[dependabot]

Bumps the python group with 5 updates in the / directory:

Package	From	To
supervision	0.30.2	0.30.5
fiftyone	1.21.0	1.22.0
onnx	1.22.0	1.23.0
onnxruntime	1.29.0	1.30.0
ruff	0.16.6	0.16.8

Updates supervision from 0.30.2 to 0.30.5

Release notes

Sourced from supervision's releases.

supervision-0.30.5

0.30.5: Tracking, metrics, and image-drawing correctness fixes

supervision 0.30.5 is a patch release closing 11 correctness and crash bugs across line-crossing tracking, mAR@K scoring, model connectors, key points, and image drawing/loading — no new public API of note, no breaking changes. The most consequential fixes are silent, not crashes: LineZone.trigger miscounted crossings by one per flicker whenever a tracker briefly touched the far side of the line, and MeanAverageRecall scored mAR@K against the wrong predictions when a lower-ranked one fit a target more tightly than one within the top K. The remaining fixes close a hard crash in InferenceSlicer on conflicting slice metadata (plus two related Detections.__eq__ bugs), bring the OpenCV-free fallback backend to parity with OpenCV for rotated videos, CMYK images, transparent/1-bit PNGs, and default JPEG/WebP write quality, fix two drawing bugs that reproduce with OpenCV installed (16-bit draw_image, grayscale IconAnnotator icons), and fix two isolated bugs in KeyPoints.as_detections and plot_images_grid. Every fix ships a regression test.

✨ Spotlights / highlights

sv.LineZone.trigger no longer counts flicker as a crossing

A crossing was confirmed whenever the oldest entry of a minimum_crossing_threshold + 1 frame history differed from every later entry, which never verified the tracker had actually settled on the side it supposedly came from. With minimum_crossing_threshold=2 the side sequence A,A,A,B,A,A,A counted a crossing into A — the side the object never left — so counts drifted by one per flicker, in the wrong direction; three separated flickers gave in_count=3 instead of 0.

line_zone = sv.LineZone(
    start=sv.Point(0, 0), end=sv.Point(0, 100), minimum_crossing_threshold=2
)
# a tracker that flickers to the far side for one frame and back
# no longer registers a phantom crossing; only a sustained crossing counts

Crossings are now measured against the last side a tracker was confirmed on, not against the oldest history entry. Sustained crossings and minimum_crossing_threshold=1 (the default) are unchanged.

sv.metrics.MeanAverageRecall now scores mAR@K from each image's own top K

The matcher pairs predictions to targets by highest IoU, not confidence, so a prediction ranked below K could take a target away from one ranked within it. Adding a low-confidence duplicate that fit a target more tightly than the top prediction actually lowered mAR@1 — one target with a top prediction at IoU 0.71 scored mAR@1 0.5 alone but 0.0 once a second, unrelated prediction at IoU 1.0 and confidence 0.1 was added. Each detection limit now matches only its own top K predictions.

sv.InferenceSlicer no longer crashes when slices disagree on metadata

RF-DETR and inference-package connectors attach a source_image array per slice; any mismatch across slices previously crashed the merge outright. Any metadata key that isn't identical across every slice is now dropped with a one-time warning naming the dropped keys; source_image is reattached afterward as the full input image.

slicer = sv.InferenceSlicer(callback=callback)
detections = slicer(image)  # metadata.source_image is the full input image again

Fixing this also closed two Detections.__eq__ bugs: NaN in a float-array metadata value now compares equal to itself, and a list-valued value against an ndarray-valued one now returns False instead of raising ValueError.

Rotated videos read upright without OpenCV

OpenCV's FFmpeg backend applies a video's display-rotation matrix to decoded frames and to the reported width/height; the OpenCV-free fallback ignored it, so a portrait phone video came back sideways with its width/height swapped.

sv.KeyPoints.as_detections drops invisible key points from the derived box

as_detections stretched each box over every key point that wasn't [0, 0] or non-finite, ignoring visible — unlike with_nms, which already respected it. A pose whose low-confidence joints were predicted off-frame no longer produces an inflated box.

🔄 Migration guide

No breaking changes in this release.

No deprecations or removals landed in 0.30.5 either. All scheduled remove_in markers in the codebase target 0.31.0 and are untouched by this patch release.

... (truncated)

Changelog

Sourced from supervision's changelog.

0.30.5 Sep 22, 2026

• sv.InferenceSlicer no longer raises when slices disagree on metadata (e.g. a source_image NumPy array attached per-slice by RF-DETR/inference-package connectors), which previously crashed the merge outright. A mismatched key is now dropped from the merged result with a SupervisionWarnings warning naming it; source_image is a special case, reattached afterward as the full input image rather than a single slice's tile. Also fixes two related Detections.__eq__ bugs: metadata holding NaN in a float array now compares equal to itself instead of always reading unequal, and comparing a list-valued value against an ndarray-valued one now returns False instead of raising ValueError. (#2596)

• sv.VideoInfo.from_video_path, sv.get_video_frames_generator and sv.process_video now turn a rotated video upright when OpenCV is not installed, as they already do with OpenCV. Phones store portrait clips as landscape frames with the turn recorded in the container's display matrix; the OpenCV-free fallback ignored it, so a portrait video loaded sideways with width and height swapped — models ran on sideways frames and sv.VideoSink saved the output sideways. #2601

• sv.ImageSink and the dataset exports that encode in-memory images now write JPEG and WebP at OpenCV's default quality (JPEG 95, lossless WebP) when OpenCV is not installed, instead of Pillow's defaults (JPEG 75, lossy WebP) — a .jpg came out with visibly stronger compression artifacts (a third of the size for one test frame), and a .webp no longer held the frame's exact pixels. A .webp written by the fallback is now larger than before, since lossless output is larger than the previous lossy default. The fallback's in-memory encoder also now accepts .jpe as a JPEG alias, and .tif/.jp2/.pgm, all four previously rejected with False, None even though file writes already accepted them. #2592

• sv.IconAnnotator and sv.draw_image now draw CMYK JPEG and TIFF images in their real colors when OpenCV is not installed. The fallback returned the four ink channels — cyan, magenta, yellow, black — as if they were blue/green/red/alpha, so an icon drew in the wrong colors, and a CMYK image with no black ink didn't draw at all. #2602

• sv.draw_image now scales a 16-bit PNG down to 8 bits on load instead of blending it straight into the 8-bit scene, which saturated every nonzero channel to 255: a dark gray logo drew white, and a red of 200 drew as 255. Eight-bit images, and images passed as arrays, are unaffected. #2603

• sv.metrics.MeanAverageRecall now scores mAR@K from each image's K most confident predictions alone, instead of matching every prediction first and only then keeping the top K — the matcher pairs by highest IoU, not confidence, so a prediction ranked below K could steal a target from one ranked within it. One target with a top prediction at IoU 0.71 scored mAR@1 0.5 alone but 0.0 once a second, lower-ranked prediction at IoU 1.0 was added; mAR@1/mAR@10 now equal the recall of each image's own top-1/top-10 predictions, as documented. #2604

• sv.KeyPoints.as_detections now leaves key points marked not visible out of the box it derives for each skeleton, as sv.KeyPoints.with_nms already does — a pose whose low-confidence joints were predicted outside the person (e.g. legs below the bottom of the frame) previously got a box reaching out to them. A skeleton with no visible key point is now dropped, as one with only missing key points already was. #2605

• sv.IconAnnotator now draws grayscale PNG icons instead of failing with IndexError: tuple index out of range — a grayscale PNG without alpha reads as a 2-D array, which the overlay (BGR/BGRA only) can't handle; PNG optimizers like optipng/oxipng convert all-gray RGB icons to grayscale, so this hit real assets. A 16-bit icon is now scaled to 8 bits on load instead of wrapping modulo 256 (a value of 60000 previously drew as 96, near black); an icon that's neither 8-bit nor 16-bit now raises ValueError naming the file. #2591

• sv.IconAnnotator and sv.draw_image now keep the transparency of grayscale PNGs with alpha, RGB PNGs with a transparent color, and 1-bit PNGs, when OpenCV is not installed. The fallback returned Pillow's pixel layout instead of OpenCV's for IMREAD_UNCHANGED, so a grayscale-with-alpha icon failed with ValueError: could not broadcast input array from shape (16,16,2) into shape (16,16,3), sv.draw_image failed with ValueError: Image must have 3 or 4 channels., and a transparent-color RGB icon pasted with its transparent pixels drawn black. #2588

• sv.plot_images_grid now plots a single image in a grid_size=(1, 1) grid instead of failing with AttributeError: 'Axes' object has no attribute 'flat' — plt.subplots returns a lone Axes rather than an array for a 1x1 grid, which hit any code sizing the grid from the image count (e.g. grid_size=(1, len(images))) whenever there was only one image. #2590

• sv.LineZone.trigger no longer counts a spurious crossing in the opposite direction when a tracker flickers to the far side of the line for fewer than minimum_crossing_threshold frames. With minimum_crossing_threshold=2, the side sequence A,A,A,B,A,A,A previously counted a crossing into A — the side the object never left — so three separated flickers gave in_count=3 instead of 0. Crossings are now measured against the last side a tracker was confirmed on rather than the oldest history entry; sustained crossings and minimum_crossing_threshold=1 (the default) are unchanged. #2600

0.30.4 Sep 17, 2026

• sv.DetectionDataset.from_coco now rounds polygon vertices to the nearest pixel before rasterising masks, instead of truncating them to int32, as from_yolo/from_labelme/from_pascal_voc already do. Truncation shifted every mask up and to the left by up to a pixel — a polygon with corners at 2.6/7.6 covered pixels 2 to 7 from COCO but 3 to 8 from LabelMe, an IoU of 0.53 between the two masks. A non-finite vertex now raises ValueError naming the annotation id; integer vertices and RLE masks load as before. #2587

• sv.TraceAnnotator.annotate no longer raises ValueError: Length of color lookup 3 does not match length of detections 2 when a custom_color_lookup is passed alongside pending (tracker_id == -1) tracks — the annotator skips those detections but still resolved colors against the full-length lookup, although the other annotators accept the same detections and lookup. The lookup is now filtered alongside the detections, so each confirmed track keeps its own color; frames without pending tracks, and calls without custom_color_lookup, are unchanged. #2586

• sv.DetectionDataset.from_coco/from_labelme/from_createml/from_yolo now read JSON/YAML as UTF-8, and as_pascal_voc writes XML as UTF-8, instead of the platform default (cp1252 on Windows). A COCO category or YOLO data.yaml name outside ASCII broke on Windows: café loaded as café, 고양이 failed with UnicodeDecodeError, and as_pascal_voc either failed with UnicodeEncodeError or wrote a file from_pascal_voc rejected with ParseError: not well-formed (invalid token) — Linux/macOS, already UTF-8 by default, are unaffected. #2585

• sv.ClassificationDataset.as_folder_structure now copies source image files unchanged instead of round-tripping them through cv2.imread/cv2.imwrite, which dropped alpha channels, downcast 16-bit PNGs to 8-bit, and recompressed JPEGs on every export — matching sv.DetectionDataset's exports (as_yolo/as_pascal_voc/as_coco), which already copied — exporting into the folder the dataset was loaded from previously rewrote its own images the same lossy way. Images held in memory are still encoded with cv2.imwrite. #2584

• sv.get_video_frames_generator no longer reads start frames past end when iterative_seek=True — it counted start down to zero, then measured end from that zero instead of from start (start=2, end=5 yielded frames 2 to 6 instead of 2 to 4; start=4, end=6 yielded frames 4 to 9 instead of 4 to 6). A separate counter now keeps both seek modes aligned; start=0 and non-iterative calls are unchanged. #2583

• sv.DetectionDataset.from_labelme now finds images for LabelMe files saved on Windows when loading on Linux or macOS. imagePath is written with \, but the loader took only Path(...).name, which doesn't split on \ on POSIX — the whole value became the filename and reading failed with ValueError: Could not read image from path. The filename is now taken with either separator on every system, as LabelMe itself does when reading its own files; forward-slash paths, and every file on Windows, are unchanged. #2581

• sv.DetectionDataset.from_yolo now loads label files whose class ids are written as decimals (e.g. 1.0 0.5 0.5 0.2 0.4), which previously aborted the whole load with ValueError: invalid literal for int() — np.savetxt writes floats by default and Ultralytics tolerates them. Whole numbers load in any notation now; fractional, non-finite, or non-numeric ids still raise, naming the offending id. #2580

• sv.DetectionDataset.from_yolo/as_coco now size EXIF-oriented images the way cv2.imread loads them (swapping width/height for orientations 5 to 8), instead of reading the un-rotated file-header size via Pillow — quarter-turned photos previously scaled boxes/polygons by the swapped dimensions and produced mismatched mask shapes. The OpenCV-free fallback backend's imread/imdecode now apply EXIF orientation too, matching OpenCV's behavior for every read except IMREAD_UNCHANGED — previously the same file loaded with a different shape depending on whether opencv-python was installed. #2577

• sv.Detections.from_transformers now loads Transformers v5 return_binary_maps=True instance results (a (num_instances, H, W) stack), which the v5 path previously compared against each segment's id as if it were an id-map, producing a 4-D array that mask_to_xyxy rejected with ValueError: too many values to unpack (expected 3). Each segment now indexes the stack at its own id, keeping full masks for overlapping instances; segment-id-map results are unchanged. #2576

• sv.KeyPoints.from_inference now places each key point at the slot given by its class_id (skeleton index) instead of appending in received order — Inference drops key points below keypoint_confidence and multi-skeleton models report different counts per object, so stacking as-received either raised ValueError: ... inhomogeneous shape or silently slid later key points into earlier slots, joining the wrong joints. Omitted slots now stay (0, 0) at zero confidence, already skipped by the key point annotators and as_detections; a result with every key point omitted now loads with zero key points instead of failing validation. #2575

• sv.DetectionDataset.from_pascal_voc no longer fails on annotations with decimal coordinates (e.g. <xmin>48.5</xmin>), which aborted the whole load with ValueError: invalid literal for int() — Datumaro, which CVAT uses for its exports, writes VOC this way. Box coordinates are now read as floats and keep their precision; polygon vertices are rounded after the 1-index offset, as the YOLO and LabelMe loaders already do; non-finite values are still rejected. #2568

• sv.Detections.from_transformers no longer crashes on a Transformers v4 panoptic result with no segments — post_process_panoptic's empty segments_info produced a (0,) mask array instead of (0, H, W), and mask_to_xyxy raised ValueError: not enough values to unpack (expected 3, got 1). The path now builds a (0, H, W) mask stack and an integer class_id, matching the v5 paths, and yields empty Detections. #2571

... (truncated)

Commits

• 5956d7b releasing 0.30.5
• a05f594 ⬆️ bump astral-sh/setup-uv in the github-actions group (#2609)
• 7d381ea chore(deps): bump anyio in the uv group across 1 directory (#2607)
• 55c4789 fix(key_points): leave invisible key points out of as_detections boxes (#2605)
• 1c871bb fix(metrics): score mAR@K from each image's top K predictions only (#2604)
• c251321 fix(draw): scale 16-bit images down in draw_image (#2603)
• 665a31a fix(cv2): read CMYK images unchanged as color without OpenCV (#2602)
• 4faa218 fix(cv2): turn rotated videos upright without OpenCV (#2601)
• 34a039c fix(detection): stop LineZone counting sub-threshold flicker as a crossing (#...
• c6c6345 fix(detection): stop LineZone counting sub-threshold flicker as a crossing (#...
• Additional commits viewable in compare view

Updates fiftyone from 1.21.0 to 1.22.0

Release notes

Sourced from fiftyone's releases.

v1.22.0

Please see the official Voxel51 Release Notes for details.

Commits

• 4c3294e Merge pull request #8450 from voxel51/cherry-pick/v1.22.0/pr-8423
• de72a35 Merge pull request #8423 from voxel51/docs/release-notes-1.22.0
• 7e8cb86 Merge pull request #8425 from voxel51/cherry-pick/v1.22.0/pr-8409
• cc17f69 Merge pull request #8428 from voxel51/cherry-pick/v1.22.0/pr-8424
• 08fe3f7 Merge pull request #8444 from voxel51/cherry-pick/v1.22.0/pr-8439
• cb49349 Merge pull request #8446 from voxel51/cherry-pick/v1.22.0/pr-8414
• 91a561b Merge pull request #8445 from voxel51/cherry-pick/v1.22.0/pr-8393
• 23f8f0c Merge pull request #8414 from voxel51/fix/lerobot-windows-path-tests-2
• aa41d71 Merge pull request #8443 from voxel51/cherry-pick/v1.22.0/pr-8437
• f437b10 Merge pull request #8393 from voxel51/docs/skill-editor-fo-agent
• Additional commits viewable in compare view

Updates onnx from 1.22.0 to 1.23.0

Release notes

Sourced from onnx's releases.

v1.23.0

ONNX v1.23.0 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

IR Version 14

IR Version is changed from 13->14

Breaking Changes and Deprecations

• perf(reference): vectorize Conv implementation by @​justinchuby with @​Copilot in onnx/onnx#8366

Spec and Operator

New Operator SwiGLU is added [SwiGLU]

• Fix Attention is_causal causal-mask alignment + composed is_causal/attn_mask NaN robustness for external (static) KV cache (#8054) by @​titaiwangms in onnx/onnx#8068
• Add Celu-28 with float16/bfloat16/double support by @​cyyever in onnx/onnx#8107
• docs: clarify Transpose operator spec by @​pctablet505 in onnx/onnx#8197
• Add SwiGLU as a function-op by @​gramalingam in onnx/onnx#8202
• Mark Range operator as deterministic by @​take-cheeze in onnx/onnx#8232
• docs: fix ScatterND updates shape formula by @​uditjainstjis in onnx/onnx#8212
• Add local_window_size attribute to Attention opset 25 by @​FuZoe in onnx/onnx#8108
• Fix TensorScatter circular mode wrapping non-sequence coordinates by @​justinchuby in onnx/onnx#8353
• Attention (opset 23/24): fix bf16 type mismatch in causal-mask and padding-mask paths by @​justinchuby with @​Copilot in onnx/onnx#7840
• feat: add FLOAT6E2M3 and FLOAT6E3M2 quantization data types by @​andife in onnx/onnx#8349
• feat(defs): support bfloat16 in Compress and related ops by @​justinchuby with @​Copilot in onnx/onnx#8078
• Add mode attribute (DCR/CRD) to SpaceToDepth in opset 28, add function bodies to SpaceToDepth and DepthToSpace by @​justinchuby with @​Copilot in onnx/onnx#7848
• Allow float input to Mod when fmod=0 by @​justinchuby with @​Copilot in onnx/onnx#7521
• Add Einsum-28 with bfloat16 support by @​mcollinswisc in onnx/onnx#8313
• refactor(defs): centralize shared schema docs by @​justinchuby in onnx/onnx#8387
• Improve STFT operator documentation by @​justinchuby with @​Copilot in onnx/onnx#7905
• Add BitShift-28 with signed integer type support by @​mcollinswisc in onnx/onnx#8270
• feat(defs): support all IR14 types in Optional ops by @​youzow3 in onnx/onnx#8176
• fix(defs): restrict ReduceLogSum operators to float types in opset 28 by @​malakazlan in onnx/onnx#8384
• RFC Proposal for Grouped MatMul operator by @​gramalingam in onnx/onnx#8193

Reference Implementation

• Fix ScatterND reference impl for min/max with multi-axis indices by @​Ankita7033 in onnx/onnx#8099
• Register latest QuantizeLinear and DequantizeLinear reference implementations by @​napronald in onnx/onnx#8182
• Fix GatherElements output shape for empty indices by @​kiwigitops in onnx/onnx#8298
• fix(reference): handle scalar NonZero inputs by @​kiwigitops in onnx/onnx#8296
• Fix ReduceMax on empty boolean tensors by @​kiwigitops in onnx/onnx#8312
• fix(reference): handle zero-length ReverseSequence slices by @​kiwigitops in onnx/onnx#8304
• Support higher-rank ScatterElements evaluation by @​kiwigitops in onnx/onnx#8299
• fix(reference): reject out-of-range Concat axes by @​arcz in onnx/onnx#8327
• Runtime checks of shape annotations in reference evaluator by @​gramalingam in onnx/onnx#8307
• fix(reference): use accurate exponential functions by @​justinchuby with @​Copilot in onnx/onnx#8355

Utilities and Tools

• Fix heap buffer over-read in Conv/Pool shape inference for weight rank mismatch by @​titaiwangms with @​Copilot in onnx/onnx#8037
• Fix make_attribute_ref to set ref_attr_name by @​devin-lai in onnx/onnx#8009

... (truncated)

Commits

• ee3ccbd Version changed to 1.23.0 (#8469)
• 5f0e948 Version change to rc1 (#8407)
• 3515c31 Update RELEASE-MANAGEMENT.md (#8406)
• 0b1ce25 RFC Proposal for Grouped MatMul operator (#8193)
• f0430f0 fix(shape_inference): prevent Einsum ellipsis-rank segfault (#8273)
• 7f55643 build(deps): bump github/codeql-action/upload-sarif from 4.37.3 to 4.37.8 (#8...
• 41326c4 build(deps): bump github/codeql-action/init from 4.37.3 to 4.37.8 (#8397)
• 7e98dfa build(deps): bump github/codeql-action/analyze from 4.37.3 to 4.37.8 (#8401)
• f9b0137 build(deps): bump mypy from 2.3.0 to 2.3.1 (#8395)
• 765abb0 build(deps): bump actions/stale from 10.4.0 to 11.0.0 (#8398)
• 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 ruff from 0.16.6 to 0.16.8

Release notes

Sourced from ruff's releases.

0.16.8

Release Notes

Released on 2026-09-16.

Bug fixes

• Visit functional TypedDict keyword arguments correctly (#28584)
• [flake8-simplify] Detect nested async with under sync parent (SIM117) (#27821)
• [flake8-simplify] Preserve operand order in SIM109 fix (#27824)
• [pyupgrade] Preserve required parentheses in multiline UP040 fixes (#28164)
• [pyupgrade] Skip TypeVarTuple and ParamSpec conversions with bounds or constraints (UP040, UP046, UP047) (#28505)

Rule changes

• Add support for __lazy_modules__ (#28459)
• Recognize PEP-728 TypedDict class keywords (#28533)
• Recognize quoted types in typing.TypeForm (#28507)
• Support conditional assignment to __lazy_modules__ (#28491)
• [flake8-type-checking] Prefer lazy imports over TYPE_CHECKING on Python 3.15 and later (TC001, TC002, TC003) (#28541)
• [pyupgrade] Make the fix for UP040 always unsafe (#28526)
• [pyupgrade] Stop recommending deprecated ByteString aliases (UP035) (#28498)
• [ruff, flake8-use-pathlib] Recognize the parent_mode argument (RUF064, PTH103) (#28528)
• [ruff] Detect \Z in pytest.raises() match patterns (RUF043) (#28598)

CLI

• Use rule name and code in formatter incompatibility warnings (#28571)

Configuration

• [flake8-tidy-imports] Add extend-banned-api (#28644)

Contributors

• @​VedantMadane
• @​alzeph
• @​charliermarsh
• @​fredrikblau
• @​ntBre
• @​zsol
• @​Aniket-a14
• @​r-b-1

Install ruff 0.16.8

Install prebuilt binaries via shell script

curl --proto '=https' --tlsv1.2 -LsSf https://releases.astral.sh/github/ruff/releases/download/0.16.8/ruff-installer.sh | sh
</tr></table> 

... (truncated)

Changelog

Sourced from ruff's changelog.

0.16.8

Released on 2026-09-16.

Bug fixes

• Visit functional TypedDict keyword arguments correctly (#28584)
• [flake8-simplify] Detect nested async with under sync parent (SIM117) (#27821)
• [flake8-simplify] Preserve operand order in SIM109 fix (#27824)
• [pyupgrade] Preserve required parentheses in multiline UP040 fixes (#28164)
• [pyupgrade] Skip TypeVarTuple and ParamSpec conversions with bounds or constraints (UP040, UP046, UP047) (#28505)

Rule changes

• Add support for __lazy_modules__ (#28459)
• Recognize PEP-728 TypedDict class keywords (#28533)
• Recognize quoted types in typing.TypeForm (#28507)
• Support conditional assignment to __lazy_modules__ (#28491)
• [flake8-type-checking] Prefer lazy imports over TYPE_CHECKING on Python 3.15 and later (TC001, TC002, TC003) (#28541)
• [pyupgrade] Make the fix for UP040 always unsafe (#28526)
• [pyupgrade] Stop recommending deprecated ByteString aliases (UP035) (#28498)
• [ruff, flake8-use-pathlib] Recognize the parent_mode argument (RUF064, PTH103) (#28528)
• [ruff] Detect \Z in pytest.raises() match patterns (RUF043) (#28598)

CLI

• Use rule name and code in formatter incompatibility warnings (#28571)

Configuration

• [flake8-tidy-imports] Add extend-banned-api (#28644)

Contributors

• @​VedantMadane
• @​alzeph
• @​charliermarsh
• @​fredrikblau
• @​ntBre
• @​zsol
• @​Aniket-a14
• @​r-b-1

0.16.7

Released on 2026-09-10.

Preview features

• [ruff] Add rule for default values on method receivers (RUF077) (#26700)

... (truncated)

Commits

• 62914c4 Bump version to 0.16.8 (#28648)
• c47e0cd [ty] Bound aliased intersection expansion during inference (#28546)
• ff4747b renovate: update uv hashes correctly with setup-uv (#28621)
• 94efeaa [ty] Compact reachable binding and declaration histories (#28349)
• 50020fb [ty] Avoid storing constraint nodes twice (#28375)
• 446bb68 [ty] Compare bound-method receivers before signatures (#28384)
• 304ab86 [flake8-type-checking] Prefer lazy imports over TYPE_CHECKING on 3.15+ (`...
• d940b24 [ty] Watch script dependencies in CLI watch mode (#28125)
• fe9f065 [flake8-tidy-imports] Add extend-banned-api (#28644)
• 31131db [ty] Support type[A & B] (#27124)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• `@dependabot show <depend...

Description has been truncated

[dependabot]

Labels

The following labels could not be found: dependencies. Please create it before Dependabot can add it to a pull request.

Please fix the above issues or remove invalid values from dependabot.yml.

[dependabot]

Looks like these dependencies are updatable in another way, so this is no longer needed.