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| library_name: kernels | |
| license: apache-2.0 | |
| tags: | |
| - kernel | |
| - webgpu | |
| - wgsl | |
| # ai.onnx.Sum | |
| `ai.onnx` · standard ONNX operator · ONNX opset ≥ 13 | |
| ## Description | |
| Computes the elementwise sum of one or more input tensors with multidirectional (NumPy-style) broadcasting. All inputs and the output must share the same data type. | |
| See the [ONNX `Sum` spec](https://onnx.ai/onnx/operators/onnx__Sum.html) for the reference semantics. | |
| ## Inputs | |
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | | |
| | --- | --- | --- | --- | --- | --- | --- | | |
| | `a` | `A` | `T` | — | — | First input tensor. | required | | |
| | `b` | `B` | `T` | — | — | Second input tensor (optional). | optional | | |
| | `c` | `C` | `T` | — | — | Third input tensor (optional). | optional | | |
| | `d` | `D` | `T` | — | — | Fourth input tensor (optional). | optional | | |
| ## Outputs | |
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | | |
| | --- | --- | --- | --- | --- | --- | --- | | |
| | `y` | `sum` | `T` | derived | derived | Elementwise sum of all provided input tensors. | required | | |
| ## Type constraints | |
| | Variable | Allowed dtypes | | |
| | --- | --- | | |
| | `T` | `float32`, `float16` | | |
| ## 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 cases | |
| - [`datamove-elementwise-copy.wgsl.jinja`](build/webgpu/datamove-elementwise-copy.wgsl.jinja) | |
| - [`summean-broadcast.wgsl.jinja`](build/webgpu/summean-broadcast.wgsl.jinja) | |
| - [`summean-vec4.wgsl.jinja`](build/webgpu/summean-vec4.wgsl.jinja) | |
| ## Use with `@huggingface/kernels` | |
| ```sh | |
| npm install --save-exact @huggingface/kernels@0.0.1-preview.3 | |
| ``` | |
| 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. | |
| ```js | |
| import { getKernel } from "@huggingface/kernels"; | |
| const kernel = await getKernel("webgpu-kernels/ai.onnx.Sum", { version: 1 }); | |
| const { y } = await kernel({ a: { data: aData, shape: [3] } }); | |
| ``` | |