| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # ai.onnx.CausalConvWithState |
|
|
| `ai.onnx` · standard ONNX operator · ONNX opset ≥ 27 |
|
|
| ## Description |
|
|
| Stateful causal 1-D depthwise convolution. It left-pads each channel with `past_state` (or zeros), applies a `(channels, 1, kernel_size)` depthwise convolution and optional SiLU/Swish activation, and returns both the output and the last `kernel_size - 1` values as `present_state`. This package supports float16 and float32 tensors; bfloat16 is unsupported. |
|
|
| See the [ONNX `CausalConvWithState` spec](https://onnx.ai/onnx/operators/onnx__CausalConvWithState.html) for the reference semantics. |
|
|
| ## Inputs |
|
|
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `inputT` | `input` | `T` | `3` | — | Input tensor with shape `(batch_size, channels, length)` in channels-first layout. | required | |
| | `weightT` | `weight` | `T` | `3` | — | Depthwise convolution kernel with shape `(channels, 1, kernel_size)`, matching the ONNX Conv weight layout for `group = channels`. | required | |
| | `biasT` | `bias` | `T` | `1` | — | Optional per-channel bias with shape `(channels)`. | optional | |
| | `pastStateT` | `past_state` | `T` | `3` | — | Carry state from the previous step with shape `(batch_size, channels, kernel_size - 1)`. If omitted, the left padding is zero. | optional | |
|
|
| ## Outputs |
|
|
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `outputT` | `output` | `T` | `3` | same as `inputT` | Convolution output with the same shape as `input`. | required | |
| | `presentStateT` | `present_state` | `T` | `3` | derived | Updated carry state with shape `(batch_size, channels, kernel_size - 1)`, including prior state or zero-padding when the current input is shorter than the state. | required | |
|
|
| ## Attributes |
|
|
| Default values (overridable per request): |
|
|
| | Attribute | Default | Description | |
| | --- | --- | --- | |
| | `activation` | `"none"` | Optional fused activation. `silu` and `swish` are aliases; `none` leaves the convolution result unchanged. | |
|
|
| ## Type constraints |
|
|
| | Variable | Allowed dtypes | |
| | --- | --- | |
| | `T` | `float32`, `float16` | |
|
|
| ## 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 |
| - [`causal-conv-with-state-tiled.wgsl.jinja`](build/webgpu/causal-conv-with-state-tiled.wgsl.jinja) |
| - [`causal-conv-with-state-vec4.wgsl.jinja`](build/webgpu/causal-conv-with-state-vec4.wgsl.jinja) |
| - [`causal-conv-with-state.wgsl.jinja`](build/webgpu/causal-conv-with-state.wgsl.jinja) |
|
|
| ## Use with `@huggingface/kernels` |
|
|
| ```sh |
| npm install --save-exact @huggingface/kernels@0.0.1-preview.3 |
| ``` |
|
|
| Required output shapes and logical data types are inferred from the supplied inputs and attributes; result tensors are allocated automatically. |
|
|
| 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.CausalConvWithState", { version: 1 }); |
| const { outputT, presentStateT } = await kernel({ |
| inputT: { data: inputTData, shape: [1, 1, 2] }, |
| weightT: { data: weightTData, shape: [1, 1, 5] }, |
| }); |
| ``` |
|
|
