ai.onnx.HannWindow
ai.onnx · standard ONNX operator · ONNX opset ≥ 17
Description
Generates a Hann window of a given length using the formula 0.5 - 0.5 * cos(2π * n / N), where N is size for periodic mode or size - 1 for symmetric mode. The output is a 1-D tensor of length size.
See the ONNX HannWindow spec for the reference semantics.
Inputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
size |
size |
T1 |
0 |
— | Scalar indicating the number of elements in the output window. | required |
Outputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
output |
y |
T2 |
1 |
— | 1-D Hann window tensor of shape [size]. |
required |
Attributes
Default values (overridable per request):
| Attribute | Default | Description |
|---|---|---|
output_datatype |
1 |
Data type of the output tensor, encoded as a DataType enum value from TensorProto (default 1 = FLOAT). |
periodic |
1 |
If 1 (default), returns a periodic window of length size; if 0, returns a symmetric window of length size. |
Type constraints
| Variable | Allowed dtypes |
|---|---|
T1 |
int32 |
T2 |
float32, float16, uint32, int32, uint8, int8, int16 |
Files
metadata.json— kernel metadata (id, digests, provenance)manifest.json— the op contract (source of truth)test.json— correctness casesbench.json— benchmark + tuning caseswindow-cosine-sum.wgsl.jinja
Use with @huggingface/kernels
The loader automatically allocates outputs whose metadata it can derive from the manifest contract and this call.
The explicit outputs entries provide shape and logical dtype metadata for the results listed below:
y
Each entry either requests an optional result or supplies metadata that cannot be inferred from the inputs.
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.HannWindow", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { y } = await kernel({ size: { data: sizeData, shape: [] } }, {
outputs: { y: { shape: [1], dtype: "float32" } },
});
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Requires WebGPU support. See the compatibility table.