ai.onnx.ConstantOfShape

ai.onnx · standard ONNX operator · ONNX opset ≥ 9

Description

Generates a tensor filled with a constant value and an input-specified shape. The shape is provided as a 1-D integer tensor; if empty, the output is a scalar. The fill value and its dtype are taken from the value attribute, defaulting to 0 of type float32.

See the ONNX ConstantOfShape spec for the reference semantics.

Inputs

Outputs

Attributes

Attributes and default values (overridable per request):

Type constraints

Implementation variants

One implementation is selected per call from the device capabilities, the request shapes and the dtypes; these notes say what each one covers.

• fill_float_tail — Uses vec4 stores for the aligned prefix and a one-invocation scalar tail when the element count is not divisible by four.
• fill_integer_tail — Uses vec4 stores for the aligned prefix and a one-invocation scalar tail when the element count is not divisible by four.

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
• constant-of-shape.wgsl.jinja

Use with @huggingface/kernels

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

Outputs with inferable metadata are allocated automatically. Explicit outputs entries request optional results or provide metadata that cannot be inferred from the supplied inputs and attributes.

This example supplies explicit metadata for:

• output

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.ConstantOfShape", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { output } = await kernel({ input: { data: inputData, shape: [2] } }, {
  outputs: { output: { shape: [2, 3], dtype: "float32" } },
});