeetThePatel | open | [
"triaged",
"open source",
"release notes: optim"
] | 3 | CONTRIBUTOR | This PR adds a tensor LR variant for the CPU Adagrad(fused=True).
I copied the behavior from the tensor LR variant of CPU Adam(fused=True), where the `lr.item()` is cast to a double and passed in the default function. | true |
3,046,743,699 | Mismatch of mixed precision `cast_fn` in FSDP and FSDP2 | markovka17 | open | [
"oncall: distributed",
"module: fsdp"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
FSDP2 does not work with `dataclasses` as input. More specifically, FSDP2's pre_hook does not cast tensors from dataclass. FSDP uses [_apply_to_tensors_](https://github.com/pytorch/pytorch/blob/172e6415299e93629497d9660c525c8bf60af912/torch/distributed/utils.py#L218) to handle dataclass-like ob... | true |
3,046,733,312 | Fix test/test_optim.py error message. | MeetThePatel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Fixes an error message in test/test_optim.py
Current behavior: If running the test with Adagrad, the error message reads: "SGD does not currently support capturable".
Fix: The error message now says correctly: "Adagrad does not currently support capturable". | true |
3,046,732,426 | Delete .github/workflows/docker-cache-mi300.yml | seemethere | open | [
"topic: not user facing"
] | 2 | MEMBER | The runner group for this has 0 runners, we should probably just delete.
| true |
3,046,729,068 | Fix TORCH_CHECK error message in FusedSgdKernel | MeetThePatel | closed | [
"open source",
"Merged",
"ciflow/trunk",
"release notes: cuda"
] | 3 | CONTRIBUTOR | This fixes an issue in the TORCH_CHECK error message in the FusedSgdKernel.
Current behavior: If the LR tensor is not on the same device as the parameters, the error message reads: "found_inf must be on the same GPU device as the params".
Fix: The error message now correctly points out "lr must be on the same GPU... | true |
3,046,724,169 | [inductor] Fix #153071 | rec | open | [
"open source",
"topic: not user facing",
"module: inductor",
"ciflow/inductor"
] | 3 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153073
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov | true |
3,046,707,691 | fbgemm Update pinned version | gchalump | open | [
"fb-exported",
"topic: not user facing"
] | 6 | NONE | Differential Revision: D74335570
| true |
3,046,661,927 | Link check fails on link from comment in torch/_inductor/codegen/cpp.py to Stack Overflow | rec | open | [
"module: lint",
"triaged",
"actionable",
"bug"
] | 3 | COLLABORATOR | ### 🐛 Describe the bug
My PR kept stalling in merge complaining about link checking without providing a message, so I rebased it to reveal this:
https://github.com/pytorch/pytorch/actions/runs/14888839700/job/41815590757?pr=149958
```
[...]
200 https://github.com/pytorch/pytorch/blob/f353d17755ed23b02924c962a86ff99... | true |
3,046,661,687 | Fix path matching in `CPythonTestCase/setUpClass` | guilhermeleobas | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152991
* #152990
* #152908
* #152907
* #152989
* #152906
* #152905
* #152903
* #152902
* #152901
* #152904
* #152988
* #152987
* #150792
* #152900
* __->__ #153070
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSupe... | true |
3,046,646,916 | `torch.ldexp` goes out of range when `2**other` is out of range | roman-openai | open | [
"high priority",
"triage review",
"module: correctness (silent)"
] | 3 | NONE | ### 🐛 Describe the bug
```python
import torch
torch.ldexp(torch.tensor([2], dtype=torch.float16), torch.tensor([-25], dtype=torch.int32))
```
Gives
```python
tensor([0.], dtype=torch.float16)
```
Even though `2 * 2**-25 = 2**-24` is non-zero and is within representable range of `torch.float16`, and
```python
torch.ld... | true |
3,046,641,284 | OSS CI Infra Storm (Scenario 1 + 2) - May 7, 2025 | seemethere | open | [
"triaged"
] | 2 | MEMBER | ## Current Status
Executing Scenario 2
## Scenario 1
Following along scenario 1 ([link, for Metamates only](https://docs.google.com/document/d/1ttAsjMrCEoEyqnIs5UdxzkAvL7xKnO10ytsm7hg9rWQ/edit?fbclid=IwZXh0bgNhZW0CMTEAYnJpZBExeXRVeUNaSlJVeG9NenBsUQEeQMjB0mGfUzUl5CQ3NcECnkY1we9HB_aw1MaM55y3smJvGT4jbkicOix5j-s_aem_tzgX... | true |
3,046,634,751 | Add device guard for xpu conv on multi device | guangyey | open | [
"module: cpu",
"open source",
"ciflow/trunk",
"keep-going",
"merging",
"ciflow/xpu",
"release notes: xpu"
] | 12 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153067
# Motivation
fixes https://github.com/pytorch/pytorch/issues/153022
The root cause is that the XPU backend registers the convolution op using `m.impl`, which bypasses the device guard logic typically added by the code gen... | true |
3,046,576,289 | fix bug with TORCHINDUCTOR_DUMP_LAUNCH_PARAMS | exclamaforte | open | [
"fb-exported",
"module: inductor",
"ciflow/inductor"
] | 3 | CONTRIBUTOR | Summary:
https://fb.workplace.com/groups/1028545332188949/posts/9503194033132340/?comment_id=9504669536318123&reply_comment_id=9506405459477864¬if_id=1746154132646897¬if_t=work_group_comment_mention
Aligns the arguments for the triton inputs
Differential Revision: D74085173
cc @voznesenskym @penguinwu @Eika... | true |
3,046,554,465 | [ONNX] dynamic_shapes uses DYNAMIC | titaiwangms | closed | [
"module: onnx",
"open source",
"Merged",
"ciflow/trunk",
"release notes: onnx",
"topic: improvements"
] | 3 | COLLABORATOR | Although Dim.AUTO covers the cases that a user sets more axes to be dynamic than the model actually needs, it silently falls back to STATIC when DYNAMIC fails. This increases the difficulty of debugging. | true |
3,046,532,741 | Keep raw cubin file around in case it gets deleted underneath us | jamesjwu | open | [
"ciflow/trunk",
"topic: not user facing",
"module: inductor",
"ciflow/inductor",
"ciflow/pull"
] | 2 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153064
This diff hardens StaticCudaLauncher in the event a cubin file gets deleted under us. We store the raw cubin on the static cuda launcher, and reload it as needed. On cold start, this can happen if the cubin file is created ... | true |
3,046,516,669 | [FlexAttention] export fails to trace with functorch | tugsbayasgalan | open | [
"triaged",
"oncall: pt2",
"module: functorch",
"module: flex attention"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
import torch.nn as nn
from torch.func import vmap
from torch.export import export
# 1. Inner model (shared across batch)
class TinyModel(nn.Module):
def __init__(self):
super().__init__()
self.linear = nn.Linear(8, 4)
def forward(self, x):
... | true |
3,046,481,642 | non-strict export should detect fake tensor leakage | tugsbayasgalan | open | [
"oncall: pt2",
"oncall: export"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
self.buffer = torch.nn.Buffer(torch.randn(4, 4))
def forward(self, x):
return self.buffer.sum() + x.sum()
class Pipeline:
def __init__(self, model):
self.model = model
... | true |
3,046,466,098 | register_constant doesn't work on simple types | tugsbayasgalan | open | [
"module: pytree",
"oncall: pt2",
"oncall: export"
] | 1 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
from enum import Enum
class Color(Enum):
RED = 1
GREEN = 2
BLUE = 3
class Foo(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, col):
return x + col.value
torch.utils._pytree.register_constant(Color)
torch.export.ex... | true |
3,046,465,981 | Fix misleadingly high AOT Inductor dashboard performance | benjaminglass1 | open | [
"open source",
"topic: not user facing",
"module: dynamo",
"ciflow/inductor"
] | 2 | COLLABORATOR | An [example benchmark](https://hud.pytorch.org/benchmark/timm_models/inductor_aot_inductor?dashboard=torchinductor&startTime=Wed%2C%2030%20Apr%202025%2015%3A54%3A04%20GMT&stopTime=Wed%2C%2007%20May%202025%2015%3A54%3A04%20GMT&granularity=hour&mode=inference&dtype=bfloat16&deviceName=cuda%20(h100)&lBranch=main&lCommit=1... | true |
3,046,429,194 | DISABLED test_input_hooks_same (__main__.HooksTests) | pytorch-bot[bot] | open | [
"module: flaky-tests",
"skipped",
"module: unknown",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: linux, mac, macos, rocm, asan, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_input_hooks_same&suite=HooksTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41796649006).
Over the p... | true |
3,046,315,502 | `cuda.Event` handling in dynamo is broken | bdhirsh | open | [
"module: cuda",
"oncall: pt2",
"module: dynamo"
] | 1 | CONTRIBUTOR | Here's an example:
```
import torch
lst = []
@torch.compile(backend="eager", fullgraph=True)
def f(x):
start_event = torch.cuda.Event(enable_timing=True)
end_event = torch.cuda.Event(enable_timing=True)
start_event.record()
out = torch.matmul(x, x)
end_event.record()
lst.append(start_event)
... | true |
3,046,272,178 | [BE] Update ruamel to 0.18.10 | malfet | closed | [
"better-engineering",
"Merged",
"ciflow/trunk",
"topic: not user facing"
] | 3 | CONTRIBUTOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* #152719
* __->__ #153057
To address the feedback from https://github.com/pytorch/pytorch/pull/153013
Previously it was pinned to 0.17.4, that was released in 2021 | true |
3,046,252,394 | Export doesn't move embedding to correct device | tugsbayasgalan | open | [
"oncall: pt2",
"oncall: export"
] | 0 | CONTRIBUTOR | ### 🐛 Describe the bug
```python
import torch
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
self.embedding = torch.nn.Embedding(num_embeddings=10, embedding_dim=8)
def forward(self, x):
token_ids = torch.randint(0, 10, (4,), device=x.device)
embedded... | true |
3,046,238,361 | [BE]: Add PEP621 project section to pyproject.toml | Skylion007 | open | [
"triaged",
"open source",
"better-engineering",
"topic: not user facing"
] | 3 | COLLABORATOR | Follow up to @ezyang's PR #153020 , but better uses PEP621 to reduce redundant fields and pass through metadata better to uv, setuptools, poetry and other tooling.
* Enables modern tooling like uv sync and better support for tools like poetry.
* Also allows us to set project wide settings that are respected by lin... | true |
3,046,198,637 | [HOP] Reworked HOPs to use FunctionalizeCtxWrapper | bohnstingl | open | [
"triaged",
"open source",
"topic: not user facing"
] | 3 | COLLABORATOR | This PR reworks the `py_functionalize_impl` of HOPs and introduces the use of `FunctionalizeCtxWrapper`.
cc @ydwu4
| true |
3,046,102,584 | [BE]: Blacklist broken setuptools until we upgrade MSVC API | Skylion007 | open | [
"open source",
"topic: not user facing"
] | 1 | COLLABORATOR | Alternative to #153052 where we just ban the broken setuptools version | true |
3,046,100,119 | [BE]: Use undocumented temp shim to restore setuptools compat | Skylion007 | open | [
"oncall: releng",
"open source",
"better-engineering",
"topic: not user facing"
] | 2 | COLLABORATOR | null | true |
3,046,096,583 | [Intel GPU] scalar tensor case handling in addmm, baddmm | ZhiweiYan-96 | open | [
"module: cpu",
"module: mkldnn",
"open source",
"ciflow/trunk",
"topic: not user facing",
"ciflow/binaries_wheel",
"ciflow/xpu",
"ciflow/linux-aarch64"
] | 2 | COLLABORATOR | Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #153051
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 @gujinghui @PenghuiCheng @jianyuh @min-jean-cho @yanbing-j @Guobing-Chen @Xia-Weiwen @snadampal | true |
3,045,564,719 | Process never ends when sending tensors through multiprocessing queues in Python 3.12+ on macOS | rafalh | open | [
"needs reproduction",
"module: multiprocessing",
"triaged",
"module: macos",
"module: deadlock"
] | 4 | NONE | ### 🐛 Describe the bug
If a tensor is sent in multiprocessing queue, something blocks the process from ending after the end of script is reached (I have to press Ctrl+C to end the program).
It seems to be related to the resource tracker (`multiprocessing.resource_tracker.ResourceTracker`) process started by Python au... | true |
3,045,487,542 | Update docs of saved_tensors_hooks to avoid ref cycle | ppwwyyxx | closed | [
"triaged",
"open source",
"Merged",
"ciflow/trunk",
"release notes: autograd",
"topic: docs"
] | 3 | COLLABORATOR | Fixes #115255
| true |
3,045,394,006 | 🌠 Add Muon optimizer | kadirnar | open | [
"triaged",
"open source",
"release notes: optim"
] | 3 | NONE | Fixes https://github.com/pytorch/pytorch/issues/148819 | true |
3,045,385,461 | DISABLED test_comprehensive_special_ndtri_cuda_int64 (__main__.TestInductorOpInfoCUDA) | pytorch-bot[bot] | open | [
"high priority",
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: inductor"
] | 2 | NONE | Platforms: inductor
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_comprehensive_special_ndtri_cuda_int64&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41770133820).
Over ... | true |
3,045,385,330 | DISABLED test_comprehensive_trunc_cuda_float64 (__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_trunc_cuda_float64&suite=TestInductorOpInfoCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41775258519).
Over the past ... | true |
3,045,385,194 | DISABLED test_hook_with_nested_closure (__main__.HooksTests) | pytorch-bot[bot] | open | [
"triaged",
"module: flaky-tests",
"skipped",
"oncall: pt2",
"module: dynamo"
] | 3 | NONE | Platforms: asan, linux, mac, macos, rocm, slow
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_hook_with_nested_closure&suite=HooksTests&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/41771802586).
Over... | true |
3,045,331,296 | Unexpected float32 overflow for amp training with torch.compile | zbh2047 | open | [
"high priority",
"triage review",
"oncall: pt2"
] | 1 | NONE | ### 🐛 Describe the bug
I recently encountered significant precision issue when using torch.amp together with torch.compile. I was finally able to create a minimal reproducible code as shown below:
```python
import torch
import torch.nn
class Model(nn.Module):
def __init__(self):
super().__init__()
... | true |
3,045,117,090 | [Typing] Remove redundant type aliases of `_device_t` for `torch.types.Device` in `torch/_dynamo/device_interface.py` | shink | closed | [
"triaged",
"open source",
"topic: not user facing",
"module: dynamo"
] | 3 | CONTRIBUTOR | Part of: #152952
Follow up: #153007
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames | true |
3,045,054,926 | Pytorch 2.7 crashes when using flex attention with torch.amp | zbh2047 | open | [
"module: crash",
"oncall: pt2",
"module: higher order operators",
"module: pt2-dispatcher",
"module: flex attention"
] | 2 | NONE | ### 🐛 Describe the bug
I believe this bug should exist for a very long time but is still not fixed yet, so I post this new issue here.
Basically, the current flex attention is incompatible with torch.amp.autocast. The bug can be reproduced with the following (extremely simple) code:
```python
import torch
import to... | true |
3,044,898,009 | gen_alias_from_base ruins the result of view after inductor generated a copy for the results of the view operations. | laithsakka | open | [
"triaged"
] | 2 | CONTRIBUTOR | There is three issues here:
1) if we have the following aot_graph inductor generates a copy for the view operation which is not permitted. (it should generate a view). see the view operation on the last line. cc @eellison
```
2000 3525273 torch/fx/experimental/symbolic_shapes.py:1220] [0/0] For C++ stack trace, run ... | true |
End of preview. Expand in Data Studio
Dataset Card for github-pytorch-issues
Dataset Summary
This dataset is a curated collection of GitHub issues from the PyTorch repository. Each entry includes the issue title, body, user, state, labels, comments, and other relevant fields that are useful for tasks such as text classification, semantic search, and question answering.
Supported Tasks and Leaderboards
The dataset supports the following tasks:
- Open-domain Question Answering: Given a user query, match it to a relevant issue and retrieve the response from the issue body or comments.
- Closed-domain Question Answering: Same as above but restricted to PyTorch-related questions.
- Text Generation / Language Modeling: Use the issue title as prompt and body as target text to fine-tune generative models.
Languages
- English (
en)
Dataset Structure
Data Fields
id: Unique issue IDtitle: Title of the issueuser: GitHub user who opened the issuestate: Open or closedlabels: Comma-separated labels/tagscomments: Number of commentsauthor_association: Role of the author in the repositorybody: Main text of the issue
Example
{
"id": 1500,
"title": "torch.save crashes on certain tensor inputs",
"user": "some_user",
"state": "open",
"labels": ["bug", "serialization"],
"comments": 4,
"author_association": "CONTRIBUTOR",
"body": "I'm encountering a crash when trying to serialize certain model outputs..."
}
Dataset Creation
The dataset was created by collecting issues via the GitHub REST API using the endpoint:
https://api.github.com/repos/pytorch/pytorch/issues
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