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WebNN Python API Documentation

Welcome to the WebNN Python API documentation. This library provides Python bindings for the W3C WebNN (Web Neural Network) API, enabling you to build, validate, and execute neural network graphs in Python.

Overview

The WebNN Python API allows you to:

  • Build neural network graphs using a simple, intuitive Python API
  • Validate graphs using the same validation logic as web browsers
  • Convert graphs to ONNX and CoreML formats
  • Execute models on CPU, GPU, or Neural Engine (macOS)
  • Integrate seamlessly with NumPy for tensor operations

Key Features

  • ✓ W3C Standard Compliant - Implements the official WebNN specification
  • ✓ 85 Operations - 89% coverage of WebNN spec operations
  • ✓ Type-Safe - Full type hints for IDE autocomplete
  • ✓ NumPy Integration - Seamless conversion between NumPy arrays
  • ✓ Multiple Backends - ONNX Runtime (CPU/GPU) and CoreML (macOS)
  • ✓ Actual Execution - Run models with real tensor inputs/outputs
  • ✓ Async Support - Non-blocking execution with Python asyncio
  • ✓ Fast - Built with Rust and PyO3 for maximum performance
  • ✓ Cross-Platform - Works on Linux, macOS, and Windows

Quick Example

import webnn
import numpy as np

# Create ML context with device hints
ml = webnn.ML()
context = ml.create_context(accelerated=True)  # Request GPU/NPU if available
builder = context.create_graph_builder()

# Build a simple computation: z = relu(x + y)
x = builder.input("x", [2, 3], "float32")
y = builder.input("y", [2, 3], "float32")
z = builder.add(x, y)
output = builder.relu(z)

# Compile the graph (backend-agnostic)
graph = builder.build({"output": output})

# Execute with actual data
x_data = np.array([[1, -2, 3], [4, -5, 6]], dtype=np.float32)
y_data = np.array([[-1, 2, -3], [-4, 5, -6]], dtype=np.float32)
results = context.compute(graph, {"x": x_data, "y": y_data})

print(results["output"])  # [[0. 0. 0.] [0. 0. 0.]]

# Export to ONNX for deployment
context.convert_to_onnx(graph, "model.onnx")

Installation

From Source

# Clone the repository
git clone https://github.com/tarekziade/rustnn.git
cd rustnn

# Install maturin
pip install maturin

# Build and install
maturin develop --features python

From PyPI

pip install pywebnn

Documentation Structure

Support

License

Apache-2.0 License - See LICENSE for details.