Files
wasmtime/crates/wasi-nn
Andrew Brown e9e4afe2c7 wasi-nn: use the MobileNet model instead of AlexNet
The MobileNet model is significantly smaller in size (14MB) than the AlexNet model (233MB); this change should reduce bandwidth used during CI.
2021-04-13 16:00:06 -07:00
..
2021-02-18 14:45:20 -08:00

wasmtime-wasi-nn

This crate enables support for the wasi-nn API in Wasmtime. Currently it contains an implementation of wasi-nn using OpenVINO™ but in the future it could support multiple machine learning backends. Since the wasi-nn API is expected to be an optional feature of WASI, this crate is currently separate from the wasi-common crate. This crate is experimental and its API, functionality, and location could quickly change.

Use

Use the Wasmtime APIs to instantiate a Wasm module and link in the WasiNn implementation as follows:

let wasi_nn = WasiNn::new(&store, WasiNnCtx::new()?);
wasi_nn.add_to_linker(&mut linker)?;

Build

This crate should build as usual (i.e. cargo build) but note that using an existing installation of OpenVINO™, rather than building from source, will drastically improve the build times. See the openvino crate for more information

Example

An end-to-end example demonstrating ML classification is included in examples:

  • tests/wasi-nn-rust-bindings contains ergonomic bindings for writing Rust code against the wasi-nn APIs
  • tests/classification-example contains a standalone Rust project that uses the wasi-nn APIs and is compiled to the wasm32-wasi target using the wasi-nn-rust-bindings

Run the example from the Wasmtime project directory:

ci/run-wasi-nn-example.sh