Add Function Body

Follow the full guide in docs/AddFunctionBody.md.

File Locations

Method 1: Simple String-Based Function Body

ONNX_OPERATOR_SET_SCHEMA(
    LessOrEqual, 16,
    OpSchema()
        // ... inputs, outputs, type constraints ...
        .TypeAndShapeInferenceFunction(inferenceFunction)
        .FunctionBody(R"ONNX(
        {
            O1 = Less (A, B)
            O2 = Equal (A, B)
            C = Or (O1, O2)
        }
        )ONNX"));

With explicit opset version:

        .FunctionBody(R"ONNX(...)ONNX", 18)  // Valid from opset 18

Referencing attributes with @attr_name:

        .FunctionBody(R"ONNX(
          {
            Alpha = Constant <value_float: float = @alpha>()
            AlphaCast = CastLike (Alpha, X)
            ...
          }
        )ONNX")

Method 2: Context-Dependent Function Body

For ops whose decomposition varies based on attributes or optional inputs:

static bool BuildFunctionBodyMyOp(
    const FunctionBodyBuildContext& ctx,
    const OpSchema& schema,
    FunctionProto& functionProto) {
  FunctionBuilder builder(functionProto);
  // Build graph based on ctx.hasInput(), ctx.getAttribute(), etc.
  builder.Add("output = SomeOp (input)");
  schema.BuildFunction(functionProto);
  return true;
}

// Register:
    .SetContextDependentFunctionBodyBuilder(BuildFunctionBodyMyOp)

FunctionBuilder API

FunctionBuilder builder(functionProto);
builder.Add("Y = Relu (X)");                          // Add node
builder.Const("alpha", std::vector<float>{0.01f});    // Constant tensor
builder.Const1D("axes", int64_t(1));                  // 1-D constant
builder.Add(R"(                                       // Multi-line
    X_Sub = Sub (X, X_Max)
    X_Exp = Exp (X_Sub)
)");
builder.AddOpset("", 18);                             // Opset dependency
schema.BuildFunction(functionProto);                  // Finalize
return true;

Multiple Opset Versions

    .SetContextDependentFunctionBodyBuilder(builderForOpset13)
    .SetContextDependentFunctionBodyBuilder(builderForOpset18, 18)

ONNX Function Body Syntax

Function body strings use the ONNX text format ("onnxtxt"). See the onnxtxt skill for the full syntax cheat sheet, attribute references (@attr_name), Constant <value = ...> forms, CastLike vs Cast, body-subgraph idioms, and parser tests. Quick reminders specific to function bodies:

• Variable names are local intermediates; input/output names must match the schema's declared names.
• Reference enclosing-op attributes with @attr_name — and only those declared in .Attr(...) calls.
• Use CastLike (not Cast) when the target type depends on another input.

Code Style: Prefer Named Functions

Define context-dependent function body builders as separate named functions rather than inline lambdas within ONNX_OPERATOR_SET_SCHEMA. The macro expansion makes setting breakpoints on inline lambdas unreliable in debuggers.

Simple string-based .FunctionBody(R"ONNX(...)ONNX") definitions don't have this issue.

After Making Changes

python onnx/defs/gen_doc.py
lintrunner -a --output oneline

Common Mistakes

• Forgetting schema.BuildFunction(functionProto) at end of context-dependent builders
• Forgetting to return true from the builder function
• Variable names conflicting with input/output names
• Using Cast instead of CastLike for dynamic type matching
• Function body not producing all declared outputs
• Using @attr_name for an attribute not declared in .Attr() calls