ai.onnx.Max

ai.onnx · standard ONNX operator · ONNX opset ≥ 13

Description

Computes the elementwise maximum across one or more input tensors with NumPy-style multidirectional broadcasting. All inputs must share the same data type, and the output has the broadcasted shape.

See the ONNX Max 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
• datamove-elementwise-copy.wgsl.jinja
• minmax-broadcast.wgsl.jinja
• minmax-vec4.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.Max", { version: 1 });
const { y } = await kernel({ a: { data: aData, shape: [] } });