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WebGPU Plugin Execution Provider

plugin-ep-webgpu/README.md

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WebGPU Plugin Execution Provider

Packaging sources for the ONNX Runtime WebGPU plugin Execution Provider (EP), distributed as a standalone artifact that plugs into an existing ONNX Runtime installation rather than being built into the main onnxruntime binary.

For more information about plugin EPs, see the documentation here.

Contents

  • VERSION_NUMBER — Base plugin EP version consumed by the CI pipeline. The pipeline derives the final package version (release, dev) from this via tools/ci_build/github/azure-pipelines/templates/set-plugin-ep-build-variables-step.yml.
  • MIN_ONNXRUNTIME_VERSION — Minimum compatible core onnxruntime version. Single source of truth shared by all packages built from this directory. The packages do not declare a hard dependency on a specific ONNX Runtime package; instead, this version string is injected into each package's README at build/pack time, and the native plugin EP code validates compatibility at registration time.
  • python/ — Sources and build script for the onnxruntime-ep-webgpu Python wheel. See python/README.md for build and test instructions.
  • csharp/ — Sources and packaging script for the Microsoft.ML.OnnxRuntime.EP.WebGpu NuGet package. See csharp/README.md for build and test instructions.

How it fits together

The plugin EP is built as a shared library (onnxruntime_providers_webgpu.{dll,so,dylib}) by the main ONNX Runtime build (--use_webgpu shared_lib). The resulting binaries are then packaged into:

  • A Python wheel (onnxruntime-ep-webgpu), built from python/.
  • A NuGet package (Microsoft.ML.OnnxRuntime.EP.WebGpu), built from csharp/.
  • A universal package published to the internal ORT-Nightly feed for Windows (x64 / arm64), Linux x64, and macOS arm64.

Packaging is driven by the WebGPU Plugin EP Packaging Pipeline (tools/ci_build/github/azure-pipelines/plugin-webgpu-pipeline.yml), and post-build smoke tests run in the companion WebGPU Plugin EP Test Pipeline (tools/ci_build/github/azure-pipelines/plugin-webgpu-test-pipeline.yml).

Usage

Once installed, the plugin EP is registered at runtime. Example in Python:

python
import onnxruntime as ort
import onnxruntime_ep_webgpu as webgpu_ep

ort.register_execution_provider_library("webgpu", webgpu_ep.get_library_path())

devices = [d for d in ort.get_ep_devices() if d.ep_name == webgpu_ep.get_ep_name()]
sess_options = ort.SessionOptions()
sess_options.add_provider_for_devices(devices, {})
session = ort.InferenceSession("model.onnx", sess_options=sess_options)

See the user-facing package READMEs (bundled into the published packages) for full per-language usage: