My proposal here is to use GitHub Dependabot to make sure that `transformers` version used in CI are always up-to-date. To achieve this, this PR does 2 things:
1. Pin `transformers` version across all CI jobs to only one place at `.ci/docker/ci_commit_pins/huggingface.txt`. This file is now a regular pip requirements instead of a pinned commit text. There isn't any need to pin `transformers` to a specific commit and the file already refers to a stable version `v4.54.0`
2. Create `.github/dependabot.yml` to config the bot to update `transformers` automatically when there is a new version. Those labels will ensure that the right reviewers from torch.compile and Dev Infra are notified. I'm not sure how to test this out in PR, but it feels ok to land and test this in main. If this works, we should see a PR to update `v4.54.0` to the current latest `v4.55.0`
### Reference
https://docs.github.com/en/code-security/dependabot/working-with-dependabot/dependabot-options-reference
Pull Request resolved: https://github.com/pytorch/pytorch/pull/160635
Approved by: https://github.com/ZainRizvi
Fixes https://github.com/pytorch/pytorch/issues/160689
The current torchao 0.12.0 doesn't work with transformers 4.54.0 and ends up with this error:
```
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/transformers/models/albert/modeling_albert.py", line 37, in <module>
from ...modeling_utils import PreTrainedModel
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/transformers/modeling_utils.py", line 51, in <module>
from torchao.quantization import Int4WeightOnlyConfig
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/__init__.py", line 41, in <module>
from torchao.quantization import (
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/quantization/__init__.py", line 6, in <module>
from .autoquant import (
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/quantization/autoquant.py", line 11, in <module>
from torchao.dtypes import (
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/dtypes/__init__.py", line 1, in <module>
from . import affine_quantized_tensor_ops
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/dtypes/affine_quantized_tensor_ops.py", line 38, in <module>
from torchao.dtypes.uintx.dyn_int8_act_int4_wei_cpu_layout import (
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/dtypes/uintx/__init__.py", line 7, in <module>
from .dyn_int8_act_int4_wei_cpu_layout import (
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/dtypes/uintx/dyn_int8_act_int4_wei_cpu_layout.py", line 320, in <module>
from ...prototype.inductor.fx_passes import register_da8w4_concat_linear_cpu_pass
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/prototype/inductor/fx_passes/__init__.py", line 2, in <module>
from .int8_sdpa_fusion import _int8_sdpa_init
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/prototype/inductor/fx_passes/int8_sdpa_fusion.py", line 22, in <module>
from ..int8_sdpa_lowering import register_int8_sdpa # noqa: F401
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1755212960/lib/python3.12/site-packages/torchao/prototype/inductor/int8_sdpa_lowering.py", line 6, in <module>
from torch._inductor.kernel.flex_attention import construct_strides, maybe_realize
ModuleNotFoundError: No module named 'torch._inductor.kernel.flex_attention'
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/160724
Approved by: https://github.com/malfet
# set up vllm build logic
- dockerfile: please notice the dockfile introduced here is only temporary, once we migrate this file to vllm, we will fetch it directly from there
- VllmBuildRunner:
- implement logic to prepare and run vllm build with dockerfile
-
Pull Request resolved: https://github.com/pytorch/pytorch/pull/160089
Approved by: https://github.com/huydhn
ghstack dependencies: #160043
Automatically replaces split with rsplit when relevant and only performs the split up to the first ( or last value). This allows early return of the split function and improve efficiency.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/160107
Approved by: https://github.com/albanD
Before this change there were build+test jobs:
- s89 build+tests
- sm75 build+distributed_test
- sm_75 build+pr_time_benchmark test
This change compiles all 3 builds into one (for 2 architectures) and skips testing sm86 as it never found any new regressions that were not found at the same time on sm89
Pull Request resolved: https://github.com/pytorch/pytorch/pull/159890
Approved by: https://github.com/clee2000, https://github.com/seemethere
When one builds CD docker, all CUDA dependencies must be installed into `/usr/local/cuda/` folder
Test plan: Looks at the binary build logs, for example [here](https://github.com/pytorch/pytorch/actions/runs/16768141521/job/47477380147?pr=159907):
```
2025-08-06T05:58:00.7347471Z -- NVSHMEM_HOME set to: ''
2025-08-06T05:58:00.7348378Z -- NVSHMEM wheel installed at: ''
2025-08-06T05:58:00.7392528Z -- NVSHMEM_HOST_LIB: '/usr/local/cuda/lib64/libnvshmem_host.so'
2025-08-06T05:58:00.7393251Z -- NVSHMEM_DEVICE_LIB: '/usr/local/cuda/lib64/libnvshmem_device.a'
2025-08-06T05:58:00.7393792Z -- NVSHMEM_INCLUDE_DIR: '/usr/local/cuda/include'
2025-08-06T05:58:00.7394252Z -- NVSHMEM found, building with NVSHMEM support
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/159907
Approved by: https://github.com/Skylion007, https://github.com/ngimel
Removes unused docker images from the docker build workflow
Then removes unused definitions in build.sh
The only one I left is the vllm one because I'm pretty sure it's going to be used in the future
I assume everything not mentioned is old and we forgot to remove them
Pull Request resolved: https://github.com/pytorch/pytorch/pull/159171
Approved by: https://github.com/yangw-dev
ROCm inductor benchmark builds failing fbgemm build stage https://ossci-raw-job-status.s3.amazonaws.com/log/46800456622
```
2025-07-27T08:00:32.3443858Z /var/lib/jenkins/pytorch/fbgemm/src/RowWiseSparseAdagradFused.cc:389:18: error: no matching function for call to ‘asmjit::v1_17::x86::Vec::Vec(uint32_t)’
2025-07-27T08:00:32.3444080Z 389 | x86::Xmm partial_sum_xmm(partial_sum_vreg.id());
```
It looks like asmjit fails to build, this seems to be due to submodules of fbgemm not being updated after checking out to new commit.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/159477
Approved by: https://github.com/pruthvistony, https://github.com/eqy
