| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # 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](https://onnx.ai/onnx/operators/onnx__ConstantOfShape.html) for the reference semantics. |
|
|
| ## Inputs |
|
|
| | Name | Logical dtype | WebGPU storage | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `input` | `S` | `uint32` | `1` | — | Logical int64 1-D tensor whose elements define the output shape; all values must be non-negative and use uint32 WebGPU storage. | required | |
|
|
| ## Outputs |
|
|
| | Name | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | |
| | `output` | `T` | derived | — | Output tensor of the shape given by `input`, filled with the constant `value`. | required | |
|
|
| ## Attributes |
|
|
| Attributes and default values (overridable per request): |
|
|
| | Attribute | Default | Description | |
| | --- | --- | --- | |
| | `value` | — | Optional single-element tensor specifying the fill value and output dtype; defaults to 0 of type float32 if omitted. | |
|
|
| ## Type constraints |
|
|
| | Variable | Allowed dtypes | |
| | --- | --- | |
| | `S` | `int64` | |
| | `T` | `float32`, `float16`, `int32`, `int16`, `uint32`, `int8`, `uint8`, `bool` | |
|
|
| ## 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`](build/webgpu/metadata.json) — kernel metadata (id, digests, per-variant templates, provenance) |
| - [`manifest.json`](build/webgpu/manifest.json) — the op contract (source of truth) |
| - [`test.json`](build/webgpu/test.json) — correctness cases |
| - [`bench.json`](build/webgpu/bench.json) — benchmark + tuning cases |
| - [`constant-of-shape.wgsl.jinja`](build/webgpu/constant-of-shape.wgsl.jinja) |
|
|
| ## Use with `@huggingface/kernels` |
|
|
| ```sh |
| 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. |
|
|
| ```js |
| 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" } }, |
| }); |
| ``` |
|
|
