ai.onnx.SplitToSequence

ai.onnx · internal tensor lowering (non-standard) · reviewed against ONNX opset 11

Description

Support status: the standard ONNX SplitToSequence operator is not implemented because this kernel ABI exposes tensors rather than an ONNX sequence value. This internal lowering copies an input into two, three, four, or six caller-shaped tensor outputs and therefore does not implement the standard output_sequence contract; it must not be treated as ONNX SplitToSequence.

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

Inputs

Name	Bind key	Logical dtype	Rank	Shape	Description	Presence
`input`	`input`	`T`	—	—	The tensor to split.	required
`split`	`split`	`S`	—	—	Length of each output slice: a scalar for uniform chunks or a 1-D tensor of per-output lengths.	optional

Outputs

Name	Bind key	Logical dtype	Rank	Shape	Description	Presence
`Y0`	`y0`	`T`	derived	—	First output tensor slice.	required
`Y1`	`y1`	`T`	derived	—	Second output tensor slice.	required
`Y2`	`y2`	`T`	derived	—	Third output tensor slice.	optional
`Y3`	`y3`	`T`	derived	—	Fourth output tensor slice.	optional
`Y4`	`y4`	`T`	derived	—	Fifth output tensor slice.	optional
`Y5`	`y5`	`T`	derived	—	Sixth output tensor slice.	optional

Attributes

Default values (overridable per request):

Attribute	Default	Description
`axis`	`0`	Axis along which to split; negative values count from the back. Accepted range is `[-rank, rank-1]`.
`keepdims`	`1`	Whether to keep the split dimension in the output (default `1`). Ignored when `split` is provided.

Type constraints

Variable	Allowed dtypes
`T`	`float32`, `float16`, `bool`
`S`	`uint32`

Files

metadata.json — kernel metadata (id, digests, provenance)
manifest.json — the op contract (source of truth)
test.json — correctness cases
bench.json — benchmark + tuning cases
split-to-sequence.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:

y0
y1

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.

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

const kernel = await getKernel("webgpu-kernels/ai.onnx.SplitToSequence", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { y0, y1 } = await kernel({ input: { data: inputData, shape: [3, 2] } }, {
  outputs: {
    y0: { shape: [1, 2], dtype: "float32" },
    y1: { shape: [1, 2], dtype: "float32" },
  },
});

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kernel

webgpu

wgsl

apache-2.0

WebGPU

Requires WebGPU support. See the compatibility table.