ai.onnx.Scan

ai.onnx · internal tensor lowering (non-standard) · reviewed against ONNX opset 25

Description

Internal additive prefix-scan lowering over one rank-1 state and one rank-2 input, with forward and reverse traversal. This package does not implement ONNX Scan body-graph semantics.

See the standard ONNX Scan spec for the contract this internal lowering does not implement.

Inputs

Name	Logical dtype	Rank	Shape	Description	Presence
`initial_state`	`T`	`1`	—	Initial rank-1 additive state of shape `[dim]`.	required
`scan_input`	`T`	`2`	—	Rank-2 input of shape `[steps, dim]`. Each row is added to the running state in forward or reverse traversal order.	required

Outputs

Name	Logical dtype	Rank	Shape	Description	Presence
`final_state`	`T`	`1`	same as `initial_state`	Final rank-1 state of shape `[dim]` after all input rows have been accumulated.	required
`scan_output`	`T`	`2`	same as `scan_input`	Inclusive additive prefix results with the same `[steps, dim]` shape as `scan_input`. Reverse traversal still writes each result at its corresponding input row.	required

Attributes

Default values (overridable per request):

Attribute	Default	Description
`reverse`	`0`	When non-zero, the scan input sequence is traversed in reverse order (equivalent to `scan_input_directions=1`); default `0` scans forward.

Type constraints

Variable	Allowed dtypes
`T`	`float32`

Files

metadata.json — kernel metadata (id, digests, per-variant templates, provenance)
manifest.json — the op contract (source of truth)
test.json — correctness cases
bench.json — benchmark + tuning cases
scan-coop-channel.wgsl.jinja
scan-multichunk-apply.wgsl.jinja
scan-multichunk-carries.wgsl.jinja
scan-multichunk-local.wgsl.jinja
scan-prefix-sum.wgsl.jinja

Use with `@huggingface/kernels`

npm install --save-exact @huggingface/kernels@0.0.1-preview.2

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.

import { getKernel } from "@huggingface/kernels";

const kernel = await getKernel("webgpu-kernels/ai.onnx.Scan", { version: 1 });
const { final_state, scan_output } = await kernel({
  initial_state: { data: initial_stateData, shape: [1] },
  scan_input: { data: scan_inputData, shape: [3, 1] },
});

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kernel

webgpu

wgsl

apache-2.0

WebGPU

Requires WebGPU support. See the compatibility table.