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Add rotary embedding onnx domain support - #29261

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Xiaoyu Z (xiaoyu-work) merged 6 commits into
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Jul 22, 2026
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Xiaoyu Z (xiaoyu-work) merged 6 commits into
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Description

Mobius exports standard ONNX rotary embedding op. Adding support for this.

Motivation and Context

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Pull request overview

This PR updates the GroupQueryAttention fusion optimizer pass to recognize standard (ONNX-domain) RotaryEmbedding nodes when extracting the cos_cache/sin_cache inputs needed to fuse rotary embedding into the com.microsoft.GroupQueryAttention node.

Changes:

  • Adds a helper to retrieve cos_cache/sin_cache NodeArgs for both com.microsoft.RotaryEmbedding and ONNX-domain RotaryEmbedding (different input ordering).
  • Updates the fusion pattern-matching logic to use that helper and to require that rotary cache inputs were successfully identified before fusing.

Comment thread onnxruntime/core/optimizer/group_query_attention_fusion.cc Outdated
Comment thread onnxruntime/core/optimizer/group_query_attention_fusion.cc Outdated
@titaiwangms

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cc Tianlei Wu (@tianleiwu)

@tianleiwu Tianlei Wu (tianleiwu) left a comment

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Summary

The change extends GroupQueryAttentionFusion to also match the standard ONNX-domain RotaryEmbedding (X, cos_cache, sin_cache, position_ids) in addition to com.microsoft.RotaryEmbedding, plumbing position_ids through to GQA input 9 and setting the input-arg-count. The approach is sound:

  • Requiring position_ids to be present for the ONNX-domain path (and bailing otherwise) correctly avoids the 3D per-batch cos/sin cache form that GQA's 2D rotary cache validation cannot consume.
  • The position_ids_arg_mismatch guard and the added cos_cache_arg == nullptr || sin_cache_arg == nullptr checks make the fusion safely skip ambiguous/mixed cases.
  • MutableInputArgsCount()[9] is in-bounds because the GQA schema declares formal inputs up to index 11, so UpdateInputArgCount() sizes the vector accordingly.
  • Both the fused (with position_ids) and non-fused (omitted position_ids) cases are covered by new tests.

Main concern

Rotary interleaved / rotary_embedding_dim attributes are not validated or propagated. GQA's do_rotary path runs non-interleaved, full-width RoPE (rotary_interleaved defaults to 0 and the fusion never sets it). A standard ONNX RotaryEmbedding with interleaved=1, or a partial-rotary node with rotary_embedding_dim > 0 (and a correspondingly narrower cos/sin cache), is silently fused into a GQA that applies a different rotation — producing incorrect results with no error. Since this PR specifically targets a standard-ONNX export path where interleaved RoPE is common, the fusion should either verify interleaved == 0 and rotary_embedding_dim == 0 (full rotary) before matching, or propagate interleaved to GQA's rotary_interleaved. Inline comment below. (Note: the pre-existing com.microsoft.RotaryEmbedding path has the same latent gap.)

Minor

  • Only position_ids is checked for consistency between the two rotary nodes; cos_cache/sin_cache are taken from whichever rotary node is visited first without verifying the second uses the same caches. In practice Q/K share caches, but an explicit equality guard (mirroring the position_ids_arg_mismatch check) would make the fusion robust to malformed graphs.

Comment thread onnxruntime/core/optimizer/group_query_attention_fusion.cc Outdated

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Thanks for updating the ONNX-domain RotaryEmbedding handling and adding the targeted fusion tests. I found one remaining correctness issue around explicit 2D position_ids: the fused GQA path can use different prompt-time position semantics than ONNX RotaryEmbedding, so I am requesting changes for that case.

Comment thread onnxruntime/core/optimizer/group_query_attention_fusion.cc

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Summary

The ONNX-domain RotaryEmbedding handling is now correctly disabled, and propagating rotary_interleaved plus the new Q/K mismatch guard address the earlier interleaved/attribute concerns — thanks for those. Two smaller follow-ups below, plus a note left on the existing position_ids thread.

  • Positive-path test coverage. All five new tests exercise only the not-fused branches (ONNX-domain skip and interleaved/position-id mismatch). The substantive new MS-domain behavior this PR adds — forwarding position_ids as GQA input 9 and setting the rotary_interleaved attribute on the fused node — has no test. The existing TestGQAFusion model tests only assert op counts, so they won't catch a missing/incorrect position_ids input or a wrong rotary_interleaved value. Consider a positive test that fuses a com.microsoft.RotaryEmbedding graph and asserts the fused GQA has 10 inputs (position_ids at index 9) and the expected rotary_interleaved attribute (including the interleaved=1 case).
  • MS-domain position_ids forwarding — see the reply on the existing thread; the full 2D position_ids is only partially honored on the first prompt.
  • Minor cleanup noted inline in TryGetRotaryEmbeddingArgs.

Comment thread onnxruntime/core/optimizer/group_query_attention_fusion.cc Outdated
Copilot-Session: 5b0af57d-0541-44f7-88d8-3adfdeca63a2
Copilot-Session: 5b0af57d-0541-44f7-88d8-3adfdeca63a2
@xiaoyu-work
Xiaoyu Z (xiaoyu-work) enabled auto-merge (squash) July 16, 2026 01:19
@xiaoyu-work
Xiaoyu Z (xiaoyu-work) merged commit 7208212 into main Jul 22, 2026
90 of 106 checks passed
@xiaoyu-work
Xiaoyu Z (xiaoyu-work) deleted the xiaoyu/re branch July 22, 2026 09:57
Kristoffer-Andre Kalliainen (181192) pushed a commit to 181192/brasscribe that referenced this pull request Sep 30, 2026
Updated [AlphaSkia.Native.Linux](https://github.com/CoderLine/alphaSkia)
from 3.4.135 to 3.5.147.

<details>
<summary>Release notes</summary>

_Sourced from [AlphaSkia.Native.Linux's
releases](https://github.com/CoderLine/alphaSkia/releases)._

## 3.5.147

## What's Changed
* chore(deps): update skia and update patches by @​Danielku15 in
CoderLine/alphaSkia#69


**Full Changelog**:
CoderLine/alphaSkia@v3.4.135...v3.5.147

Commits viewable in [compare
view](CoderLine/alphaSkia@v3.4.135...v3.5.147).
</details>

Updated [AlphaSkia.Native.MacOs](https://github.com/CoderLine/alphaSkia)
from 3.4.135 to 3.5.147.

<details>
<summary>Release notes</summary>

_Sourced from [AlphaSkia.Native.MacOs's
releases](https://github.com/CoderLine/alphaSkia/releases)._

## 3.5.147

## What's Changed
* chore(deps): update skia and update patches by @​Danielku15 in
CoderLine/alphaSkia#69


**Full Changelog**:
CoderLine/alphaSkia@v3.4.135...v3.5.147

Commits viewable in [compare
view](CoderLine/alphaSkia@v3.4.135...v3.5.147).
</details>

Updated
[Microsoft.ML.OnnxRuntime](https://github.com/Microsoft/onnxruntime)
from 1.24.4 to 1.30.0.

<details>
<summary>Release notes</summary>

_Sourced from [Microsoft.ML.OnnxRuntime's
releases](https://github.com/Microsoft/onnxruntime/releases)._

## 1.30.0

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](microsoft/onnxruntime#32168),
[#​32340](microsoft/onnxruntime#32340),
[#​32515](microsoft/onnxruntime#32515)).
- Improved WebGPU PagedAttention, added GPT-OSS support and INT8
KV-cache block quantization, and extended convolution optimizations
([#​31727](microsoft/onnxruntime#31727),
[#​32277](microsoft/onnxruntime#32277),
[#​32284](microsoft/onnxruntime#32284),
[#​32420](microsoft/onnxruntime#32420)).
- Added fused CPU LinearAttention kernels for AVX-512, Arm64 NEON, and
SVE, plus AVX2 LayerNorm/RMSNorm acceleration
([#​31674](microsoft/onnxruntime#31674),
[#​31973](microsoft/onnxruntime#31973),
[#​32178](microsoft/onnxruntime#32178),
[#​32356](microsoft/onnxruntime#32356)).
- Added Go bindings for the ONNX Runtime C API and DeepSeek Engram
contrib operators
([#​29615](microsoft/onnxruntime#29615),
[#​32268](microsoft/onnxruntime#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](microsoft/onnxruntime#32096),
[#​32163](microsoft/onnxruntime#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](microsoft/onnxruntime#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](microsoft/onnxruntime#32301),
[#​32197](microsoft/onnxruntime#32197)).
- WebGPU plugin EP packaging now supports Linux AArch64. Plugin versions
were advanced to WebGPU 0.4.0 and CUDA 0.2
([#​32287](microsoft/onnxruntime#32287),
[#​31960](microsoft/onnxruntime#31960),
[#​31970](microsoft/onnxruntime#31970)).

## Security & Reliability

### Model Loading, Memory, and Input Validation

- Limited nested model-graph depth and canonicalized external-data
locations to harden model loading
([#​32344](microsoft/onnxruntime#32344),
[#​32135](microsoft/onnxruntime#32135)).
- Added checked rounding for BFC arena allocations and fixed
prepacked-weight reference lifetimes
([#​32010](microsoft/onnxruntime#32010),
[#​32040](microsoft/onnxruntime#32040)).
- Strengthened shape, rank, and parameter validation for `Split`,
`Scan`, `GatherND`, `ScatterND`, `SpaceToDepth`/`DepthToSpace`, `Crop`,
`Conv`, `Normalizer`, and pooling
([#​29461](microsoft/onnxruntime#29461),
[#​31668](microsoft/onnxruntime#31668),
[#​32034](microsoft/onnxruntime#32034),
[#​32039](microsoft/onnxruntime#32039),
[#​32076](microsoft/onnxruntime#32076),
[#​32157](microsoft/onnxruntime#32157),
[#​32160](microsoft/onnxruntime#32160),
[#​32161](microsoft/onnxruntime#32161),
[#​32345](microsoft/onnxruntime#32345),
[#​32349](microsoft/onnxruntime#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](microsoft/onnxruntime#31648),
[#​31701](microsoft/onnxruntime#31701),
[#​32009](microsoft/onnxruntime#32009),
[#​32078](microsoft/onnxruntime#32078),
[#​32144](microsoft/onnxruntime#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](microsoft/onnxruntime#32031),
[#​32043](microsoft/onnxruntime#32043),
[#​32011](microsoft/onnxruntime#32011),
[#​32002](microsoft/onnxruntime#32002)).
- Added an allowlist of safe LoRA adapter parameter data types,
validated `MatMulFpQ4` shape inputs, and checked MLAS blockwise
quantization/dequantization index ranges
([#​31682](microsoft/onnxruntime#31682),
[#​32032](microsoft/onnxruntime#32032),
[#​32007](microsoft/onnxruntime#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](microsoft/onnxruntime#31643),
[#​31994](microsoft/onnxruntime#31994),
[#​31995](microsoft/onnxruntime#31995),
[#​31996](microsoft/onnxruntime#31996),
[#​31998](microsoft/onnxruntime#31998),
[#​32014](microsoft/onnxruntime#32014),
[#​32029](microsoft/onnxruntime#32029),
[#​32030](microsoft/onnxruntime#32030)).
- Fixed overflow in CUDA reduction scans and Softmax offset arithmetic,
and handled zero-sized outputs in CUDA random-generator kernels
([#​32137](microsoft/onnxruntime#32137),
[#​32330](microsoft/onnxruntime#32330),
[#​31997](microsoft/onnxruntime#31997)).
- Fixed CUDA MultiHeadAttention shared-cache scratch lifetimes and kept
`CudaAsyncBuffer` staging storage alive across CUDA graph replay
([#​31968](microsoft/onnxruntime#31968),
[#​32121](microsoft/onnxruntime#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](microsoft/onnxruntime#32364),
[#​32063](microsoft/onnxruntime#32063),
[#​32317](microsoft/onnxruntime#32317)).

### Dependencies and Tooling

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

## New Features

### Core APIs & Runtime

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

### Plugin Execution Providers
 ... (truncated)

## 1.29.1

This is a patch release on top of
[v1.29.0](https://github.com/microsoft/onnxruntime/releases/tag/v1.29.0),
containing GroupQueryAttention capability and KV-cache layout
improvements, plugin Execution Provider performance tooling updates, and
targeted graph and optimizer fixes.

## GroupQueryAttention

- Added bidirectional GroupQueryAttention support on CPU and CUDA
through a backward-compatible `causal` attribute, with explicit handling
for unsupported execution paths
([#​31704](microsoft/onnxruntime#31704))
- Added a session option and Execution Provider metadata contract for
using the BNHS Value KV-cache layout, with graph transformations that
preserve compatibility with the existing BNSH operator schema
([#​32139](microsoft/onnxruntime#32139))
- Added CPU support for `attention_bias` with a sliding-window KV cache,
including explicit position IDs and post-eviction bias indexing
([#​32302](microsoft/onnxruntime#32302))

## Runtime and Performance Tools

- Fixed Compile API model serialization when output-model and custom
initializer-location callbacks are used together, preventing duplicate
graph fields in emitted models
([#​32303](microsoft/onnxruntime#32303))
- Updated `onnxruntime_perf_test` to use plugin Execution Provider
device allocators for generated inputs, loaded test data, and
pre-allocated outputs, avoiding unnecessary per-run host/device copies
([#​32244](microsoft/onnxruntime#32244))

## Bug Fixes and Documentation

- Hardened FastGelu fusion to skip malformed `Mul` and `Pow` patterns
([#​32016](microsoft/onnxruntime#32016))
- Added validation for in-memory external initializer references,
rejecting unregistered or mismatched data before graph transformation
([#​32042](microsoft/onnxruntime#32042))
- Restored the C API documentation workflow by switching the pinned
Doxygen download to the official GitHub release asset
([#​32210](microsoft/onnxruntime#32210))

## Contributors

Thanks to our 7 contributors for this release!

[@​adrastogi](https://github.com/adrastogi),
[@​apsonawane](https://github.com/apsonawane),
[@​edgchen1](https://github.com/edgchen1),
[@​javier-intel](https://github.com/javier-intel),
[@​jnagi-intel](https://github.com/jnagi-intel),
[@​tianleiwu](https://github.com/tianleiwu),
[@​Wayne-Ch](https://github.com/Wayne-Ch)

<sub>Release highlights were drafted with AI assistance and are subject
to release-team review.</sub>

Full Changelog:
[v1.29.0...v1.29.1](microsoft/onnxruntime@v1.29.0...v1.29.1)


## 1.29.0

## Announcements & Breaking Changes

- onnxruntime-web has announced the deprecation of WebGL and JSEP. The
native WebGPU EP is the recommended path going forward. See the
deprecation and migration plans for details
([#​29716](microsoft/onnxruntime#29716),
[#​31683](microsoft/onnxruntime#31683)).
- POSIX telemetry is now available on Linux, macOS, Android, and iOS
when ONNX Runtime is built with telemetry enabled. It does not change
the public ABI, WebAssembly remains telemetry-free, and setting
`ORT_DISABLE_TELEMETRY=1` before initialization disables non-Windows
telemetry for the process
([#​27379](microsoft/onnxruntime#27379),
[#​29872](microsoft/onnxruntime#29872)).
- The unused internal `onnxruntime/python/tools/tensorrt` dashboard
tooling was removed. This does not affect the TensorRT Execution
Provider APIs
([#​29395](microsoft/onnxruntime#29395)).

## Security Fixes

### Path, bounds, and input validation

- Fixed a path traversal vulnerability in TensorRT and NvTensorRTRTX
engine refitting by making external-data path validation unconditional
([#​29396](microsoft/onnxruntime#29396)).
- Validated the CPU MoE `k` attribute against the number of experts and
fixed a CPU `TensorScatter` security issue
([#​29907](microsoft/onnxruntime#29907),
[#​29916](microsoft/onnxruntime#29916)).
- Added missing rank, shape, and parameter validation for pooling, LSTM
and DynamicQuantizeLSTM, Sampling, FeatureVectorizer, SkipLayerNorm,
QLinearConv, Whisper decoding, RNN activations, GridSample, contrib
`Range`, and `CropAndResize`
([#​29254](microsoft/onnxruntime#29254),
[#​29255](microsoft/onnxruntime#29255),
[#​29265](microsoft/onnxruntime#29265),
[#​29579](microsoft/onnxruntime#29579),
[#​29595](microsoft/onnxruntime#29595),
[#​29605](microsoft/onnxruntime#29605),
[#​29871](microsoft/onnxruntime#29871),
[#​31636](microsoft/onnxruntime#31636),
[#​31671](microsoft/onnxruntime#31671),
[#​31675](microsoft/onnxruntime#31675),
[#​31676](microsoft/onnxruntime#31676),
[#​31684](microsoft/onnxruntime#31684)).
- Hardened CUDA indexing and buffer handling in GridSample, transpose,
GatherBlockQuantized, InstanceNormalization, LayerNorm/RMSNorm,
BeamSearch, DeformConv, AveragePool, and MaxPool
([#​29581](microsoft/onnxruntime#29581),
[#​29631](microsoft/onnxruntime#29631),
[#​29638](microsoft/onnxruntime#29638),
[#​31640](microsoft/onnxruntime#31640),
[#​31642](microsoft/onnxruntime#31642),
[#​31644](microsoft/onnxruntime#31644),
[#​31645](microsoft/onnxruntime#31645),
[#​31647](microsoft/onnxruntime#31647),
[#​31650](microsoft/onnxruntime#31650)).
- Fixed packed sub-byte tensor over-copying in `OrtApi::GetValue` and
validated DML constant tensor byte sizes
([#​29157](microsoft/onnxruntime#29157),
[#​31665](microsoft/onnxruntime#31665)).

### Supply chain and tooling

- Updated npm lockfiles, refreshed the Next.js end-to-end fixture
lockfile for security advisories, and upgraded `adm-zip` for
`onnxruntime-node`
([#​29827](microsoft/onnxruntime#29827),
[#​29926](microsoft/onnxruntime#29926),
[#​31192](microsoft/onnxruntime#31192)).

## New Features

### Core APIs & Runtime

- Default intra-op and inter-op thread-pool sizes can now be set with
`ORT_INTRA_OP_NUM_THREADS` and `ORT_INTER_OP_NUM_THREADS`. Explicit
thread settings still take precedence, and `0` preserves machine-sized
defaults
([#​29688](microsoft/onnxruntime#29688)).
- Added weightless-model support for all initializer types, allowed
zero-input `EpContext` nodes, and wired maximum-shape inference into
workspace estimation
([#​29607](microsoft/onnxruntime#29607),
[#​29799](microsoft/onnxruntime#29799),
[#​31613](microsoft/onnxruntime#31613)).
- Added ONNX-domain support for rotary embedding and a fused
`MRotaryEmbedding` contrib operator for Qwen mRoPE variants
([#​29261](microsoft/onnxruntime#29261),
[#​31728](microsoft/onnxruntime#31728)).
- Added multi-shape profiling to `onnxruntime_perf_test` through
`--data_shape`, plus verbose graph-transformer tracing and broader
inference-session error-path coverage
([#​29555](microsoft/onnxruntime#29555),
[#​29558](microsoft/onnxruntime#29558),
[#​29569](microsoft/onnxruntime#29569),
[#​29571](microsoft/onnxruntime#29571)).

### Execution Provider ABI & Plugin EPs

- WebGPU now supports device-free compile-only sessions for offline
graph transformation
([#​29681](microsoft/onnxruntime#29681)).
- Expanded CUDA plugin EP packaging and testing, including Windows ARM64
package and size options, updated package outputs, and aligned
architecture selections across Python, C API, TensorRT, Node.js, and
plugin packages
([#​31635](microsoft/onnxruntime#31635),
[#​31722](microsoft/onnxruntime#31722),
[#​31992](microsoft/onnxruntime#31992)).
- Improved plugin lifecycle handling by unloading failed EP library
loads and fixing allocator-deleter lifetime
([#​29634](microsoft/onnxruntime#29634),
[#​29770](microsoft/onnxruntime#29770)).

## Execution Provider Updates

### NVIDIA CUDA EP

#### Attention and decoding

- Added `PagedAttention` with quantized KV cache, XQA decode, MLA,
QK-Norm, and head-sink support
([#​29912](microsoft/onnxruntime#29912)).
- Extended quantized KV-cache support with attention sinks, independent
and per-channel scales, sliding-window cache support, and a fused K/V
dequantization launch
([#​29900](microsoft/onnxruntime#29900),
[#​29904](microsoft/onnxruntime#29904),
[#​31480](microsoft/onnxruntime#31480)).
- Added a cuDNN SDPA decode tier to the standard ONNX `Attention` CUDA
kernel and enabled cuDNN SDPA for contrib `Attention`
([#​29715](microsoft/onnxruntime#29715),
[#​29717](microsoft/onnxruntime#29717)).
- Added `attention_bias` support to the GroupQueryAttention unfused path
and `state_window` support to LinearAttention and CausalConvWithState
for MTP ([#​29525](microsoft/onnxruntime#29525),
[#​31157](microsoft/onnxruntime#31157)).
- Fixed LinearAttention on GPUs with limited shared memory
([#​31982](microsoft/onnxruntime#31982)).

#### MoE and quantized GEMM

- Added NVFP4 QMoE, including native FP4xFP4 prefill on SM120, faster
decode GEMV, fused routing/finalization paths, and reduced activation
and weight-dequantization overhead
([#​29697](microsoft/onnxruntime#29697),
[#​29824](microsoft/onnxruntime#29824),
[#​29887](microsoft/onnxruntime#29887),
[#​29919](microsoft/onnxruntime#29919),
[#​31156](microsoft/onnxruntime#31156),
[#​31159](microsoft/onnxruntime#31159),
[#​31349](microsoft/onnxruntime#31349),
[#​31479](microsoft/onnxruntime#31479)).
 ... (truncated)

## 1.28.2

This is a patch release on top of
[v1.28.1](https://github.com/microsoft/onnxruntime/releases/tag/v1.28.1),
containing a targeted fix for Compile API model serialization.

## Highlights

### Bug Fixes

- Fixed Compile API callback serialization to prevent duplicate graph
nodes, inputs, outputs, and value information in emitted optimized
models, including models with embedded or external initializers
([#​32303](microsoft/onnxruntime#32303))

## Contributors

Thanks to our contributor for this release!

[@​adrastogi](https://github.com/adrastogi)

Full Changelog:
[v1.28.1...v1.28.2](microsoft/onnxruntime@v1.28.1...v1.28.2)

> These release notes were drafted with assistance from GitHub Copilot.


## 1.28.1

This is a patch release on top of
[v1.28.0](https://github.com/microsoft/onnxruntime/releases/tag/v1.28.0),
containing support for device-free WebGPU compilation, improved
compatibility with sandboxed Windows processes, and targeted
graph-validation fixes.

## WebGPU EP

- Added support for device-free compile-only sessions, enabling offline
graph transformation and optimized-model serialization without access to
GPU hardware
([#​29681](microsoft/onnxruntime#29681))

## Bug Fixes

- Prevented an access violation in Windows processes under Win32k
lockdown by skipping DXGI device discovery
([#​29755](microsoft/onnxruntime#29755))
- Allowed zero-input `EPContext` nodes, aligning their schema with
support for compiling zero-input models
([#​29799](microsoft/onnxruntime#29799))
- Hardened FastGelu fusion to skip malformed `Mul` and `Pow` patterns
([#​32016](microsoft/onnxruntime#32016))
- Added validation for in-memory external initializer references,
rejecting unregistered or mismatched data before graph transformation
([#​32042](microsoft/onnxruntime#32042))

## Contributors

Thanks to our 4 contributors for this release!

[@​apsonawane](https://github.com/apsonawane),
[@​shiyi9801](https://github.com/shiyi9801),
[@​adrastogi](https://github.com/adrastogi),
[@​mingmingtasd](https://github.com/mingmingtasd)

Full Changelog:
[v1.28.0...v1.28.1](microsoft/onnxruntime@v1.28.0...v1.28.1)

## 1.28.0

## Announcements & Breaking Changes

- Upgraded to **ONNX 1.22.0** and protobuf 6.33.5
([#​28754](microsoft/onnxruntime#28754),
[#​29606](microsoft/onnxruntime#29606),
[#​28967](microsoft/onnxruntime#28967)). Graph
optimizer opset version checks were updated accordingly
([#​28966](microsoft/onnxruntime#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](microsoft/onnxruntime#29252),
[#​29808](microsoft/onnxruntime#29808),
[#​29705](microsoft/onnxruntime#29705),
[#​29620](microsoft/onnxruntime#29620)).
- An **experimental C/C++ API surface** was introduced.
`OrtModelPackageApi` now lives in the experimental C API and may change
in future releases
([#​28746](microsoft/onnxruntime#28746),
[#​29142](microsoft/onnxruntime#29142),
[#​28990](microsoft/onnxruntime#28990)).
- **Deprecated / removed:**
- SkipLayerNorm strict mode is deprecated
([#​29388](microsoft/onnxruntime#29388)).
- The TensorRT fused causal attention kernels were removed from the CUDA
EP ([#​29143](microsoft/onnxruntime#29143)).
- The dynamic WGSL generator (duktape/Node) path was removed in favor of
the Python `wgsl-gen` implementation
([#​29141](microsoft/onnxruntime#29141),
[#​28355](microsoft/onnxruntime#28355)).
- `CUDA_QUANT_PREPROCESS` is off by default
([#​29687](microsoft/onnxruntime#29687)).
- NPM packages are now published from the CUDA 13 pipeline
([#​28773](microsoft/onnxruntime#28773)).
- The CUDA 12.8 package architecture list was refreshed for this release
([#​29711](microsoft/onnxruntime#29711)).

## Security Fixes

### Memory safety & input validation

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

### Integer overflow & allocation size

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

### Supply chain & tooling

 ... (truncated)

## 1.27.1

This is a patch release on top of
[v1.27.0](https://github.com/microsoft/onnxruntime/releases/tag/v1.27.0),
containing targeted bug fixes, a CUDA QMoE decode-path optimization, and
CI/build infrastructure fixes.

## Bug Fixes

- [MLAS] Fixed an `igemm` regression in the KleidiAI path
([#​28571](microsoft/onnxruntime#28571))
- Fixed a QMoE CPU livelock by eliminating nested intra-op parallelism
([#​29081](microsoft/onnxruntime#29081))
- Fixed a regression in graph-capture session initialization that
rejected an empty graph
([#​29457](microsoft/onnxruntime#29457))
- Fixed CustomOp forward compatibility by capping the version instead of
rejecting it
([#​29574](microsoft/onnxruntime#29574))

## Performance

### NVIDIA CUDA EP

- Added a QMoE GEMV fast path for batch-1 decode
([#​29038](microsoft/onnxruntime#29038))

## CI & Build Infrastructure

- Fixed an incorrect identity for `azcopy`
([#​29274](microsoft/onnxruntime#29274))
- Fixed a `brew install applesimutils` failure by trusting the wix/brew
tap ([#​29450](microsoft/onnxruntime#29450))
- Upgraded to Xcode 26
([#​29468](microsoft/onnxruntime#29468))
- Stopped echoing the command when setting a VSO variable in
`mac-cpu-packing-jobs.yml`
([#​29575](microsoft/onnxruntime#29575))
- Fixed the web e2e (npm/vite) and Python DML CI pipelines
([#​29609](microsoft/onnxruntime#29609))

## Contributors

Thanks to our 8 contributors for this release!

[@​tianleiwu](https://github.com/tianleiwu),
[@​chilo-ms](https://github.com/chilo-ms),
[@​edgchen1](https://github.com/edgchen1),
[@​adrastogi](https://github.com/adrastogi),
[@​damdoo01-arm](https://github.com/damdoo01-arm),
[@​JonathanC-ARM](https://github.com/JonathanC-ARM),
[@​martin-klacer-arm](https://github.com/martin-klacer-arm),
[@​sanaa-hamel-microsoft](https://github.com/sanaa-hamel-microsoft)

Full Changelog:
[v1.27.0...v1.27.1](microsoft/onnxruntime@v1.27.0...v1.27.1)

## 1.27.0

n.b. This release is targeting ONNX 1.21. ONNX 1.22 will be supported in
ORT 1.28.
n.b. This changelog was generated via LLM. Only the contributor list has
been verified. As always, only trust the commit history.

## Announcements & Breaking Changes

* CUDA 12 package files are now explicitly named as such.
* CUDA 12 packages are deprecated, please move to CUDA 13 ASAP.

---

## Security Fixes

* Fixed out-of-bounds read in `SoftmaxCrossEntropyLoss` via label bounds
validation
([#​28004](microsoft/onnxruntime#28004))
* Hardened `OneHot` input validation and output-size computation
([#​28014](microsoft/onnxruntime#28014))
* Added SafeInt overflow protection in `Expand` and capped
constant-folding output sizes
([#​28055](microsoft/onnxruntime#28055))
* Bounded total output allocation size in `Tile` kernel
([#​28070](microsoft/onnxruntime#28070))
* Added mask/input shape consistency checks in
`MaxpoolWithMask::Compute`
([#​28223](microsoft/onnxruntime#28223))
* Fixed `BitShift` UB for shift amounts greater than or equal to bit
width ([#​28272](microsoft/onnxruntime#28272))
* Validated sequence bounds in GQA (`seqlens_k` vs `cos_cache`)
([#​28277](microsoft/onnxruntime#28277))
* Validated conv bias shape in `WordConvEmbedding` to prevent OOB reads
([#​28279](microsoft/onnxruntime#28279))
* Fixed int32 overflow in CUDA Cast and UnaryElementWise kernels for
very large tensors
([#​28386](microsoft/onnxruntime#28386))
* Fixed out-of-bounds read in `CropBase` scale handling
([#​28399](microsoft/onnxruntime#28399))
* Fixed rank-underflow bug in Inverse kernel trailing-dimension indexing
([#​28400](microsoft/onnxruntime#28400))
* Added sparse tensor external file path validation and additional
external-path hardening
([#​28408](microsoft/onnxruntime#28408),
[#​28709](microsoft/onnxruntime#28709),
[#​28725](microsoft/onnxruntime#28725))
* Switched remaining `torch.load()` calls to `weights_only=True`
([#​28421](microsoft/onnxruntime#28421))
* Added CPU cache-indirection beam-index validation
([#​28486](microsoft/onnxruntime#28486))
* Added additional overflow/bounds checks and test coverage in runtime
buffers ([#​28713](microsoft/onnxruntime#28713),
[#​28747](microsoft/onnxruntime#28747))

---

## New Features

### Execution Provider Plugin API

* Added zero-copy I/O for plugin EPs with HOST_ACCESSIBLE memory
([#​28037](microsoft/onnxruntime#28037))
* Added `OrtEp::OnSessionInitializationEnd()` callback
([#​28319](microsoft/onnxruntime#28319))
* Added plugin EP session-options getters
([#​28377](microsoft/onnxruntime#28377))
* Added CUDA Plugin EP provider options for streams and external
allocators
([#​28603](microsoft/onnxruntime#28603))

### Core APIs & Runtime

* Added support for ONNX overloaded functions (IR v10+)
([#​28275](microsoft/onnxruntime#28275))
* Added FLOAT8E8M0 datatype support in ONNX Runtime
([#​28381](microsoft/onnxruntime#28381))
* Added CPU Cast support for FLOAT8E8M0
([#​28435](microsoft/onnxruntime#28435))
* Added `kOrtEpDevice_EpMetadataKey_OSDriverVersion` example and docs
([#​28282](microsoft/onnxruntime#28282))

### Quantization & Training Tooling

* Added calibration cache support to `quantize_static`
([#​28221](microsoft/onnxruntime#28221))
* Added `ActivationRestrictedAsymmetric` quantization option
([#​28237](microsoft/onnxruntime#28237))
 ... (truncated)

## 1.26.0

n.b. The following was generated via LLM from Git history. Only the
contributor list has been verified.

## Announcement - Breaking Changes

- **Support for CUDA 12 will be removed in 1.27.0.**
- CUDA 13 will continue to be published as
`onnxruntime-<os>-<arch>-gpu_cuda13-<version>.<ext>`
- CUDA runtime will be moving soon to a dedicated Execution Provider
(EP) instead of a published package from ORT core.

## Highlights

- Added optional memory mapping for `.ort` model loads
([#​28164](microsoft/onnxruntime#28164)).
- Added RISC-V Vector (RVV) support for CPU EP
([#​28261](microsoft/onnxruntime#28261)).
- OpenVINO EP upgraded for 1.26.0 development release
([#​28297](microsoft/onnxruntime#28297)).
- WebGPU gained GridSample support
([#​28264](microsoft/onnxruntime#28264)) and
Split-K improvements
([#​28151](microsoft/onnxruntime#28151)).
- CUDA plugin EP gained graph support
([#​28002](microsoft/onnxruntime#28002)),
profiling API
([#​28216](microsoft/onnxruntime#28216)).

## Security and Reliability Hardening

- Replaced unrestricted Python `setattr` configuration with an allowlist
([#​28083](microsoft/onnxruntime#28083)).
- Hardened multiple OOB and overflow scenarios across ML and core ops:
- Attention mask index OOB write
([#​27789](microsoft/onnxruntime#27789)).
- MaxPoolGrad indices bounds validation
([#​27903](microsoft/onnxruntime#27903)).
- SVM and TreeEnsemble bounds/security fixes
([#​27950](microsoft/onnxruntime#27950),
[#​27951](microsoft/onnxruntime#27951),
[#​27952](microsoft/onnxruntime#27952),
[#​27989](microsoft/onnxruntime#27989)).
- RNN sequence_lens OOB read and integer overflow handling
([#​28052](microsoft/onnxruntime#28052),
[#​28003](microsoft/onnxruntime#28003)).
- GroupQueryAttention seqlens_k bounds validation and compatibility
follow-up
([#​28031](microsoft/onnxruntime#28031),
[#​28259](microsoft/onnxruntime#28259)).
- MatMulBnb4 and ML coefficient SafeInt checks
([#​27995](microsoft/onnxruntime#27995),
[#​28001](microsoft/onnxruntime#28001)).
- CUDA Gather int32 overflow fix
([#​28108](microsoft/onnxruntime#28108)).
- GridSample float->int64 cast hardening for NaN/Inf/out-of-range coords
([#​28302](microsoft/onnxruntime#28302)).
- Fixed session logger use-after-free during EP teardown under verbose
logging
([#​28274](microsoft/onnxruntime#28274)).

## CUDA, Attention, and MLAS

- Filled CUDA opset/operator gaps and extended support:
- Transpose opset 23 -> 25
([#​27740](microsoft/onnxruntime#27740)).
- QuantizeLinear/DequantizeLinear opset 25
([#​28046](microsoft/onnxruntime#28046)).
- CUDA TopK INT8/INT16/UINT8 support
([#​27862](microsoft/onnxruntime#27862)).
- LabelEncoder CUDA support for numeric types
([#​28045](microsoft/onnxruntime#28045)).
- Attention/GQA improvements:
- Fixed ONNX Attention min-bias alignment crash on SM<80 and
masked-batch NaN behavior
([#​27831](microsoft/onnxruntime#27831)).
- Added FP32 QK accumulation path for unfused GQA attention
([#​28198](microsoft/onnxruntime#28198)).
- Added CUDART_VERSION reduction compatibility in GQA attention
([#​28296](microsoft/onnxruntime#28296)).
- Fixed CUDA 13 build error in GQA unfused attention
([#​28309](microsoft/onnxruntime#28309)).
- PagedAttention fallback for SM<80 fp16
([#​28200](microsoft/onnxruntime#28200)).
- MLAS updates:
- FP16 Gelu enablement
([#​26815](microsoft/onnxruntime#26815)).
- Arm64 BF16 fast-math conv kernels for NCHW/NCHWc paths
([#​27878](microsoft/onnxruntime#27878)).

## WebGPU, WebNN, and JavaScript

- WebGPU feature and correctness updates:
 ... (truncated)

## 1.25.1

n.b. This changelog is LLM generated. Only the contributor listing has
been verified.

# ONNX Runtime Release 1.25.1

## 📢 Announcements & Breaking Changes

### ONNX Op Updates

* **Enhanced ONNX operator support** with new opset versions: Reshape
(opset 25), Transpose (opset 24)
([#​27752](microsoft/onnxruntime#27752))

---

## ✨ New Features

### 📊 New ONNX Ops & Model Support

* **LinearAttention and CausalConvState operators** for Qwen3.5 model
support ([#​27907](microsoft/onnxruntime#27907))
* **RotaryEmbedding (RotEMB) and RMSNorm operators** added
([#​27752](microsoft/onnxruntime#27752))
* **Linear Attention signature** support
([#​27842](microsoft/onnxruntime#27842))

---

## 🌐 Web & JavaScript

### WebGPU EP

* **Qwen3.5 model support** on WebGPU execution provider
([#​27996](microsoft/onnxruntime#27996))
* **QMoE 1-token decode path optimization** — fused operations to reduce
GPU dispatches for improved performance
([#​27998](microsoft/onnxruntime#27998))

---

## 🐛 Bug Fixes

### Core Runtime Fixes

* **Improved filesystem error messages** during Linux device discovery
for better debugging experience
([#​27289](microsoft/onnxruntime#27289))
* Fixed missing include for `SetRawDataInTensorProto` in NVIDIA TensorRT
RTX tests
([#​28065](microsoft/onnxruntime#28065))

---

## 🙏 Contributors

Thanks to our **7 contributors** for this release:
[@​guschmue](https://github.com/guschmue),
[@​sanaa-hamel-microsoft](https://github.com/sanaa-hamel-microsoft),
[@​apsonawane](https://github.com/apsonawane),
[@​eserscor](https://github.com/eserscor),
[@​ishwar-raut1](https://github.com/ishwar-raut1),
[@​qjia7](https://github.com/qjia7),
[@​theHamsta](https://github.com/theHamsta)

**Full Changelog**:
microsoft/onnxruntime@v1.25.0...v1.25.1

## 1.25.0

## 📢 Announcements & Breaking Changes

### Build & Platform

* **C++20 is now required** to build ONNX Runtime from source. Minimum
toolchains: MSVC 19.29+, GCC 10+, Clang 10+. Users of prebuilt packages
are unaffected.
([#​27178](microsoft/onnxruntime#27178))
* **CUDA minimum version raised to 12.0** — CUDA 11.x is no longer
supported. Users pinned to CUDA 11.x should stay on ORT 1.24.x or
upgrade their CUDA toolkit/driver.
([#​27570](microsoft/onnxruntime#27570))
* **ONNX upgraded to 1.21.0**
([#​27601](microsoft/onnxruntime#27601))
* **sympy is now an optional dependency** for Python builds.
([#​27200](microsoft/onnxruntime#27200))

### Execution Provider Changes

* **ArmNN EP has been removed.** Users should remove any `--use_armnn`
build flags and migrate to the MLAS/KleidiAI-backed CPU EP or QNN EP for
Qualcomm hardware.
([#​27447](microsoft/onnxruntime#27447))

### API Version

* **ORT_API_VERSION** updated to **25**.
([#​27280](microsoft/onnxruntime#27280))

---

## 🔒 Security Fixes

* Fixed **potential integer truncation leading to heap out-of-bounds
read/write**
([#​27544](microsoft/onnxruntime#27544))
* Addressed **Pad Reflect vulnerability**
([#​27652](microsoft/onnxruntime#27652))
* **Security fix for transpose optimizer**
([#​27555](microsoft/onnxruntime#27555))
* Upgraded minimatch 3.1.2 → 3.1.4 for **CVE-2026-27904**
([#​27667](microsoft/onnxruntime#27667))
* Hardened shell command handling for constant strings
([#​27840](microsoft/onnxruntime#27840))
* Added validation of `onnx::TensorProto` data size before allocation
([#​27547](microsoft/onnxruntime#27547))
* Cleaned up external data path validation
([#​27539](microsoft/onnxruntime#27539))
* Fixed misaligned address reads for tensor attributes from raw data
buffers ([#​27312](microsoft/onnxruntime#27312))
* Fixed **CPU Attention overflow** issue
([#​27822](microsoft/onnxruntime#27822))
* Fixed **CPU LRN integer overflow** issues
([#​27886](microsoft/onnxruntime#27886))
*   Additional input validation hardening:
* Tile kernel dim overflow
([#​27566](microsoft/onnxruntime#27566))
* Out-of-bounds read in cross entropy
([#​27568](microsoft/onnxruntime#27568))
* TreeEnsembleClassifier attributes
([#​27571](microsoft/onnxruntime#27571))
* AffineGrid
([#​27572](microsoft/onnxruntime#27572))
* EmbedLayerNorm position_ids
([#​27573](microsoft/onnxruntime#27573))
* RotaryEmbedding position_ids
([#​27597](microsoft/onnxruntime#27597))
* RoiAlign batch_indices
([#​27603](microsoft/onnxruntime#27603))
* MaxUnpool indices
([#​27432](microsoft/onnxruntime#27432))
* QMoECPU swiglu OOB
([#​27748](microsoft/onnxruntime#27748))
* SVMClassifier initializer
([#​27699](microsoft/onnxruntime#27699))
* Col2Im SafeInt
([#​27625](microsoft/onnxruntime#27625))

---

## ✨ New Features

### 🔌 Execution Provider Plugin API & CUDA Plugin EP

 ... (truncated)

Commits viewable in [compare
view](microsoft/onnxruntime@v1.24.4...v1.30.0).
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