ai.onnx.CumProd

ai.onnx · standard ONNX operator · ONNX opset ≥ 26

Description

Computes the cumulative product of input elements along a given axis. By default the product is inclusive (each output element is the product of all preceding elements including itself); setting exclusive to 1 shifts the window so the current element is excluded. Setting reverse to 1 performs the scan in the opposite direction along the axis.

See the ONNX CumProd spec for the reference semantics.

Inputs

Outputs

Runtime arguments

Attributes

Default values (overridable per request):

Type constraints

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
• cumprod-tiled-short-rows.wgsl.jinja
• scan-row-chunked-vec4.wgsl.jinja
• scan-row-chunked.wgsl.jinja
• scan-thread-row.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.CumProd", { version: 1 });
const { y } = await kernel({ x: { data: xData, shape: [3] }, axis: 0 });