chore(deps)(deps): bump the python-versions group across 1 directory with 4 updates

[dependabot]

Bumps the python-versions group with 4 updates in the / directory: huggingface-hub, onnxruntime, nvidia-cudnn-cu12 and onnxruntime-gpu.

Updates huggingface-hub from 1.30.0 to 1.31.0

Release notes

Sourced from huggingface-hub's releases.

[v1.31.0] Custom labels for Sandboxes, More resilient downloads and more

🏷️ Custom labels for Sandboxes

Dedicated sandboxes now accept custom labels, attached to the underlying Job. This is useful for cost attribution, bookkeeping, or finding and reconnecting to the sandboxes created by a given controller run. Labels use the same -l / --label KEY=VALUE syntax as hf jobs run. They are merged with the labels the SDK uses internally, and invalid or reserved labels are rejected before a billable Job is started. Pool-based sandboxes are unchanged: custom labels are only accepted for dedicated sandboxes.

>>> from huggingface_hub import Sandbox
>>> sandbox = Sandbox.create(image="python:3.12", labels={"controller-run": "run-42"})

hf sandbox create --label controller-run=run-42 --label team=data-infra

• [Sandbox] Support custom Job labels by @​Wauplin in #4824

📥 More resilient downloads

A batch of fixes makes downloads more robust to unusual server responses, network hiccups and concurrent usage:

• A timeout while waiting for the response headers of a streamed download is now retried and resumed like a body read failure, instead of escaping http_get() while retries remain.

• Regular HTTP downloads no longer fail when the HEAD response has no Content-Length. The file size is validated against the GET response when available.

• snapshot_download now writes the refs/ cache file atomically, reusing the logic already used by hf_hub_download. This fixes a long-standing race when many concurrent snapshot_download calls target the same repo (seen in vLLM / llm-compressor).

• hf download --dry-run --local-dir ... no longer copies files from the Hub cache into the destination. On large files and slow disks this looked like a hang and could leave an incomplete file behind.

• [Download] Share retry handling for stream entry and body failures by @​Wauplin in #4826

• [Download] Tolerate missing HEAD Content-Length by @​Wauplin in #4805

• [Download] Write cache ref file atomically in snapshot_download by @​Wauplin in #4829

• [Download] Prevent cached file copies during local-dir dry runs by @​wakamex in #4817

🔌 httpx re-exported for library integrators

huggingface_hub now re-exports the HTTP library it uses as huggingface_hub.utils.httpx. Libraries built on top of huggingface_hub that need httpx types or exceptions (typically to catch errors) should import it from there rather than importing httpx directly. v1.x is built on httpx, and v2.x will move to its successor httpx2, so importing through huggingface_hub.utils keeps your code compatible with both. This is only for types and exceptions: to make requests to the Hub, keep using get_session().

from huggingface_hub.utils import httpx
try:
...
except httpx.HTTPError:
...

📚 Documentation: Utilities — The httpx module

• [httpx migration] Expose httpx as a huggingface_hub submodule by @​Wauplin in #4803

🔒 Security

HfFileSystem.get() now validates remote filenames before writing anything locally. A server-side filename such as folder/..\..\outside.txt could previously escape the destination directory on Windows during a recursive download. The same check already protected hf_hub_download, snapshot_download and bucket sync. Unsafe filenames now raise ValueError on all platforms, including when downloading to an explicitly named file or a file object.

... (truncated)

Commits

• 495b17c Release: v1.31.0
• 0f50db0 Release: v1.31.0.rc1
• d592df8 Revert "[Jobs] Add network groups to hf jobs run (#4833)"
• 3c08b69 Release: v1.31.0.rc0
• f148666 [CLI] Fix truncated command descriptions in the CLI reference (#4849)
• c4f076c (LFS)Fix SliceFileObj.iter yielding only the first 4MB chunk (#4844)
• 22fe960 Fix dotenv parser truncating unquoted values containing '#' (#4842)
• 6cae778 [Jobs] Add network groups to hf jobs run (#4833)
• 063b37b [CLI] Raise explicit error for shell-script extensions on Windows (#4846)
• b9c14d9 [Download] Write cache ref file atomically in snapshot_download (#4829)
• Additional commits viewable in compare view

Updates onnxruntime from 1.29.0 to 1.30.0

Release notes

Sourced from onnxruntime's releases.

ONNX Runtime v1.30.0

ONNX Runtime 1.30.0 expands generative AI inference, improves CPU and GPU performance, adds Go bindings, and strengthens runtime reliability. These notes cover changes since ONNX Runtime 1.29.1.

Highlights

• Expanded CUDA inference support with variable-length causal convolution for continuous batching, speculative decoding in paged XQA, and INT4 paged KV caches with per-channel scales (#32168, #32340, #32515).
• Improved WebGPU PagedAttention, added GPT-OSS support and INT8 KV-cache block quantization, and extended convolution optimizations (#31727, #32277, #32284, #32420).
• Added fused CPU LinearAttention kernels for AVX-512, Arm64 NEON, and SVE, plus AVX2 LayerNorm/RMSNorm acceleration (#31674, #31973, #32178, #32356).
• Added Go bindings for the ONNX Runtime C API and DeepSeek Engram contrib operators (#29615, #32268).

Announcements & Compatibility

• FP4 QMoE kernels are now enabled by default in CUDA builds, with Windows build support added in this release. Source builds can opt out with -Donnxruntime_USE_FP4_QMOE=OFF (#32096, #32163).
• CUDA fpA-intB builds now default to a compact kernel set for FP16 activations, INT4/INT8 weights, scale-only quantization, and block_size=32. Set -Donnxruntime_USE_FPA_INTB_GEMM_FULL=ON when building from source to retain the full kernel set, including BF16, zero-point, bias, larger-block-size, and native Hopper variants (#32324).
• CPU FP16 Gemm and MatMul execution is gated on hardware acceleration. CPU-assigned FP16 nodes without a matching kernel now fall back to FP32 (#32301, #32197).
• WebGPU plugin EP packaging now supports Linux AArch64. Plugin versions were advanced to WebGPU 0.4.0 and CUDA 0.2 (#32287, #31960, #31970).

Security & Reliability

Model Loading, Memory, and Input Validation

• Limited nested model-graph depth and canonicalized external-data locations to harden model loading (#32344, #32135).
• Added checked rounding for BFC arena allocations and fixed prepacked-weight reference lifetimes (#32010, #32040).
• Strengthened shape, rank, and parameter validation for Split, Scan, GatherND, ScatterND, SpaceToDepth/DepthToSpace, Crop, Conv, Normalizer, and pooling (#29461, #31668, #32034, #32039, #32076, #32157, #32160, #32161, #32345, #32349).
• Hardened generation and attention input handling, including attention-attribute narrowing, BifurcationDetector inputs, generation subgraph shapes, and QEmbed segment inputs. BeamSearch buffer expansion now uses dynamic shape storage (#31648, #31701, #32009, #32078, #32144).
• Validated TreeEnsemble node references and bounded subtree comparison, rejected non-finite CPU RoiAlign coordinates, and required ImageScaler bias to match the channel count (#32031, #32043, #32011, #32002).
• Added an allowlist of safe LoRA adapter parameter data types, validated MatMulFpQ4 shape inputs, and checked MLAS blockwise quantization/dequantization index ranges (#31682, #32032, #32007).

GPU Bounds and Resource Lifetimes

• Hardened CUDA indexing and buffer-size arithmetic in MatMulNBits, RemovePadding, RotaryEmbedding, SparseAttention, Whisper beam search, NMS, QDQ, and GatherElements (#31643, #31994, #31995, #31996, #31998, #32014, #32029, #32030).
• Fixed overflow in CUDA reduction scans and Softmax offset arithmetic, and handled zero-sized outputs in CUDA random-generator kernels (#32137, #32330, #31997).
• Fixed CUDA MultiHeadAttention shared-cache scratch lifetimes and kept CudaAsyncBuffer staging storage alive across CUDA graph replay (#31968, #32121).
• Fixed WebGPU out-of-bounds subgroup-matrix loads for partial tiles, zero-initialized writable device-allocator buffers, and rejected foreign GPU handles in built-in data transfers (#32364, #32063, #32317).

Dependencies and Tooling

• Upgraded Protobuf to 33.6 and refreshed Python documentation dependencies, including an ONNX security-related update (#29906, #32190, #32424).
• Updated JavaScript dependencies including js-yaml, joi, fast-uri, and the Next.js end-to-end fixture (#32397, #32486, #32488, #32505, #32508).
• Pinned GitHub Actions to full-length commit SHAs and strengthened packaging infrastructure with authenticated package feeds and NPM network isolation (#32176, #32005, #32440).

New Features

Core APIs & Runtime

• Added Go bindings for the ONNX Runtime C API (#29615).
• Extended memory importing with host-pointer support and added access to preallocated outputs through KernelContext::GetPreallocatedOutput (#29726, #32089).
• Added packed-attention workspace recipes and estimates, and made workspace input-shape handling aware of optional inputs (#32283, #32321, #32312).
• Added DeepSeek Engram contrib operators, EngramGate and NGramHashMapping, and expanded kernel coverage for Qwen-3.5 operators (#32268, #32106).

... (truncated)

Commits

• f2c39fe [CUDA] Add INT4 paged KV cache with per-channel scales (#32515)
• 5894ba8 Add portable random-access file reads to Env (#32503)
• a2ee3eb Fix CUDA plugin device discovery on WSL (#32517)
• b652e59 [WebGPU] Prepack Conv weights for the im2col-matmul path (#32420)
• 0f0f29f Get rid of spurious warning about not being able to find spectre mitigation (...
• 23dd651 Register ONNX schemas only when static registration is disabled (#32353)
• 33af5d3 Release external data loaders after graph initialization (#32502)
• 2e3c24d Clarify external initializer and EP context path interaction (#32442)
• e76036b [CUDA] Pin FP8 GEMV residency for grids just past two blocks per SM (#32433)
• 82583c5 Add session option for a BNHS GroupQueryAttention Value cache layout (#32139)
• Additional commits viewable in compare view

Updates nvidia-cudnn-cu12 from 9.25.1.1 to 9.26.0.51

Updates onnxruntime-gpu from 1.29.0 to 1.30.0

Release notes

Sourced from onnxruntime-gpu's releases.

ONNX Runtime v1.30.0

ONNX Runtime 1.30.0 expands generative AI inference, improves CPU and GPU performance, adds Go bindings, and strengthens runtime reliability. These notes cover changes since ONNX Runtime 1.29.1.

Highlights

• Expanded CUDA inference support with variable-length causal convolution for continuous batching, speculative decoding in paged XQA, and INT4 paged KV caches with per-channel scales (#32168, #32340, #32515).
• Improved WebGPU PagedAttention, added GPT-OSS support and INT8 KV-cache block quantization, and extended convolution optimizations (#31727, #32277, #32284, #32420).
• Added fused CPU LinearAttention kernels for AVX-512, Arm64 NEON, and SVE, plus AVX2 LayerNorm/RMSNorm acceleration (#31674, #31973, #32178, #32356).
• Added Go bindings for the ONNX Runtime C API and DeepSeek Engram contrib operators (#29615, #32268).

Announcements & Compatibility

• FP4 QMoE kernels are now enabled by default in CUDA builds, with Windows build support added in this release. Source builds can opt out with -Donnxruntime_USE_FP4_QMOE=OFF (#32096, #32163).
• CUDA fpA-intB builds now default to a compact kernel set for FP16 activations, INT4/INT8 weights, scale-only quantization, and block_size=32. Set -Donnxruntime_USE_FPA_INTB_GEMM_FULL=ON when building from source to retain the full kernel set, including BF16, zero-point, bias, larger-block-size, and native Hopper variants (#32324).
• CPU FP16 Gemm and MatMul execution is gated on hardware acceleration. CPU-assigned FP16 nodes without a matching kernel now fall back to FP32 (#32301, #32197).
• WebGPU plugin EP packaging now supports Linux AArch64. Plugin versions were advanced to WebGPU 0.4.0 and CUDA 0.2 (#32287, #31960, #31970).

Security & Reliability

Model Loading, Memory, and Input Validation

• Limited nested model-graph depth and canonicalized external-data locations to harden model loading (#32344, #32135).
• Added checked rounding for BFC arena allocations and fixed prepacked-weight reference lifetimes (#32010, #32040).
• Strengthened shape, rank, and parameter validation for Split, Scan, GatherND, ScatterND, SpaceToDepth/DepthToSpace, Crop, Conv, Normalizer, and pooling (#29461, #31668, #32034, #32039, #32076, #32157, #32160, #32161, #32345, #32349).
• Hardened generation and attention input handling, including attention-attribute narrowing, BifurcationDetector inputs, generation subgraph shapes, and QEmbed segment inputs. BeamSearch buffer expansion now uses dynamic shape storage (#31648, #31701, #32009, #32078, #32144).
• Validated TreeEnsemble node references and bounded subtree comparison, rejected non-finite CPU RoiAlign coordinates, and required ImageScaler bias to match the channel count (#32031, #32043, #32011, #32002).
• Added an allowlist of safe LoRA adapter parameter data types, validated MatMulFpQ4 shape inputs, and checked MLAS blockwise quantization/dequantization index ranges (#31682, #32032, #32007).

GPU Bounds and Resource Lifetimes

• Hardened CUDA indexing and buffer-size arithmetic in MatMulNBits, RemovePadding, RotaryEmbedding, SparseAttention, Whisper beam search, NMS, QDQ, and GatherElements (#31643, #31994, #31995, #31996, #31998, #32014, #32029, #32030).
• Fixed overflow in CUDA reduction scans and Softmax offset arithmetic, and handled zero-sized outputs in CUDA random-generator kernels (#32137, #32330, #31997).
• Fixed CUDA MultiHeadAttention shared-cache scratch lifetimes and kept CudaAsyncBuffer staging storage alive across CUDA graph replay (#31968, #32121).
• Fixed WebGPU out-of-bounds subgroup-matrix loads for partial tiles, zero-initialized writable device-allocator buffers, and rejected foreign GPU handles in built-in data transfers (#32364, #32063, #32317).

Dependencies and Tooling

• Upgraded Protobuf to 33.6 and refreshed Python documentation dependencies, including an ONNX security-related update (#29906, #32190, #32424).
• Updated JavaScript dependencies including js-yaml, joi, fast-uri, and the Next.js end-to-end fixture (#32397, #32486, #32488, #32505, #32508).
• Pinned GitHub Actions to full-length commit SHAs and strengthened packaging infrastructure with authenticated package feeds and NPM network isolation (#32176, #32005, #32440).

New Features

Core APIs & Runtime

• Added Go bindings for the ONNX Runtime C API (#29615).
• Extended memory importing with host-pointer support and added access to preallocated outputs through KernelContext::GetPreallocatedOutput (#29726, #32089).
• Added packed-attention workspace recipes and estimates, and made workspace input-shape handling aware of optional inputs (#32283, #32321, #32312).
• Added DeepSeek Engram contrib operators, EngramGate and NGramHashMapping, and expanded kernel coverage for Qwen-3.5 operators (#32268, #32106).

... (truncated)

Commits

• f2c39fe [CUDA] Add INT4 paged KV cache with per-channel scales (#32515)
• 5894ba8 Add portable random-access file reads to Env (#32503)
• a2ee3eb Fix CUDA plugin device discovery on WSL (#32517)
• b652e59 [WebGPU] Prepack Conv weights for the im2col-matmul path (#32420)
• 0f0f29f Get rid of spurious warning about not being able to find spectre mitigation (...
• 23dd651 Register ONNX schemas only when static registration is disabled (#32353)
• 33af5d3 Release external data loaders after graph initialization (#32502)
• 2e3c24d Clarify external initializer and EP context path interaction (#32442)
• e76036b [CUDA] Pin FP8 GEMV residency for grids just past two blocks per SM (#32433)
• 82583c5 Add session option for a BNHS GroupQueryAttention Value cache layout (#32139)
• Additional commits viewable in compare view

[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud