ai.onnx.Pow

ai.onnx · standard ONNX operator · ONNX opset ≥ 15

Description

Computes elementwise exponentiation Z = X ^ Y, applying f(x) = x^y to each element. Supports multidirectional (NumPy-style) broadcasting between X and Y.

See the ONNX Pow spec for the reference semantics.

Inputs

Outputs

Type constraints

Files

• metadata.json — kernel metadata (id, digests, provenance)
• manifest.json — the op contract (source of truth)
• test.json — correctness cases
• bench.json — benchmark + tuning cases
• pow-scalar-exponent-vec4.wgsl.jinja
• pow-vec4.wgsl.jinja
• pow.wgsl.jinja

Use with @huggingface/kernels

The loader derives every required output's shape and logical dtype from the manifest contract and this call. It then allocates the result tensors automatically.

The version: 1 option selects the published kernel contract; it is independent of any operator opset, contrib since_version, or model 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.Pow", { version: 1 });
const { z } = await kernel({ x: { data: xData, shape: [1] }, y: { data: yData, shape: [1] } });