ai.onnx.Constant
ai.onnx · standard ONNX operator · ONNX opset ≥ 24
Description
Produces a numeric constant from ONNX's tensor-valued value attribute or its float scalar/list shorthands. Sparse, string, and int64-only shorthand attributes are not yet supported.
See the ONNX Constant spec for the reference semantics.
Outputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
output |
output |
T |
— | — | Output tensor containing the constant value(s) specified by the attribute. | required |
Attributes
Attributes and default values (overridable per request):
| Attribute | Default | Description |
|---|---|---|
value |
— | Tensor-valued constant represented as { dtype, shape, values }; dtype and shape must match the output contract and values supplies the tensor elements in row-major order. |
value_float |
— | A single float32 value producing a scalar tensor. |
value_floats |
— | Float32 values producing a one-dimensional tensor. |
Type constraints
| Variable | Allowed dtypes |
|---|---|
T |
float32, float16, int32, int16, uint32, int8, uint8, bool |
Files
metadata.json— kernel metadata (id, digests, provenance)manifest.json— the op contract (source of truth)test.json— correctness casesbench.json— benchmark + tuning casesconstant.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.
import { getKernel } from "@huggingface/kernels";
const kernel = await getKernel("webgpu-kernels/ai.onnx.Constant", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { output } = await kernel({}, {
attrs: { value_float: -2.5 },
outputs: { output: { shape: [], dtype: "float32" } },
});
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Requires WebGPU support. See the compatibility table.