ai.onnx.If

ai.onnx · internal tensor lowering (non-standard) · reviewed against ONNX opset 25

Description

Support status: the standard ONNX If control-flow operator is not implemented because standalone kernel packages cannot carry or execute its then_branch and else_branch graph attributes. This internal lowering only selects elementwise between two pre-evaluated, equal-sized tensors from a scalar condition and must not be treated as ONNX If.

See the standard ONNX If spec for the contract this internal lowering does not implement.

Inputs

Outputs

Type constraints

Files

• metadata.json — kernel metadata (id, digests, per-variant templates, provenance)
• manifest.json — the op contract (source of truth)
• test.json — correctness cases
• bench.json — benchmark + tuning cases
• if-select.wgsl.jinja

Use with @huggingface/kernels

npm install --save-exact @huggingface/kernels@0.0.1-preview.2

Outputs with inferable metadata are allocated automatically. Explicit outputs entries request optional results or provide metadata that cannot be inferred from the supplied inputs and attributes.

This example supplies explicit metadata for:

• y

The version: 1 option selects the published kernel contract; it is independent of any operator opset, contrib since_version, or model version. It follows the v1 branch as fixes land. To pin exact artifact bytes, pass a 40-character commit revision instead of version.

Replace each *Data placeholder with a typed array containing the corresponding input data.

import { getKernel } from "@huggingface/kernels";

const kernel = await getKernel("webgpu-kernels/ai.onnx.If", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { y } = await kernel({
  cond: { data: condData, shape: [1] },
  then_value: { data: then_valueData, shape: [1] },
  else_value: { data: else_valueData, shape: [1] },
}, {
  outputs: { y: { shape: [1], dtype: "float32" } },
});