ai.onnx.BitShift

ai.onnx · standard ONNX operator · ONNX opset ≥ 11

Description

Performs an elementwise bitwise shift on unsigned integer tensors. X is shifted left or right by the amounts in Y, with the direction controlled by the direction attribute. Supports multidirectional (NumPy-style) broadcasting between X and Y.

See the ONNX BitShift spec for the reference semantics.

Inputs

Name Upstream name Logical dtype Rank Shape Description Presence
x X T Input tensor to be shifted. required
y Y T Tensor specifying the number of bit positions to shift each element of X. required

Outputs

Name Upstream name Logical dtype Rank Shape Description Presence
z Z T derived broadcast result of x and y Output tensor with the same shape as the broadcast result of X and Y. required

Attributes

Attributes and default values (overridable per request):

Attribute Default Description
direction Direction of the bit shift: LEFT shifts bits toward higher significance (increasing value), while RIGHT shifts toward lower significance (decreasing value).

Type constraints

Variable Allowed dtypes
T uint32, uint8

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.BitShift", { version: 1 });
const { z } = await kernel({ x: { data: xData, shape: [1] }, y: { data: yData, shape: [3] } }, {
  attrs: { direction: "LEFT" },
});
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WebGPU

Requires WebGPU support. See the compatibility table.