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 Upstream name Logical dtype Rank Shape Description Presence
x input T Input tensor to be cast. required

Outputs

Name Upstream name Logical dtype Rank Shape Description Presence
y output U same as x same as x 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

Use with @huggingface/kernels

npm install --save-exact @huggingface/kernels@0.0.1-preview.2

Required output shapes and logical data types are inferred from the supplied inputs and attributes; result tensors are allocated automatically.

The version: 1 option selects the published kernel contract; it is independent of any operator opset, contrib since_version, or model version. It follows the v1 branch as fixes land. To pin exact artifact bytes, pass a 40-character commit revision instead of 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.