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| library_name: kernels | |
| license: apache-2.0 | |
| tags: | |
| - kernel | |
| - webgpu | |
| - wgsl | |
| # ai.onnx.SplitToSequence | |
| `ai.onnx` · internal tensor lowering (non-standard) · reviewed against ONNX opset 11 | |
| ## Description | |
| Internal fixed-output split lowering that returns two, three, four, or six tensors with invocation-supplied shapes. It does not construct an ONNX sequence value. | |
| See the [standard ONNX `SplitToSequence` spec](https://onnx.ai/onnx/operators/onnx__SplitToSequence.html) for the contract this internal lowering does not implement. | |
| ## Inputs | |
| | Name | Logical dtype | Rank | Shape | Description | Presence | | |
| | --- | --- | --- | --- | --- | --- | | |
| | `input` | `T` | — | — | The tensor to split. | required | | |
| | `split` | `S` | — | — | Length of each output slice: a scalar for uniform chunks or a 1-D tensor of per-output lengths. | optional | | |
| ## Outputs | |
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | | |
| | --- | --- | --- | --- | --- | --- | --- | | |
| | `y0` | `Y0` | `T` | derived | — | First output tensor slice. | required | | |
| | `y1` | `Y1` | `T` | derived | — | Second output tensor slice. | required | | |
| | `y2` | `Y2` | `T` | derived | — | Third output tensor slice. | optional | | |
| | `y3` | `Y3` | `T` | derived | — | Fourth output tensor slice. | optional | | |
| | `y4` | `Y4` | `T` | derived | — | Fifth output tensor slice. | optional | | |
| | `y5` | `Y5` | `T` | derived | — | Sixth output tensor slice. | optional | | |
| ## Attributes | |
| Default values (overridable per request): | |
| | Attribute | Default | Description | | |
| | --- | --- | --- | | |
| | `axis` | `0` | Axis along which to split; negative values count from the back. Accepted range is `[-rank, rank-1]`. | | |
| | `keepdims` | `1` | Whether to keep the split dimension in the output (default `1`). Ignored when `split` is provided. | | |
| ## Type constraints | |
| | Variable | Allowed dtypes | | |
| | --- | --- | | |
| | `T` | `float32`, `float16`, `bool` | | |
| | `S` | `uint32` | | |
| ## 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 | |
| - [`split-to-sequence.wgsl.jinja`](build/webgpu/split-to-sequence.wgsl.jinja) | |
| ## Use with `@huggingface/kernels` | |
| ```sh | |
| npm install --save-exact @huggingface/kernels@0.0.1-preview.3 | |
| ``` | |
| 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: | |
| - `y0` | |
| - `y1` | |
| 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.SplitToSequence", { version: 1 }); | |
| // Explicit destinations request optional results or supply metadata that cannot be inferred. | |
| const { y0, y1 } = await kernel({ input: { data: inputData, shape: [3, 2] } }, { | |
| outputs: { | |
| y0: { shape: [1, 2], dtype: "float32" }, | |
| y1: { shape: [1, 2], dtype: "float32" }, | |
| }, | |
| }); | |
| ``` | |