---
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 | Bind key | Logical dtype | Rank | Shape | Description | Presence |
| --- | --- | --- | --- | --- | --- | --- |
| `data` | `x` | `T` | — | — | The input tensor to transpose. | required |

## Outputs

| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
| --- | --- | --- | --- | --- | --- | --- |
| `transposed` | `y` | `T` | same as `data` | — | 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` |

## 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)

## Use with `@huggingface/kernels`

The loader automatically allocates outputs whose metadata it can derive from the manifest contract and this call.

The explicit `outputs` entries provide shape and logical dtype metadata for the results listed below:

- `y`

Each entry either requests an optional result or supplies metadata that cannot be inferred from the inputs.

The `version: 1` option selects the published kernel contract; it is independent of any operator opset, contrib `since_version`, or model 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: [] } }, {
  outputs: { y: { shape: [], dtype: "float32" } },
});
```