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

`ai.onnx`  ·  standard ONNX operator  ·  ONNX opset ≥ 11

## Description

Finds unique values or subtensors along an optional `axis`. Without an axis, `X` is flattened; results are sorted or retain first-occurrence order. Sub-32-bit integers and booleans use lossless widened 32-bit storage. Metadata outputs remain logical int64 but use lossless uint32 storage because all values are bounded by an addressable tensor extent. Callers supply exact data-dependent output shapes. ONNX-permitted uint16, 64-bit, string, and complex inputs remain unsupported because the runtime lacks matching WebGPU storage.

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

## Inputs

| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
| --- | --- | --- | --- | --- | --- | --- |
| `X` | `x` | `T` | — | — | The N-D input tensor from which unique values or subtensors are extracted. When `axis` is omitted, tensors of any rank are flattened in row-major order. | required |

## Outputs

| Name | Bind key | Logical dtype | WebGPU storage | Rank | Shape | Description | Presence |
| --- | --- | --- | --- | --- | --- | --- | --- |
| `Y` | `y` | `T` | runtime-selected; narrow integers and bool use 32-bit slots | derived | — | Tensor containing all unique values or subtensors of X, sorted or in first-occurrence order. | required |
| `indices` | `indices` | `I` | `uint32` | `1` | — | Optional logical int64 indices of each `Y` value or slice's first occurrence in `X`; stored as bounded uint32 values by WebGPU. | optional |
| `inverse_indices` | `inverse_indices` | `I` | `uint32` | `1` | — | Optional logical int64 mapping from each flattened input value, or each input-axis slice, to its corresponding index in `Y`; stored as bounded uint32 values by WebGPU. | optional |
| `counts` | `counts` | `I` | `uint32` | `1` | — | Optional logical int64 occurrence count for each unique value or slice in `Y`; stored as bounded uint32 values by WebGPU. | optional |

## Attributes

Attributes and default values (overridable per request):

| Attribute | Default | Description |
| --- | --- | --- |
| `sorted` | `1` | Whether to sort unique elements in ascending order before output; 1 (default) sorts, 0 retains first-occurrence order. |
| `axis` | — | Optional axis along which unique subtensors are identified. Negative values count from the back; when omitted, the input is flattened. |

## Type constraints

| Variable | Allowed dtypes |
| --- | --- |
| `T` | `float32`, `float16`, `uint32`, `int32`, `int16`, `uint8`, `int8`, `bool` |
| `I` | `int64` |

## 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
- [`unique-axis-compact-sort.wgsl.jinja`](build/webgpu/unique-axis-compact-sort.wgsl.jinja)
- [`unique-axis-dedup.wgsl.jinja`](build/webgpu/unique-axis-dedup.wgsl.jinja)
- [`unique-axis-hash.wgsl.jinja`](build/webgpu/unique-axis-hash.wgsl.jinja)
- [`unique-axis-scatter.wgsl.jinja`](build/webgpu/unique-axis-scatter.wgsl.jinja)
- [`unique-axis.wgsl.jinja`](build/webgpu/unique-axis.wgsl.jinja)
- [`unique-compact-sort.wgsl.jinja`](build/webgpu/unique-compact-sort.wgsl.jinja)
- [`unique-dedup.wgsl.jinja`](build/webgpu/unique-dedup.wgsl.jinja)
- [`unique-hash-build.wgsl.jinja`](build/webgpu/unique-hash-build.wgsl.jinja)
- [`unique-hash-collect.wgsl.jinja`](build/webgpu/unique-hash-collect.wgsl.jinja)
- [`unique-hash-init.wgsl.jinja`](build/webgpu/unique-hash-init.wgsl.jinja)
- [`unique-hash-mark.wgsl.jinja`](build/webgpu/unique-hash-mark.wgsl.jinja)
- [`unique-hash-sort-collected-key-only.wgsl.jinja`](build/webgpu/unique-hash-sort-collected-key-only.wgsl.jinja)
- [`unique.wgsl.jinja`](build/webgpu/unique.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.Unique", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { y } = await kernel({ x: { data: xData, shape: [1] } }, {
  outputs: { y: { shape: [1], dtype: "float32" } },
});
```