--- library_name: kernels license: apache-2.0 tags: - kernel - webgpu - wgsl --- # ai.onnx.GlobalMaxPool `ai.onnx` · standard ONNX operator · ONNX opset ≥ 1 ## Description Applies max pooling across all spatial dimensions of `X`, producing one value per channel. Equivalent to MaxPool with kernel size equal to the full spatial extent of the input; output shape is `(N x C x 1 x ... x 1)`. See the [ONNX `GlobalMaxPool` spec](https://onnx.ai/onnx/operators/onnx__GlobalMaxPool.html) for the reference semantics. ## Inputs | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | | --- | --- | --- | --- | --- | --- | --- | | `X` | `x` | `T` | — | — | Input tensor of shape `(N x C x D1 x ... x Dn)`, where `N` is the batch size and `C` is the number of channels. | required | ## Outputs | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | | --- | --- | --- | --- | --- | --- | --- | | `Y` | `y` | `T` | same as `X` | — | Output tensor of shape `(N x C x 1 x ... x 1)`; the maximum value over each spatial region per channel. | required | ## Type constraints | Variable | Allowed dtypes | | --- | --- | | `T` | `float32`, `float16` | ## Files - [`metadata.json`](build/webgpu/metadata.json) — kernel metadata (id, digests, provenance) - [`manifest.json`](build/webgpu/manifest.json) — the op contract (source of truth) - [`test.json`](build/webgpu/test.json) — correctness cases - [`bench.json`](build/webgpu/bench.json) — benchmark + tuning cases - [`pool-global-reduction.wgsl.jinja`](build/webgpu/pool-global-reduction.wgsl.jinja) - [`pool-global-serial.wgsl.jinja`](build/webgpu/pool-global-serial.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: - `y` 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. ```js import { getKernel } from "@huggingface/kernels"; const kernel = await getKernel("webgpu-kernels/ai.onnx.GlobalMaxPool", { version: 1 }); // Explicit destinations request optional results or supply metadata that cannot be inferred. const { y } = await kernel({ x: { data: xData, shape: [1, 2, 3] } }, { outputs: { y: { shape: [1, 2, 1], dtype: "float32" } }, }); ```