deps(maven): bump com.microsoft.onnxruntime:onnxruntime from 1.28.0 to 1.29.0

[dependabot]

Bumps com.microsoft.onnxruntime:onnxruntime from 1.28.0 to 1.29.0.

Release notes

Sourced from com.microsoft.onnxruntime:onnxruntime's releases.

ONNX Runtime v1.29.0

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, #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, #29872).
• The unused internal onnxruntime/python/tools/tensorrt dashboard tooling was removed. This does not affect the TensorRT Execution Provider APIs (#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).
• Validated the CPU MoE k attribute against the number of experts and fixed a CPU TensorScatter security issue (#29907, #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, #29255, #29265, #29579, #29595, #29605, #29871, #31636, #31671, #31675, #31676, #31684).
• Hardened CUDA indexing and buffer handling in GridSample, transpose, GatherBlockQuantized, InstanceNormalization, LayerNorm/RMSNorm, BeamSearch, DeformConv, AveragePool, and MaxPool (#29581, #29631, #29638, #31640, #31642, #31644, #31645, #31647, #31650).
• Fixed packed sub-byte tensor over-copying in OrtApi::GetValue and validated DML constant tensor byte sizes (#29157, #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, #29926, #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).
• Added weightless-model support for all initializer types, allowed zero-input EpContext nodes, and wired maximum-shape inference into workspace estimation (#29607, #29799, #31613).
• Added ONNX-domain support for rotary embedding and a fused MRotaryEmbedding contrib operator for Qwen mRoPE variants (#29261, #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, #29558, #29569, #29571).

Execution Provider ABI & Plugin EPs

• WebGPU now supports device-free compile-only sessions for offline graph transformation (#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, #31722, #31992).
• Improved plugin lifecycle handling by unloading failed EP library loads and fixing allocator-deleter lifetime (#29634, #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).
• 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, #29904, #31480).
• Added a cuDNN SDPA decode tier to the standard ONNX Attention CUDA kernel and enabled cuDNN SDPA for contrib Attention (#29715, #29717).
• Added attention_bias support to the GroupQueryAttention unfused path and state_window support to LinearAttention and CausalConvWithState for MTP (#29525, #31157).
• Fixed LinearAttention on GPUs with limited shared memory (#31982).

MoE and quantized GEMM

... (truncated)

Commits

• 2e2543f [CUDA] Update cuda archs in packaging pipelines (#31992)
• 9b174a4 [CUDA] Add GatedAdd contrib operator (#31835)
• a29da16 Validate SkipLayerNorm prepacked lengths (#31676)
• 831fa2f Validate whisper beginning_timestamp_token_id bounds (#31636)
• 3cee186 Handle RNN activation parameters safely (#31675)
• 37d79e3 Harden CUDA fp16 transpose index math against int overflow (#31644)
• 45bdd4c Validate QLinearConv bias size against output channels (#31684)
• f5de4c3 Fix TfIdfVectorizer weight indexing semantics (#31649)
• d3abafc Validate FeatureVectorizer batch sizes (#31671)
• 1441b36 [WebGPU] Add MRotaryEmbedding support (#31976)
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