| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # ai.onnx.NonZero |
|
|
| `ai.onnx` · standard ONNX operator · ONNX opset ≥ 9 |
|
|
| ## Description |
|
|
| Returns the indices of all non-zero elements in `X`, in row-major order, as a 2-D tensor of shape `[rank(X), nnz]` where each column is an N-dimensional index. This follows ONNX `NonZero`, including scalar output shape `[0, N]` and logical int64 output type. Because every emitted coordinate is bounded by a WebGPU-addressable input dimension, the backend stores this logical int64 tensor losslessly as uint32. The exact data-dependent output shape must be supplied as output metadata. String, float64, 64-bit input, and other ONNX input types not listed below are unsupported. |
|
|
| See the [ONNX `NonZero` spec](https://onnx.ai/onnx/operators/onnx__NonZero.html) for the reference semantics. |
|
|
| ## Inputs |
|
|
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `x` | `X` | `T` | — | — | Input tensor of any shape whose non-zero element indices are to be found. | required | |
|
|
| ## Outputs |
|
|
| | Name | Upstream name | Logical dtype | WebGPU storage | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | --- | |
| | `y` | `Y` | `I` | `uint32` | `2` | — | Logical int64 tensor of shape `[rank(X), nnz]` containing the multi-dimensional indices of non-zero elements, one index per column. The WebGPU storage representation is uint32 because every coordinate is within an addressable input dimension. | required | |
|
|
| ## 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, 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 |
| - [`nonzero-flag-block-scan-vec4.wgsl.jinja`](build/webgpu/nonzero-flag-block-scan-vec4.wgsl.jinja) |
| - [`nonzero-scatter-vec4.wgsl.jinja`](build/webgpu/nonzero-scatter-vec4.wgsl.jinja) |
| - [`nonzero.wgsl.jinja`](build/webgpu/nonzero.wgsl.jinja) |
| - [`scan-block-prefix-u32.wgsl.jinja`](build/webgpu/scan-block-prefix-u32.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. |
|
|
| 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.NonZero", { version: 1 }); |
| // Explicit destinations request optional results or supply metadata that cannot be inferred. |
| const { y } = await kernel({ x: { data: xData, shape: [4] } }, { |
| outputs: { y: { shape: [1, 2], dtype: "int64" } }, |
| }); |
| ``` |
|
|
