ai.onnx.Clip

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

Description

Limits each element of the input tensor to the interval [min, max], equivalent to Min(max, Max(input, min)). Each bound is an optional scalar input tensor; an omitted bound defaults to the input dtype's lowest or highest numeric value. When min exceeds max, all elements are set to max.

See the ONNX Clip spec for the reference semantics.

Inputs

Name Bind key Logical dtype Rank Shape Description Presence
input input T Input tensor whose elements are to be clipped. required
min min T 0 [] Scalar lower bound; elements below this value are replaced by it. optional
max max T 0 [] Scalar upper bound; elements above this value are replaced by it. optional

Outputs

Name Bind key Logical dtype Rank Shape Description Presence
output output T same as input same as input Output tensor with each element clipped to the specified interval. required

Type constraints

Variable Allowed dtypes
T float32, float16, int32, uint32, int8, uint8

Files

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.Clip", { version: 1 });
const { output } = await kernel({ input: { data: inputData, shape: [3] } });
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Requires WebGPU support. See the compatibility table.