dispatch_table.h

Registers every onnx_shapes ComputeShape* shape function (the built-in ai.onnx/ai.onnx.ml/… operator set) with the generic dispatch table owned by onnx_core (:cpp:func:core::shapes::DispatchTable).

The shape functions themselves (e.g. math::ComputeShapeAbs) stay in onnx_shapes, one per onnx_extensions/shapes/shapes/<domain>/shape_<domain>.cc file, and this translation unit is the single place that wires all of them into the shared registry via :cpp:func:RegisterShapeFunctions. Keeping the registration here (instead of in onnx_core) preserves the onnx_shapes -> onnx_core dependency direction: onnx_core never needs to know about onnx_shapes’s operator implementations.

namespace onnx_light

Alias that makes onnx-light headers compatible with code that references ONNX_LIGHT_NAMESPACE (the macro used in the standard onnx package).

Set to ONNX_LIGHT_NAMESPACE so both names resolve to the same namespace.

Symbol-visibility attribute for the public onnx-light C++ API.

Maps the upstream compatibility macro to onnx-light’s explicit proto ABI annotation. This keeps declarations from vendored ONNX headers visible when lib_onnx_proto uses hidden visibility by default.

Namespace alias so that ONNX C++ code (and consumers such as onnxruntime) that refers to the literal onnx namespace — rather than the ONNX_NAMESPACE macro — resolves to the onnx-light namespace. The standard onnx package lives in namespace onnx; onnx-light uses onnx_light (via ONNX_LIGHT_NAMESPACE), so this alias keeps onnx-light a true drop-in. It is only introduced when the onnx-light namespace differs from onnx.

namespace onnx_shapes

Functions

void RegisterShapeFunctions()

Registers every built-in onnx_shapes shape function with :cpp:func:core::shapes::RegisterComputeShapeFn. Idempotent and cheap to call more than once (the actual registration work only happens once, guarded by a function-local static).

Unlike onnx_lib’s OpSchemaRegistry::map() (which can lazily self-register because both the accessor and the registration functions live in the same library), core::shapes::DispatchTable() cannot do this: onnx_core must not depend on or call into onnx_shapes. lib_onnx_shape is also a plain static archive, so a file-scope static object with no externally-referenced symbol is not reliably linked in either. Every entry point that uses the shape-inference engine (Python bindings, C++ unit tests, examples, fuzzers, …) must therefore call this function explicitly before calling :cpp:func:core::shapes::InferShapesModel or :cpp:func:core::shapes::ShapesContext::ComputeShapeNode.

void RegisterPeakMemoryFunctions()

Registers every built-in onnx_shapes peak-memory function with :cpp:func:core::shapes::RegisterComputePeakMemoryFn. Mirrors :cpp:func:RegisterShapeFunctions for the peak-memory dispatch table: idempotent, guarded by a function-local static, and must be called explicitly before :cpp:func:core::shapes::ComputePeakMemory can resolve a built-in operator (operators without a registered function report 0).