ai.onnx.Swish

ai.onnx · standard ONNX operator · ONNX opset ≥ 24

Description

Applies the Swish activation elementwise: Y = X * sigmoid(alpha * X). The output has the same shape and dtype as the input.

See the ONNX Swish spec for the reference semantics.

Inputs

Name Bind key Logical dtype Rank Shape Description Presence
X x T Values transformed elementwise by the Swish activation. required

Outputs

Name Bind key Logical dtype Rank Shape Description Presence
Y y T same as X same as X Output tensor of the same shape as the input, with Swish applied elementwise. required

Attributes

Default values (overridable per request):

Attribute Default Description
alpha 1 Coefficient multiplied with the input before the sigmoid; defaults to 1.0.

Type constraints

Variable Allowed dtypes
T float32, float16

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.Swish", { version: 1 });
const { y } = await kernel({ x: { data: xData, shape: [3] } });
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Requires WebGPU support. See the compatibility table.