library_name: kernels
license: apache-2.0
tags:
  - kernel
  - webgpu
  - wgsl

ai.onnx.Softplus

ai.onnx · standard ONNX operator · ONNX opset ≥ 1

Description

Applies the softplus activation elementwise: y = ln(exp(x) + 1). The output has the same shape as the input.

See the ONNX Softplus 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
• unary-scalar.wgsl.jinja
• unary-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.Softplus", { version: 1 });
const { y } = await kernel({ x: { data: xData, shape: [3] } });