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

crates/wasi-nn/examples/classification-example/src/main.rs

@@ -0,0 +1,54 @@
+use std::convert::TryInto;
+use std::fs;
+use wasi_nn;
+
+pub fn main() {
+    let xml = fs::read_to_string("fixture/frozen_inference_graph.xml").unwrap();
+    println!("First 50 characters of graph: {}", &xml[..50]);
+
+    let weights = fs::read("fixture/frozen_inference_graph.bin").unwrap();
+    println!("Size of weights: {}", weights.len());
+
+    let graph = unsafe {
+        wasi_nn::load(
+            &[&xml.into_bytes(), &weights],
+            wasi_nn::GRAPH_ENCODING_OPENVINO,
+            wasi_nn::EXECUTION_TARGET_CPU,
+        )
+        .unwrap()
+    };
+    println!("Graph handle ID: {}", graph);
+
+    let context = unsafe { wasi_nn::init_execution_context(graph).unwrap() };
+    println!("Execution context ID: {}", context);
+
+    // Load a tensor that precisely matches the graph input tensor (see
+    // `fixture/frozen_inference_graph.xml`).
+    let tensor_data = fs::read("fixture/tensor-1x3x300x300-f32.bgr").unwrap();
+    println!("Tensor bytes: {}", tensor_data.len());
+    let tensor = wasi_nn::Tensor {
+        dimensions: &[1, 3, 300, 300],
+        r#type: wasi_nn::TENSOR_TYPE_F32,
+        data: &tensor_data,
+    };
+    unsafe {
+        wasi_nn::set_input(context, 0, tensor).unwrap();
+    }
+
+    // Execute the inference.
+    unsafe {
+        wasi_nn::compute(context).unwrap();
+    }
+
+    // Retrieve the output (TODO output looks incorrect).
+    let mut output_buffer = vec![0f32; 1 << 20];
+    unsafe {
+        wasi_nn::get_output(
+            context,
+            0,
+            &mut output_buffer[..] as *mut [f32] as *mut u8,
+            (output_buffer.len() * 4).try_into().unwrap(),
+        );
+    }
+    println!("output tensor: {:?}", &output_buffer[..1000])
+}