ai.onnx.Mish

ai.onnx · standard ONNX operator · ONNX opset ≥ 18

Description

Applies the Mish activation function elementwise: mish(x) = x * tanh(ln(1 + e^x)). Mish is a self-regularized non-monotonic activation that smoothly gates its input using a softplus-based tanh.

See the ONNX Mish spec for the reference semantics.

Inputs

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

Outputs

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

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.Mish", { version: 1 });
const { y } = await kernel({ x: { data: xData, shape: [] } });
Downloads last month
-
kernel
webgpu
wgsl
apache-2.0
WebGPU

Requires WebGPU support. See the compatibility table.