ai.onnx.Expand
ai.onnx · standard ONNX operator · ONNX opset ≥ 13
Description
Broadcasts input to a given shape following NumPy-style rules: dimensions are right-aligned, and corresponding dimensions must be equal or one of them must be 1. The output shape may differ from shape when a requested dimension is 1 or shape has fewer dimensions than input.
See the ONNX Expand spec for the reference semantics.
Inputs
| Name | Bind key | Logical dtype | WebGPU storage | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|---|
input |
input |
T |
runtime-selected; narrow integers and bool use 32-bit slots | — | — | Input tensor to broadcast. | required |
shape |
shape |
S |
uint32 |
1 |
— | Logical int64 1-D tensor specifying the non-negative target shape; WebGPU stores it as uint32. | required |
Outputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
output |
output |
T |
derived | — | Output tensor with the broadcasted shape. | required |
Type constraints
| Variable | Allowed dtypes |
|---|---|
T |
float32, float16, uint32, int32, int16, uint8, int8, bool |
S |
int64 |
Files
metadata.json— kernel metadata (id, digests, provenance)manifest.json— the op contract (source of truth)test.json— correctness casesbench.json— benchmark + tuning casesexpand-vec4.wgsl.jinjaexpand.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:
output
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.Expand", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { output } = await kernel({
input: { data: inputData, shape: [1, 4] },
shape: { data: shapeData, shape: [2] },
}, {
outputs: { output: { shape: [2, 4], dtype: "int16" } },
});
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Requires WebGPU support. See the compatibility table.