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chore(train-deps): bump the train-minor-and-patch group in /tools/train with 6 updates - #4

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chore(train-deps): bump the train-minor-and-patch group in /tools/train with 6 updates#4
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Bumps the train-minor-and-patch group in /tools/train with 6 updates:

Package From To
torch 2.9.1 2.13.0
numpy 2.3.4 2.5.1
onnx 1.19.1 1.22.0
onnxruntime 1.23.2 1.28.0
scikit-learn 1.7.2 1.9.0
tqdm 4.67.1 4.70.0

Updates torch from 2.9.1 to 2.13.0

Release notes

Sourced from torch's releases.

PyTorch 2.13.0 Release Notes

Highlights

For more details about these highlighted features, you can look at the release blogpost. Below are the full release notes for this release.

Tracked Regressions

ROCm wheels break torch.compile on CPU in environments without a GPU

Running a torch==2.13.0+rocm7.2 wheel in an environment where no GPU is available (torch.cuda.is_available() is False) breaks torch.compile on the CPU path: the first compile raises RuntimeError: Can't detect vectorized ISA for CPU (#189194). This is a regression from torch==2.12.1+rocm7.2, which compiles CPU code fine (detecting e.g. VecAVX2) in the same setup. The 2.13 ROCm wheel appears to rely on something present in the ROCm builder image to detect the CPU vectorized ISA, so it works when run on a ROCm image but fails on a plain CPU-only image.

Workaround: run the +rocm wheel on a ROCm image, or install a standard CPU/CUDA build for GPU-less environments.

Backwards Incompatible Changes

  • Stop building CPython 3.13t (free-threaded) binaries (#182951)

    Upstream pypa/manylinux removed CPython 3.13t (free-threaded) on 2026-05-07, because 3.13t was experimental and has been superseded by the now-non-experimental CPython 3.14t. As a result, PyTorch 2.13 no longer ships cp313t wheels (Linux, Triton, and related artifacts). Users on the free-threaded interpreter should move to Python 3.14t.

    PyTorch 2.12:

    # cp313t (free-threaded 3.13) wheels were available
python3.13t -m pip install torch

    PyTorch 2.13:

... (truncated)

Commits
  • cf30153 [release/2.13] Strip +PTX from CUDA arch list on release/RC builds (#188914) ...
  • 3e3e24b [release/2.13] Restrict cuda-bindings to Python < 3.15 for CUDA 12.9 builds (...
  • 7986b06 [release/2.13] Bump binary build timeout 280 -> 400 minutes (#188551)
  • 0bdbc26 [release/2.13] Add CUDA 12.9 to TORCH_CUDA_ARCH_LIST tables (#188443)
  • 9cabb45 [release/2.13] Update manywheel docker image pin to 78e737ad (#188409)
  • 78e737a [release/2.13] Revert "Tighten generalized scatter graph target (#184075)" (#...
  • 0bb9b5b [release/2.13] Revert "dynamo: round-trip torch.cuda.stream ctx mgr across gr...
  • aaac2bf [release/2.13] Revert "[Reland] Port D104346887/PR 182675 for index_add fast ...
  • 9330813 Fix build_with_debinfo.py broken by CONFIGURE_DEPENDS globbing (#188192)
  • 4e077a7 Remove setuptools upper bound (#188190)
  • Additional commits viewable in compare view

Updates numpy from 2.3.4 to 2.5.1

Release notes

Sourced from numpy's releases.

v2.5.1 (July 4, 2026)

NumPy 2.5.1 Release Notes

The NumPy 2.5.1 is a patch release that fixes bugs discovered after the 2.5.0 release. The most noticeable is the fix is to the numpy datetime cython API which should allow downstream to support NumPy versions older than 2.5. Preparation for Python 3.15 continues along with typing improvements.

This release supports Python versions 3.12-3.14

Changes

  • The minimum supported GCC version has been updated from 9.3.0 to 10.3.0

    (gh-31843)

Contributors

A total of 10 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

  • Adhyan Gupta +
  • Ankit Ahlawat
  • Charles Harris
  • Iason Krommydas
  • Joren Hammudoglu
  • Kumar Aditya
  • Nathan Goldbaum
  • Sebastian Berg
  • Ties Jan Hefting +
  • Vineet Kumar

Pull requests merged

A total of 20 pull requests were merged for this release.

  • #31707: MAINT: Prepare 2.5.x for further development
  • #31721: CI: fix new cython-lint errors (#31711)
  • #31723: MAINT: Update meson to match main
  • #31729: TST: use setup-sde instead of curl to get SDE binaries (#31727)
  • #31829: BUG: Relax finfo to be easier accessible for all user dtypes...
  • #31831: TYP: Fix flatiter.__next__ return type for object_ and...
  • #31832: BUG: avoid deadlocks using NpyString API (#31682)
  • #31833: BUG: fix out array leak in reduceat and accumulate when dtype...
  • #31835: BUG: fix numpy datetime cython APIs to be compatible with older...
  • #31836: TYP: Fix incorrect dtype inference of asarray([]) (#31732)
  • #31837: TYP: Fix np.ma.masked_array 2.5.0 regression
  • #31838: FIX: Refactor error handling in array_setstate to prevent typecode...
  • #31839: TST: xfail multithreaded BLAS test more generously
  • #31840: MAINT: Rename subroutine for crackfortran tests

... (truncated)

Changelog

Sourced from numpy's changelog.

This is a walkthrough of the NumPy 2.4.0 release on Linux, which will be the first feature release using the numpy/numpy-release <https://github.com/numpy/numpy-release>__ repository.

The commands can be copied into the command line, but be sure to replace 2.4.0 with the correct version. This should be read together with the :ref:general release guide <prepare_release>.

Facility preparation

Before beginning to make a release, use the requirements/*_requirements.txt files to ensure that you have the needed software. Most software can be installed with pip, but some will require apt-get, dnf, or whatever your system uses for software. You will also need a GitHub personal access token (PAT) to push the documentation. There are a few ways to streamline things:

  • Git can be set up to use a keyring to store your GitHub personal access token. Search online for the details.

Prior to release

Add/drop Python versions

When adding or dropping Python versions, multiple config and CI files need to be edited in addition to changing the minimum version in pyproject.toml. Make these changes in an ordinary PR against main and backport if necessary. We currently release wheels for new Python versions after the first Python RC once manylinux and cibuildwheel support that new Python version.

Backport pull requests

Changes that have been marked for this release must be backported to the maintenance/2.4.x branch.

Update 2.4.0 milestones

Look at the issues/prs with 2.4.0 milestones and either push them off to a later version, or maybe remove the milestone. You may need to add a milestone.

Check the numpy-release repo

... (truncated)

Commits
  • 5e1d03f Merge pull request #31863 from charris/prepare-2.5.1
  • ad0b66b REL: Prepare for the NumPy 2.5.1 release.
  • 9df8516 Merge pull request #31858 from charris/backport-31688
  • 4dee265 Merge pull request #31857 from charris/backport-31775
  • dc8d553 Merge pull request #31856 from charris/backport-31846
  • 67cb4a8 fix:Signed integer overflow in datetime.c (#31688)
  • baa2589 TST: Clean up imports, formatting, and assertions
  • 2fe5ba4 TEST: Refactor tests to use np.testing.assert_raises_regex per review
  • bb46581 MAINT: Remove deprecated Python recursion fix
  • 8f34214 MAINT: Move SeedSequence recursion guard to C-layer and add tests
  • Additional commits viewable in compare view

Updates onnx from 1.19.1 to 1.22.0

Release notes

Sourced from onnx's releases.

v1.22.0

ONNX v1.22.0 is now available with exciting new features! We would like to thank everyone who contributed to this release! Please visit onnx.ai to learn more about ONNX and associated projects.

What's Changed

Breaking Changes and Deprecations

Spec and Operator

Two new operators LinearAttention-27 and CausalConvWithState-27 were introduced.

Reference Implementation

Utilities and Tools

Build, CI and Tests

... (truncated)

Commits

Updates onnxruntime from 1.23.2 to 1.28.0

Release notes

Sourced from onnxruntime's releases.

ONNX Runtime v1.28.0

Announcements & Breaking Changes

  • Upgraded to ONNX 1.22.0 and protobuf 6.33.5 (#28754, #29606, #28967). Graph optimizer opset version checks were updated accordingly (#28966).
  • cuDNN and cuFFT are now optional at runtime for the CUDA EP, and nvrtc is no longer linked, which significantly reduces the required CUDA redistributable footprint (#29252, #29808, #29705, #29620).
  • An experimental C/C++ API surface was introduced. OrtModelPackageApi now lives in the experimental C API and may change in future releases (#28746, #29142, #28990).
  • Deprecated / removed:
    • SkipLayerNorm strict mode is deprecated (#29388).
    • The TensorRT fused causal attention kernels were removed from the CUDA EP (#29143).
    • The dynamic WGSL generator (duktape/Node) path was removed in favor of the Python wgsl-gen implementation (#29141, #28355).
    • CUDA_QUANT_PREPROCESS is off by default (#29687).
  • NPM packages are now published from the CUDA 13 pipeline (#28773).
  • The CUDA 12.8 package architecture list was refreshed for this release (#29711).

Security Fixes

Memory safety & input validation

  • Hardened the ORT FlatBuffer model loader against malformed buffers, and removed now-redundant table offset validation (#28186, #29068)
  • Fixed type confusion in raw-pointer bind_input causing an out-of-bounds write (#28839)
  • Fixed out-of-bounds pointer in TensorAt for sub-byte packed types (#28973)
  • Fixed arbitrary memory read, out-of-bounds dereference, and other OOB accesses in kernels (#28991, #29011, #29012, #29014)
  • Validated Col2Im inputs to prevent heap over-read (#28706)
  • Hardened CropAndResize against malformed crop_size tensors (#28766)
  • Validated BeamSearch vocab_size against logits width (#28774)
  • Fixed bounds in WhisperDecoderSubgraph::CreateInitialFeeds (#29239)
  • Validated SparseAttention CSR indices/key lengths and rejected zero-dimension block_row_indices (#29015, #29242)
  • Clamped derived sequence lengths and KV-cache index in CUDA GroupQueryAttention, and fixed a CPU GQA out-of-bounds read in the past-KV buffer (#29240, #29447)
  • Clamped 1D attention mask_index to valid bounds (#29449)
  • Validated MaxpoolWithMask kernel rank against input spatial rank (#29253)
  • Rejected CUDA BERT EmbedLayerNorm/SkipLayerNorm shapes exceeding 32-bit output indexing (#29264)
  • Fixed the optional-output guard in DecoderAttention/MultiHeadAttention shape inference and negative-axis handling in ExpandDims shape inference (#29268, #29448)
  • Fixed TreeEnsemble target id validation and added input validation to LinearClassifier (#29293, #29060)
  • Fixed DynamicQuantizeLSTM zero-point/scale validation typos (#29462)
  • Handled non-trivially-copyable types in Loop/Scan output concatenation (#29397)
  • Normalized bool tensor raw_data to {0, 1} on unpack (#29238)
  • Addressed hardening gaps in Resize, PadFusion, and LoRA handling (#28779, #28780, #28801)
  • Fixed unbounded lifetime on WithOutputTensor in the Rust bindings (#29251)

Integer overflow & allocation size

  • Guarded MlasConvPrepare working-buffer products and ConvTranspose pad computation with SafeInt (#29444, #29446)
  • Fixed signed-int overflow in SamplingState::Init that could cause a heap buffer overflow (#29443)
  • Hardened QMoE against integer overflow and partial K tiles (#29067)
  • Validated B/scales/zero-points shape in MatMulNBits::PrePack (#29445)
  • Pre-checked ConstantOfShape output size against the input initializer before constant folding (#28751)
  • Fixed integer overflow in RKNPU implicit bias allocation (#29249)
  • Fixed WebGPU out-of-bounds reads in Pad (int64/int32 truncation), Slice, and GatherBlockQuantized (#28721, #28704, #28718)

Supply chain & tooling

... (truncated)

Commits
  • da9b5e3 Fix Windows zip artifact to include .inc header files (#29874)
  • 45de2a8 Fix NuGet packaging to include .inc files alongside .h headers (#29868)
  • 0368187 ORT 1.28.0 release cherry-pick round 2 (#29821)
  • e1bbb64 ORT 1.28.0 release cherry-pick round 1 (#29771)
  • a06675e Fix web e2e (npm/vite) and Python DML CI pipelines (#29609)
  • c4f1961 Bump onnx to 1.22.0 and protobuf to 6.33.5 to fix security CVEs (#29606)
  • e0ad071 [CUDA] Enable native SM90, block_size=32, and fused bias for fpA_intB MatMulN...
  • a1fc71e [CUDA] Fix QMoE profiler cross-stream race and CUDA-graph-capture safety (#29...
  • 5eb4aee Fix CustomOp forward compatibility: cap version instead of rejecting (#29574)
  • 7a12371 adjusts conv kernel to use get/set by offset helpers (#29463)
  • Additional commits viewable in compare view

Updates scikit-learn from 1.7.2 to 1.9.0

Release notes

Sourced from scikit-learn's releases.

Scikit-learn 1.9.0

We're happy to announce the 1.9.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_9_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.9.html

This release adds narwhals as a new dependency that will help to improve dataframe interoperability across the project.

This version supports Python versions 3.11 to 3.14.

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

Release 1.8.0

We're happy to announce the 1.8.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_8_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.8.html

This version supports Python versions 3.11 to 3.14 and features support of free-threaded CPython.

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn
Commits
  • 77def0e trigger wheel builder [cd build]
  • ee7c0b0 generate changelog
  • 3d7fb04 bump version
  • 8954e7b DOC Release highlights for 1.9 (#34147)
  • 73a3eab Fix: Array-API - avoid failing for numpy fit + predict with sparse or array-l...
  • 8839aae DOC Thread-safety requirement for open_listener message consumer callback (#3...
  • 4d2476a DOC Refactor array API docs page (#34054)
  • f9f812f 🔒 🤖 CI Update lock files for scipy-dev CI build(s) 🔒 🤖 ...
  • d779dc3 🔒 🤖 CI Update lock files for free-threaded CI build(s) 🔒 :rob...
  • 6a03cf0 🔒 🤖 CI Update lock files for array-api CI build(s) 🔒 🤖 ...
  • Additional commits viewable in compare view

Updates tqdm from 4.67.1 to 4.70.0

Release notes

Sourced from tqdm's releases.

tqdm v4.70.0 stable

  • contrib.concurrent: major improvements
    • support process_map(mp_context, max_tasks_per_child), thread_map(thread_name_prefix) (#1265)
    • fix total based on shortest iterable length (#1473)
    • use default max_workers (#1543 <- #1530, #1518)
    • support timeout, buffersize (#1576)
    • improve ETA (#1708 <- #1161)
    • update as_completed (#1709 <- #1565)
    • add tqdm.concurrent.intepreter_map (#1777)
  • asyncio: support iterables with only __aiter__ (#1714 <- #1686)
  • support reset(float("inf")) (#1783 <- #1781, #651)
  • framework: test & reduce wheel size (#1782)

tqdm v4.69.1 stable

tqdm v4.69.0 stable

  • add tqdm.asyncio.gather(..., return_exceptions=False) (#1776, #1671 <- #1286)
  • misc minor framework updates
    • bump workflow actions & pre-commit hooks

tqdm v4.68.4 stable

tqdm v4.68.3 stable

  • utils: delay os.get_terminal_size (#1763 <- #1760)
  • autonotebook: support QtConsole, Spyder, JupyterLite (#1763, #1628, #1559 <- #1283, #1098, #512)
  • minor docs updates
    • fix typo (#1762)
    • use git-fame
  • misc minor framework updates
    • fix & update CI build
    • pre-commit: add docs & metadata generation
    • move tox.ini -> pyproject.toml, move tox-gh-actions -> tox-gh
    • add Python 3.14, drop 3.7 support

tqdm v4.68.2 stable

  • revert accidental change to ascii default (fixes #1760)
    • UnicodeEncodeError: 'charmap' codec can't encode characters in position 6-7: character maps to <undefined> can be fixed by installing tqdm!=4.68.0,!=4.68.1
  • misc docs updates
    • fix links
    • replace stray rst -> md syntax
    • consistent "progress bar" terminology (#1737)

... (truncated)

Commits
  • 96f2e60 Merge pull request #1777 from shermansiu/feat/interpreter-pool
  • c27393e misc tidy
  • 061c623 Disable tqdm.monitor_interval for subinterpreters because they do not have ...
  • 9fc160b Update how we check for interpreter_map support in the tests
  • b42463a Ensure that subinterpreters can import tqdm while unpickling the initializer
  • 16d5486 Add support for nested progress bars
  • 9f5890f Add initial implementation for interpreter_map
  • 321f920 Merge pull request #1783 from LuShadowX/reset-inf-total
  • 4664b57 minor tidy
  • 426a098 Treat inf total as unknown in reset() too
  • Additional commits viewable in compare view

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@dependabot
chore(train-deps): bump the train-minor-and-patch group
ba5007a 
Bumps the train-minor-and-patch group in /tools/train with 6 updates:

| Package | From | To |
| --- | --- | --- |
| [torch](https://github.com/pytorch/pytorch) | `2.9.1` | `2.13.0` |
| [numpy](https://github.com/numpy/numpy) | `2.3.4` | `2.5.1` |
| [onnx](https://github.com/onnx/onnx) | `1.19.1` | `1.22.0` |
| [onnxruntime](https://github.com/microsoft/onnxruntime) | `1.23.2` | `1.28.0` |
| [scikit-learn](https://github.com/scikit-learn/scikit-learn) | `1.7.2` | `1.9.0` |
| [tqdm](https://github.com/tqdm/tqdm) | `4.67.1` | `4.70.0` |


Updates `torch` from 2.9.1 to 2.13.0
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v2.9.1...v2.13.0)

Updates `numpy` from 2.3.4 to 2.5.1
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](numpy/numpy@v2.3.4...v2.5.1)

Updates `onnx` from 1.19.1 to 1.22.0
- [Release notes](https://github.com/onnx/onnx/releases)
- [Changelog](https://github.com/onnx/onnx/blob/main/docs/Changelog-ml.md)
- [Commits](onnx/onnx@v1.19.1...v1.22.0)

Updates `onnxruntime` from 1.23.2 to 1.28.0
- [Release notes](https://github.com/microsoft/onnxruntime/releases)
- [Changelog](https://github.com/microsoft/onnxruntime/blob/main/docs/ReleaseManagement.md)
- [Commits](microsoft/onnxruntime@v1.23.2...v1.28.0)

Updates `scikit-learn` from 1.7.2 to 1.9.0
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@1.7.2...1.9.0)

Updates `tqdm` from 4.67.1 to 4.70.0
- [Release notes](https://github.com/tqdm/tqdm/releases)
- [Commits](tqdm/tqdm@v4.67.1...v4.70.0)

---
updated-dependencies:
- dependency-name: torch
  dependency-version: 2.13.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: train-minor-and-patch
- dependency-name: numpy
  dependency-version: 2.5.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: train-minor-and-patch
- dependency-name: onnx
  dependency-version: 1.22.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: train-minor-and-patch
- dependency-name: onnxruntime
  dependency-version: 1.28.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: train-minor-and-patch
- dependency-name: scikit-learn
  dependency-version: 1.9.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: train-minor-and-patch
- dependency-name: tqdm
  dependency-version: 4.70.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: train-minor-and-patch
...

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@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Aug 5, 2026
@github-actions
github-actions Bot enabled auto-merge (rebase) August 5, 2026 18:44
@github-actions
github-actions Bot merged commit b6d4ee7 into main Aug 5, 2026
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@dependabot
dependabot Bot deleted the dependabot/pip/tools/train/train-minor-and-patch-cc7c6037c2 branch August 5, 2026 18:44
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