ai.onnx.IsInf

ai.onnx · standard ONNX operator · ONNX opset ≥ 20

Description

Maps each element of a floating-point tensor to true if it is infinite and false otherwise. The detect_negative and detect_positive attributes independently control whether negative and positive infinity are considered infinite for this mapping.

See the ONNX IsInf spec for the reference semantics.

Inputs

Name Upstream name Logical dtype Rank Shape Description Presence
x X T Input floating-point tensor. required

Outputs

Name Upstream name Logical dtype Rank Shape Description Presence
y Y B same as x same as x Boolean output tensor with the same shape as the input; true where the input is infinite. required

Attributes

Default values (overridable per request):

Attribute Default Description
detect_negative 1 When 1 (default), negative infinity maps to true; set to 0 to map negative infinity to false.
detect_positive 1 When 1 (default), positive infinity maps to true; set to 0 to map positive infinity to false.

Type constraints

Variable Allowed dtypes
T float32, float16
B 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.IsInf", { version: 1 });
const { y } = await kernel({ x: { data: xData, shape: [] } });
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Requires WebGPU support. See the compatibility table.