ai.onnx.Squeeze

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

Description

Removes single-dimensional entries from the shape of a tensor. If axes is provided, only those dimensions are removed; if omitted, all size-1 dimensions are removed. Selecting an axis whose size is not 1 raises an error.

See the ONNX Squeeze spec for the reference semantics.

Inputs

Name Bind key Logical dtype WebGPU storage Rank Shape Description Presence
data data T runtime-selected; narrow integers and bool use 32-bit slots Input tensor with at least as many dimensions as the largest axis index specified. required
axes axes S int32 1 Logical int64 1-D tensor of axis indices to squeeze; negative values count from the back, signed axes use int32 WebGPU storage, and omission squeezes all size-1 dimensions. optional

Outputs

Name Bind key Logical dtype Rank Shape Description Presence
squeezed squeezed T Reshaped tensor with the same data as the input but with the specified size-1 dimensions removed. required

Type constraints

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

Files

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:

  • squeezed

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.Squeeze", { version: 1 });
// Explicit destinations request optional results or supply metadata that cannot be inferred.
const { squeezed } = await kernel({ data: { data: dataData, shape: [1, 1, 1, 1] } }, {
  outputs: { squeezed: { shape: [], dtype: "float32" } },
});
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Requires WebGPU support. See the compatibility table.