| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # ai.onnx.BitShift |
|
|
| `ai.onnx` · standard ONNX operator · ONNX opset ≥ 11 |
|
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| ## Description |
|
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| Performs an elementwise bitwise shift on unsigned integer tensors. `X` is shifted left or right by the amounts in `Y`, with the direction controlled by the `direction` attribute. Supports multidirectional (NumPy-style) broadcasting between `X` and `Y`. |
|
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| See the [ONNX `BitShift` spec](https://onnx.ai/onnx/operators/onnx__BitShift.html) for the reference semantics. |
|
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| ## Inputs |
|
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| | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `X` | `x` | `T` | — | — | Input tensor to be shifted. | required | |
| | `Y` | `y` | `T` | — | — | Tensor specifying the number of bit positions to shift each element of X. | required | |
|
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| ## Outputs |
|
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| | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `Z` | `z` | `T` | derived | broadcast result of `X` and `Y` | Output tensor with the same shape as the broadcast result of X and Y. | required | |
|
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| ## Attributes |
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| Attributes and default values (overridable per request): |
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| | Attribute | Default | Description | |
| | --- | --- | --- | |
| | `direction` | — | Direction of the bit shift: `LEFT` shifts bits toward higher significance (increasing value), while `RIGHT` shifts toward lower significance (decreasing value). | |
|
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| ## Type constraints |
|
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| | Variable | Allowed dtypes | |
| | --- | --- | |
| | `T` | `uint32`, `uint8` | |
|
|
| ## Files |
|
|
| - [`metadata.json`](build/webgpu/metadata.json) — kernel metadata (id, digests, 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 |
| - [`bitshift-vec4.wgsl.jinja`](build/webgpu/bitshift-vec4.wgsl.jinja) |
| - [`bitshift.wgsl.jinja`](build/webgpu/bitshift.wgsl.jinja) |
|
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| ## Use with `@huggingface/kernels` |
|
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| The loader derives every required output's shape and logical dtype from the manifest contract and this call. |
| It then allocates the result tensors automatically. |
|
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| The `version: 1` option selects the published kernel contract; it is independent of any operator opset, contrib `since_version`, or model version. |
|
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| 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.BitShift", { version: 1 }); |
| const { z } = await kernel({ x: { data: xData, shape: [2] }, y: { data: yData, shape: [2] } }, { |
| attrs: { direction: "RIGHT" }, |
| }); |
| ``` |
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|