0.1.3

New Features

• Add SerializeOptions.max_serialized_size_bytes to hard-cap serialization output size (#3207)
• Show node indexes in pretty_onnx graph output (#3031)
• Add --token support to fillshape for binding symbolic dimension tokens to ranges (#3028)
• Add include_release option to to_svg and to_mermaid (#3020)
• Add fillshape --release-info to emit release metadata independently (#3019)
• Add verbose progress output for fillshape execution (#3012)
• Expose random input generation as onnx_light.onnx.tools.make_random_input (#3009)
• Add Logger to onnx_helpers (#2999)
• Add dim_ranges_from_expressions to infer dimension ranges from equality constraints (#2988)
• Add C++/nanobind shape, axes, and weight metadata tagging and tag-aware Mermaid/SVG rendering (#2959)
• Add runtime progress output for verbose ReferenceEvaluator execution (#2961)
• Add run subcommand to generate random inputs and execute a model from the CLI (#2956)
• Add --verbose [LEVEL] support to fillshape CLI (#2952)
• Add ChaCha20-Poly1305 support for encrypted model I/O (ONNXCRY2) (#2948)
• Add light-only ai.rt DelayedInitializer schema, runtime kernel, and shape inference (#2940)
• Add pre-serialization weight rewrite callback for model save paths (#2944)
• Add python -m onnx_light fillshape command (#2938)
• Implement ParseFromIstream for all proto classes (#2942)
• Add support for a callback function when parsing a model (#2928)
• Add include_inplace option to to_mermaid/to_svg renderers (#2930)
• Add function to record in-place reuse opportunities into node metadata (#2918)
• Guard graph inputs from in-place overwrite with an opt-in flag (#2916)
• Add ChaCha20 raw_data callback example for weight serialization/parsing (#2957)

Improvements

• Update onnxruntime integration and related compatibility changes (#3205)
• Mirror upstream onnx#8157: fix nanobind Python target resolution in cross-compile CMake path (#3217)
• Add C++ backend test for kRelease event in shape inference (#3105)
• Align floor-division simplification with Python // semantics (#3026)
• Propagate Reshape shape-tag metadata backward through producer chains (#3024)
• Reuse the core shape-inference API for fillshape shape-tag metadata writing (#3022)
• Seed weight tags for rank-2 FLOAT graph inputs in shape-tag inference (#3021)
• Fix empty-axis broadcasting and add half-precision RMSNormalization support (#3018)
• Extend ComputeContext with shape-tag release info (#3017)
• Allow Transpose in-place reuse detection when storage size is equal (#3015)
• Move tiny external-tensor inlining from fillshape into ParseOptions (#3011)
• Move inplace_reuse and value-tag helpers into onnx_optim.annotations (#3007)
• Show release, in-place, and shape-tag annotations in fillshape --show output (#3005)
• Fix symbolic shape inference for Reshape shapes built from Unsqueeze(Gather(Shape(...))) (#3003)
• Simplify nested floor divisions such as x//5//2 into x//10 (#3001)
• Slice shape inference now emits symbolic expressions instead of fresh names (#2954)
• Simplify divisible additive offsets for floor and exact division in expressions (#2950)
• Improve to_svg layout: shorten edges and reduce crossings (#2932)
• Accept arbitrary iterables in RepeatedField.extend/__init__ (#2934)
• Implement deleter in ByteSpan and TensorProto (#2926)
• Refactor ComputeInPlaceReuse into a ComputeContext class (#2924)