| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # ai.onnx.Transpose |
|
|
| `ai.onnx` · standard ONNX operator · ONNX opset ≥ 13 |
|
|
| ## Description |
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| Transposes the input tensor by permuting its axes according to the `perm` attribute. Axis `i` of the output corresponds to axis `perm[i]` of the input; if `perm` is omitted, the axes are reversed (`n-1, ..., 0`). |
|
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| See the [ONNX `Transpose` spec](https://onnx.ai/onnx/operators/onnx__Transpose.html) for the reference semantics. |
|
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| ## Inputs |
|
|
| | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `data` | `x` | `T` | — | — | The input tensor to transpose. | required | |
|
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| ## Outputs |
|
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| | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `transposed` | `y` | `T` | same as `data` | — | The transposed output tensor with permuted axes. | required | |
|
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| ## Attributes |
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| Attributes and default values (overridable per request): |
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| | Attribute | Default | Description | |
| | --- | --- | --- | |
| | `perm` | — | Optional permutation of the input axes. It must contain every axis from 0 through rank - 1 exactly once. When omitted, the axes are reversed. | |
|
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| ## Type constraints |
|
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| | Variable | Allowed dtypes | |
| | --- | --- | |
| | `T` | `float32`, `float16`, `int32`, `int16`, `uint32`, `uint8`, `int8`, `bool` | |
|
|
| ## 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 |
| - [`datamove-flat-copy.wgsl.jinja`](build/webgpu/datamove-flat-copy.wgsl.jinja) |
| - [`datamove-transpose-2d-tiled-scalar.wgsl.jinja`](build/webgpu/datamove-transpose-2d-tiled-scalar.wgsl.jinja) |
| - [`datamove-transpose-2d-tiled.wgsl.jinja`](build/webgpu/datamove-transpose-2d-tiled.wgsl.jinja) |
| - [`datamove-transpose-vec4.wgsl.jinja`](build/webgpu/datamove-transpose-vec4.wgsl.jinja) |
| - [`transpose.wgsl.jinja`](build/webgpu/transpose.wgsl.jinja) |
|
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| ## Use with `@huggingface/kernels` |
|
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| The loader automatically allocates outputs whose metadata it can derive from the manifest contract and this call. |
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| The explicit `outputs` entries provide shape and logical dtype metadata for the results listed below: |
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| - `y` |
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| Each entry either requests an optional result or supplies metadata that cannot be inferred from the inputs. |
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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.Transpose", { version: 1 }); |
| // Explicit destinations request optional results or supply metadata that cannot be inferred. |
| const { y } = await kernel({ x: { data: xData, shape: [] } }, { |
| outputs: { y: { shape: [], dtype: "float32" } }, |
| }); |
| ``` |
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|
