ai.onnx.Where

ai.onnx · standard ONNX operator · ONNX opset ≥ 16

Description

Selects elements from X or Y according to a boolean condition, following NumPy-style multidirectional broadcasting. Where condition is true, the output takes the value from X; otherwise it takes the value from Y.

See the ONNX Where spec for the reference semantics.

Inputs

Name Upstream name Logical dtype Rank Shape Description Presence
condition C Boolean mask; nonzero entries select from X, zero entries select from Y. required
x X T Values selected at indices where condition is true. required
y Y T Values selected at indices where condition is false. required

Outputs

Name Logical dtype Rank Shape Description Presence
output T derived broadcast result of condition, x, and y Tensor of shape equal to the broadcasted shape of condition, X, and Y. required

Type constraints

Variable Allowed dtypes
C bool
T float32, float16, uint32, int32, int16, 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.Where", { version: 1 });
const { output } = await kernel({
  condition: { data: conditionData, shape: [] },
  x: { data: xData, shape: [] },
  y: { data: yData, shape: [] },
});
Downloads last month
-
kernel
webgpu
wgsl
apache-2.0
WebGPU

Requires WebGPU support. See the compatibility table.