| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # ai.onnx.ReverseSequence |
|
|
| `ai.onnx` · standard ONNX operator · ONNX opset ≥ 10 |
|
|
| ## Description |
|
|
| Reverses variable-length sequences in a batch along a time axis. For each batch slice `i`, the first `sequence_lens[i]` elements along `time_axis` are reversed in place; elements beyond that length are copied unchanged. The output has the same shape as the input. |
|
|
| See the [ONNX `ReverseSequence` spec](https://onnx.ai/onnx/operators/onnx__ReverseSequence.html) for the reference semantics. |
|
|
| ## Inputs |
|
|
| | Name | Logical dtype | WebGPU storage | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `input` | `T` | runtime-selected; narrow integers and bool use 32-bit slots | — | — | Input tensor of rank 2 or greater containing the batch of sequences to reverse. | required | |
| | `sequence_lens` | `I` | `uint32` | `1` | — | Logical int64 1-D tensor of shape `[batch_size]` specifying each non-negative sequence length; WebGPU stores it as uint32. | required | |
|
|
| ## Outputs |
|
|
| | Name | Upstream name | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `y` | `Y` | `T` | same as `input` | same as `input` | Output tensor with the same shape as the input, with each sequence reversed up to its specified length. | required | |
|
|
| ## Attributes |
|
|
| Default values (overridable per request): |
|
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| | Attribute | Default | Description | |
| | --- | --- | --- | |
| | `batch_axis` | `1` | Axis that represents the batch dimension; must be 0 or 1 (default 1). | |
| | `time_axis` | `0` | Axis that represents the time/sequence dimension to be reversed; must be 0 or 1 (default 0). | |
|
|
| ## Type constraints |
|
|
| | Variable | Allowed dtypes | |
| | --- | --- | |
| | `T` | `float32`, `float16`, `uint32`, `int32`, `int16`, `uint8`, `int8`, `bool` | |
| | `I` | `int64` | |
|
|
| ## Implementation variants |
|
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| One implementation is selected per call from the device capabilities, the request shapes and the dtypes; these notes say what each one covers. |
|
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| - `rankn_output_packed8` — Copies eight half-precision values per invocation using integer storage words, preserving each source payload across reversal and vector boundaries. |
| - `rankn_output_vec4` — Writes four contiguous output values per invocation while independently gathering their reversed source positions. |
| - `rankn_vec4` — Copies aligned inner vectors whose four components share a reversed time slot. |
| - `rankn` — Copies individual elements for shapes that cannot form complete output vectors. |
|
|
| ## 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 |
| - [`reverse-sequence-output.wgsl.jinja`](build/webgpu/reverse-sequence-output.wgsl.jinja) |
| - [`reverse-sequence-vec4.wgsl.jinja`](build/webgpu/reverse-sequence-vec4.wgsl.jinja) |
| - [`reverse-sequence.wgsl.jinja`](build/webgpu/reverse-sequence.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. |
|
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| 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`. |
|
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| 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.ReverseSequence", { version: 1 }); |
| const { y } = await kernel({ |
| input: { data: inputData, shape: [4, 2, 1] }, |
| sequence_lens: { data: sequence_lensData, shape: [2] }, |
| }); |
| ``` |
|
|
