---
library_name: kernels
license: apache-2.0
tags:
- kernel
- webgpu
- wgsl
---
# ai.onnx.SpaceToDepth

`ai.onnx`  ·  standard ONNX operator  ·  ONNX opset ≥ 13

## Description

Rearranges blocks of spatial data into depth by moving values from the height and width dimensions into the channel dimension. An NCHW input of shape `[N, C, H, W]` produces an output of shape `[N, C * blocksize * blocksize, H / blocksize, W / blocksize]`.

See the [ONNX `SpaceToDepth` spec](https://onnx.ai/onnx/operators/onnx__SpaceToDepth.html) for the reference semantics.

## Inputs

| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
| --- | --- | --- | --- | --- | --- | --- |
| `input` | `input` | `T` | `4` | — | 4-D input tensor of shape `[N, C, H, W]`. | required |

## Outputs

| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
| --- | --- | --- | --- | --- | --- | --- |
| `output` | `output` | `T` | `4` | derived; see description | 4-D output tensor of shape `[N, C * blocksize * blocksize, H / blocksize, W / blocksize]`. | required |

## Attributes

Attributes and default values (overridable per request):

| Attribute | Default | Description |
| --- | --- | --- |
| `blocksize` | — | Size of the spatial block to collapse into depth; each `blocksize x blocksize` patch of pixels becomes additional channels. |

## Type constraints

| Variable | Allowed dtypes |
| --- | --- |
| `T` | `float32`, `float16`, `int32`, `int16`, `int8`, `uint32`, `uint8`, `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
- [`space-depth-permute.wgsl.jinja`](build/webgpu/space-depth-permute.wgsl.jinja)

## Use with `@huggingface/kernels`

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.

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.SpaceToDepth", { version: 1 });
const { output } = await kernel({ input: { data: inputData, shape: [1, 1, 2, 4] } }, {
  attrs: { blocksize: 2 },
});
```