ai.onnx.GatherND

ai.onnx · standard ONNX operator · ONNX opset ≥ 13

Description

Gathers slices from data using an N-dimensional index tensor, producing an output of rank q + r - indices_shape[-1] - 1 - b where r is the data rank, q the indices rank, and b the number of batch dimensions. Each index-tuple in indices selects either a scalar or a sub-tensor slice from data; this is the inverse of ScatterND.

See the ONNX GatherND spec for the reference semantics.

Inputs

Outputs

Attributes

Default values (overridable per request):

Type constraints

Files

• metadata.json — kernel metadata (id, digests, per-variant templates, provenance)
• manifest.json — the op contract (source of truth)
• test.json — correctness cases
• bench.json — benchmark + tuning cases
• datamove-gather-row.wgsl.jinja
• gather-nd.wgsl.jinja

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.GatherND", { version: 1 });
const { output } = await kernel({
  data: { data: dataData, shape: [2, 2] },
  indices: { data: indicesData, shape: [2, 1, 2] },
});