ONNX Runtime 发布: ONNX Runtime v1.30.0

来源摘要

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](https://github.com/microsoft/onnxruntime/pull/32168), [#32340](https://github.com/microsoft/onnxruntime/pull/32340), [#32515](https://github.com/microsoft/onnxruntime/pull/32515)). - Improved WebGPU PagedAttention, added GPT-OSS support and INT8 KV-cache block quantization, and extended convolution optimizations ([#31727](https://github.com/microsoft/onnxruntime/pull/31727), [#32277](https://github.com/microsoft/onnxruntime/pull/32277), [#32284](https://github.com/microsoft/onnxruntime/pull/32284), [#32420](https://github.com/microsoft/onnxruntime/pull/32420)). - Added fused CPU LinearAttention kernels for AVX-512, Arm64 NEON, and SVE, plus AVX2 LayerNorm/RMSNorm acceleration ([#31674](https://github.com/microsoft/onnxruntime/pull/31674), [#31973](https://github.com/microsoft/onnxruntime/pull/31973), [#32178](https://github.com/microsoft/onnxruntime/pull/32178), [#32356](https://github.com/microsoft/onnxruntime/pull/32356)). - Added Go bindings for the ONNX Runtime C API and DeepSeek Engram contrib operators ([#29615](https://github.com/microsoft/onnxruntime/pull/29615), [#32268](https://github.com/microsoft/onnxruntime/pull/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](https://github.com/microsof