ai.onnx.Size

ai.onnx · standard ONNX operator · ONNX opset ≥ 13

Description

Returns the total number of elements in a tensor as a logical int64 scalar equal to the product of the input dimensions. The input may have any shape; supported element types are listed below.

See the ONNX Size spec for the reference semantics.

Inputs

Name Logical dtype Rank Shape Description Presence
data T Input tensor of arbitrary shape. required

Outputs

Name Logical dtype WebGPU storage Rank Shape Description Presence
size S uint32 0 [] Logical int64 scalar holding the total number of elements in the input tensor; WebGPU emits the bounded value as uint32. required

Type constraints

Variable Allowed dtypes
T float32, float16, int32, uint32, int16, int8, uint8, bool
S int64

Files

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.Size", { version: 1 });
const { size } = await kernel({ data: { data: dataData, shape: [] } });
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Requires WebGPU support. See the compatibility table.