com.microsoft.BiasGelu
com.microsoft · ONNX Runtime contrib operator · contrib since_version 1
Description
Applies GELU to A + B, where the 1-D bias B is broadcast along the last dimension of A. This implementation supports float16 and float32; the schema's double and bfloat16 types are not implemented.
See the ONNX Runtime BiasGelu contrib-operator spec for the reference semantics.
Inputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
A |
A |
T |
— | — | The main input tensor of any shape. | required |
B |
B |
T |
1 |
— | 1-D bias tensor whose length equals the last dimension of A. |
required |
Outputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
C |
C |
T |
same as A |
same as A |
Output tensor after applying GELU to A + B; same shape as A. |
required |
Type constraints
| Variable | Allowed dtypes |
|---|---|
T |
float32, float16 |
Files
metadata.json— kernel metadata (id, digests, provenance)manifest.json— the op contract (source of truth)test.json— correctness casesbench.json— benchmark + tuning caseselementwise-bias-gelu.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/com.microsoft.BiasGelu", { version: 1 });
const { C } = await kernel({ A: { data: AData, shape: [3] }, B: { data: BData, shape: [3] } });
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Requires WebGPU support. See the compatibility table.