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Add an initial wasi-nn implementation for Wasmtime (#2208)
* Add an initial wasi-nn implementation for Wasmtime This change adds a crate, `wasmtime-wasi-nn`, that uses `wiggle` to expose the current state of the wasi-nn API and `openvino` to implement the exposed functions. It includes an end-to-end test demonstrating how to do classification using wasi-nn: - `crates/wasi-nn/tests/classification-example` contains Rust code that is compiled to the `wasm32-wasi` target and run with a Wasmtime embedding that exposes the wasi-nn calls - the example uses Rust bindings for wasi-nn contained in `crates/wasi-nn/tests/wasi-nn-rust-bindings`; this crate contains code generated by `witx-bindgen` and eventually should be its own standalone crate * Test wasi-nn as a CI step This change adds: - a GitHub action for installing OpenVINO - a script, `ci/run-wasi-nn-example.sh`, to run the classification example
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‎.github/actions/install-openvino/README.md‎

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# install-openvino
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A GitHub action to install OpenVINO from a package repository. This is only necessary for `wasi-nn` support but there
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are enough steps here to package the functionality separately and avoid cluttering the CI.
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Future improvements:
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- make this installer work for different OS/distributions (e.g. https://docs.openvinotoolkit.org/latest/openvino_docs_install_guides_installing_openvino_windows.html)
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- it would be nice to output the install directory (i.e. `/opt/intel/openvino`)

‎.github/actions/install-openvino/action.yml‎

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name: 'Install OpenVINO'
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description: 'Install OpenVINO binaries from a package repository; this is significantly faster than building from source'
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inputs:
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version:
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description: 'The release version of OpenVINO to install'
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required: false
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default: '2020.4.287'
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runs:
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using: composite
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steps:
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- run: ${{ github.action_path }}/install.sh ${{ inputs.version }}
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shell: bash

‎.github/actions/install-openvino/install.sh‎

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#!/bin/bash
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set -e
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# Retrieve OpenVINO checksum.
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wget https://apt.repos.intel.com/openvino/2020/GPG-PUB-KEY-INTEL-OPENVINO-2020
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echo '5f5cff8a2d26ba7de91942bd0540fa4d GPG-PUB-KEY-INTEL-OPENVINO-2020' > CHECKSUM
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md5sum --check CHECKSUM
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# Add OpenVINO repository (deb).
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sudo apt-key add GPG-PUB-KEY-INTEL-OPENVINO-2020
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echo "deb https://apt.repos.intel.com/openvino/2020 all main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2020.list
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sudo apt update
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# Install OpenVINO package.
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sudo apt install -y intel-openvino-runtime-ubuntu18-$1

‎.github/workflows/main.yml‎

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runs-on: ubuntu-latest
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env:
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RUSTDOCFLAGS: -Dbroken_intra_doc_links
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OPENVINO_SKIP_LINKING: 1
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steps:
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- uses: actions/checkout@v2
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with:
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--all \
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--exclude lightbeam \
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--exclude wasmtime-lightbeam \
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--exclude wasmtime-wasi-nn \
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--exclude peepmatic \
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--exclude peepmatic-automata \
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--exclude peepmatic-fuzzing \
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CARGO_VERSION: "+nightly"
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RUST_BACKTRACE: 1
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# Build and test the wasi-nn module.
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test_wasi_nn:
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name: Test wasi-nn module
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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with:
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submodules: true
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- uses: ./.github/actions/install-rust
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with:
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toolchain: nightly-2020-08-25
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- run: rustup target add wasm32-wasi
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- uses: ./.github/actions/install-openvino
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- run: ./ci/run-wasi-nn-example.sh
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env:
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RUST_BACKTRACE: 1
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# Verify that cranelift's code generation is deterministic
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meta_determinist_check:
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name: Meta deterministic check
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--all \
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--exclude lightbeam \
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--exclude wasmtime-lightbeam \
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--exclude wasmtime-wasi-nn \
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--exclude peepmatic \
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--exclude peepmatic-automata \
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--exclude peepmatic-fuzzing \

‎.gitmodules‎

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[submodule "WASI"]
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path = crates/wasi-common/WASI
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url = https://github.com/WebAssembly/WASI
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[submodule "crates/wasi-nn/spec"]
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path = crates/wasi-nn/spec
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url = https://github.com/WebAssembly/wasi-nn

‎Cargo.lock‎

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‎Cargo.toml‎

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wasmtime-obj = { path = "crates/obj", version = "0.21.0" }
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wasmtime-wast = { path = "crates/wast", version = "0.21.0" }
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wasmtime-wasi = { path = "crates/wasi", version = "0.21.0" }
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wasmtime-wasi-nn = { path = "crates/wasi-nn", version = "0.21.0", optional = true }
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wasi-common = { path = "crates/wasi-common", version = "0.21.0" }
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structopt = { version = "0.3.5", features = ["color", "suggestions"] }
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object = { version = "0.22.0", default-features = false, features = ["write"] }
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lightbeam = ["wasmtime/lightbeam"]
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jitdump = ["wasmtime/jitdump"]
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vtune = ["wasmtime/vtune"]
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wasi-nn = ["wasmtime-wasi-nn"]
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# Try the experimental, work-in-progress new x86_64 backend. This is not stable
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# as of June 2020.

‎ci/run-experimental-x64-ci.sh‎

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--features experimental_x64 \
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--all \
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--exclude wasmtime-lightbeam \
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--exclude wasmtime-wasi-nn \
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--exclude peepmatic \
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--exclude peepmatic-automata \
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--exclude peepmatic-fuzzing \

‎ci/run-wasi-nn-example.sh‎

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#!/bin/bash
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# The following script demonstrates how to execute a machine learning inference using the wasi-nn module optionally
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# compiled into Wasmtime. Calling it will download the necessary model and tensor files stored separately in $FIXTURE
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# into $TMP_DIR (optionally pass a directory with existing files as the first argument to re-try the script). Then,
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# it will compile the example code in crates/wasi-nn/tests/example into a Wasm file that is subsequently
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# executed with the Wasmtime CLI.
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set -e
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WASMTIME_DIR=$(dirname "$0" | xargs dirname)
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FIXTURE=https://gist.github.com/abrown/c7847bf3701f9efbb2070da1878542c1/raw/07a9f163994b0ff8f0d7c5a5c9645ec3d8b24024
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# Inform the environment of OpenVINO library locations. Then we use OPENVINO_INSTALL_DIR below to avoid building all of
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# OpenVINO from source (quite slow).
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source /opt/intel/openvino/bin/setupvars.sh
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# Build Wasmtime with wasi-nn enabled; we attempt this first to avoid extra work if the build fails.
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OPENVINO_INSTALL_DIR=/opt/intel/openvino cargo build -p wasmtime-cli --features wasi-nn
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# Download all necessary test fixtures to the temporary directory.
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TMP_DIR=${1:-$(mktemp -d -t ci-XXXXXXXXXX)}
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wget --no-clobber --directory-prefix=$TMP_DIR $FIXTURE/frozen_inference_graph.bin
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wget --no-clobber --directory-prefix=$TMP_DIR $FIXTURE/frozen_inference_graph.xml
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wget --no-clobber --directory-prefix=$TMP_DIR $FIXTURE/tensor-1x3x300x300-f32.bgr
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# Now build an example that uses the wasi-nn API.
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pushd $WASMTIME_DIR/crates/wasi-nn/examples/classification-example
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cargo build --release --target=wasm32-wasi
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cp target/wasm32-wasi/release/wasi-nn-example.wasm $TMP_DIR
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popd
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# Run the example in Wasmtime (note that the example uses `fixture` as the expected location of the model/tensor files).
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OPENVINO_INSTALL_DIR=/opt/intel/openvino cargo run --features wasi-nn -- run --mapdir fixture::$TMP_DIR $TMP_DIR/wasi-nn-example.wasm
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# Clean up.
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rm -rf $TMP_DIR

‎crates/wasi-nn/Cargo.toml‎

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[package]
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name = "wasmtime-wasi-nn"
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version = "0.21.0"
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authors = ["The Wasmtime Project Developers"]
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description = "Wasmtime implementation of the wasi-nn API"
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documentation = "https://docs.rs/wasmtime-wasi-nn"
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license = "Apache-2.0 WITH LLVM-exception"
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categories = ["wasm", "computer-vision"]
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keywords = ["webassembly", "wasm", "neural network"]
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repository = "https://github.com/bytecodealliance/wasmtime"
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readme = "README.md"
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edition = "2018"
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[dependencies]
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# These dependencies are necessary for the witx-generation macros to work:
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anyhow = "1.0"
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log = { version = "0.4", default-features = false }
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wasmtime = { path = "../wasmtime", version = "0.21.0", default-features = false }
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wasmtime-runtime = { path = "../runtime", version = "0.21.0" }
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wasmtime-wiggle = { path = "../wiggle/wasmtime", version = "0.21.0" }
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wasmtime-wasi = { path = "../wasi", version = "0.21.0" }
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wiggle = { path = "../wiggle", version = "0.21.0" }
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# These dependencies are necessary for the wasi-nn implementation:
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openvino = "0.1.5"
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thiserror = "1.0"
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[badges]
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maintenance = { status = "experimental" }

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