ai.onnx.CastLike
ai.onnx · standard ONNX operator · ONNX opset ≥ 25
Description
Casts every element of input to the same dtype as target_type, producing an output with the same shape as input. The target_type tensor itself is used only for its dtype and is not read elementwise.
See the ONNX CastLike spec for the reference semantics.
Inputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
input |
x |
T1 |
— | — | Input tensor whose elements are to be cast. | required |
target_type |
target |
T2 |
— | — | Tensor whose element type defines the destination dtype; its values are not used. | required |
Outputs
| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
|---|---|---|---|---|---|---|
output |
y |
T2 |
same as input |
same as input |
Output tensor with the same shape as input and the element type of target_type. |
required |
Attributes
Default values (overridable per request):
| Attribute | Default | Description |
|---|---|---|
round_mode |
"up" |
Rounding direction used only when casting to float8e8m0. The implemented non-float8 subset accepts the ONNX default "up". |
saturate |
1 |
Whether casts to float8 saturate at the finite range. The implemented non-float8 subset accepts the ONNX default 1. |
Type constraints
| Variable | Allowed dtypes |
|---|---|
T1 |
float32, float16, uint32, int32, uint8, int8, bool |
T2 |
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.CastLike", { version: 1 });
const { y } = await kernel({ x: { data: xData, shape: [] }, target: { data: targetData, shape: [3] } });
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Requires WebGPU support. See the compatibility table.