ai.onnx.Unsqueeze

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

Description

Inserts size-1 dimensions into a tensor at the specified axis positions. The axes input lists dimension indices in the output shape where new dimensions of size 1 are inserted; negative values count from the back of the output rank. The output expanded has the same data as data with rank increased by the number of axes.

See the ONNX Unsqueeze spec for the reference semantics.

Inputs

Outputs

Type constraints

Files

• metadata.json — kernel metadata (id, digests, provenance)
• manifest.json — the op contract (source of truth)
• test.json — correctness cases
• bench.json — benchmark + tuning cases
• datamove-elementwise-copy.wgsl.jinja
• datamove-flat-copy.wgsl.jinja

Use with @huggingface/kernels

The loader automatically allocates outputs whose metadata it can derive from the manifest contract and this call.

The explicit outputs entries provide shape and logical dtype metadata for the results listed below:

• expanded

Each entry either requests an optional result or supplies metadata that cannot be inferred from the inputs.

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.Unsqueeze", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { expanded } = await kernel({
  data: { data: dataData, shape: [] },
  axes: { data: axesData, shape: [1] },
}, {
  outputs: { expanded: { shape: [1], dtype: "float32" } },
});