| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # ai.onnx.Transpose |
|
|
| `ai.onnx` · standard ONNX operator · ONNX opset ≥ 13 |
|
|
| ## Description |
|
|
| 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`). |
|
|
| See the [ONNX `Transpose` spec](https://onnx.ai/onnx/operators/onnx__Transpose.html) for the reference semantics. |
|
|
| ## Inputs |
|
|
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `x` | `data` | `T` | — | — | The input tensor to transpose. | required | |
|
|
| ## Outputs |
|
|
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `y` | `transposed` | `T` | same as `x` | — | The transposed output tensor with permuted axes. | required | |
|
|
| ## Attributes |
|
|
| Attributes and default values (overridable per request): |
|
|
| | 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. | |
|
|
| ## Type constraints |
|
|
| | Variable | Allowed dtypes | |
| | --- | --- | |
| | `T` | `float32`, `float16`, `int32`, `int16`, `uint32`, `uint8`, `int8`, `bool`, `int64` | |
|
|
| ## 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. |
|
|
| - `strided_planes_vec4` — Tiles independent physical strided planes while preserving the intervening axis. Both global IO directions are contiguous inside the tile. Demoted when padding occupies more than half the tile slots. |
| - `tiled_scalar` — Stages ragged two-dimensional transpose planes through a padded workgroup tile so reads and writes remain coalesced when vec4 alignment is unavailable. |
| - `inner_vec4` — Vectorizes the contiguous innermost dimension for permutations that leave that axis in place. It assigns multiple vectors per invocation only when enough invocations remain to keep the dispatch populated. |
|
|
| ## 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-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) |
|
|
| ## 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. |
|
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| This example supplies explicit metadata for: |
|
|
| - `y` |
|
|
| 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.Transpose", { version: 1 }); |
| // Explicit destinations request optional results or supply metadata that cannot be inferred. |
| const { y } = await kernel({ x: { data: xData, shape: [2, 3] } }, { |
| outputs: { y: { shape: [3, 2], dtype: "float32" } }, |
| }); |
| ``` |
|
|
