ai.onnx.Cast
ai.onnx · standard ONNX operator · ONNX opset ≥ 13
Description
Casts every element of the input tensor to a supported target numeric dtype, producing an output of the same shape. A conversion may change values, for example when narrowing an integer or converting a float to boolean.
See the ONNX Cast spec for the reference semantics.
Inputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
input |
x |
T |
— | — | Input tensor to be cast. | required |
Outputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
output |
y |
U |
same as input |
same as input |
Output tensor with the same shape as the input, with elements converted to the target type. | required |
Attributes
Attributes and default values (overridable per request):
| Attribute | Default | Description |
|---|---|---|
to |
— | Required TensorProto DataType enum integer naming the output element type. |
Type constraints
| Variable | Allowed dtypes |
|---|---|
T |
float32, float16, uint32, int32, uint8, int8, bool |
U |
float32, float16, uint32, int32, uint8, int8, bool |
Files
metadata.json— kernel metadata (id, digests, provenance)manifest.json— the op contract (source of truth)test.json— correctness casesbench.json— benchmark + tuning casescast-scalar-x4.wgsl.jinjaunary-scalar.wgsl.jinjaunary-vec4.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/ai.onnx.Cast", { version: 1 });
const { y } = await kernel({ x: { data: xData, shape: [] } }, {
attrs: { to: 6 },
});
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Requires WebGPU support. See the compatibility table.